IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021 1

Waveforms and End-to-End Efficiency in RF Wireless Power Transfer Using Digital Radio Transmitter Nachiket Ayir, Student Member, IEEE, Taneli Riihonen, Member, IEEE, Markus Allen,´ and Marcelo Fabian´ Trujillo Fierro

Abstract—We study radio-frequency (RF) wireless power Internet-of-Things (IoT); such an extreme-scale deployment transfer (WPT) using a digital radio transmitter for applications would certainly require equipping the sensors with replenish- where alternative analog transmit circuits are impractical. An able energy sources. Perhaps an even bigger concern would important parameter for assessing the viability of an RF WPT system is its end-to-end efficiency. In this regard, we present be the looming environmental hazard from the failure to a prototype test-bed comprising a software-defined radio (SDR) recycle IoT-connected disposables, if they comprised ordinary transmitter and an energy harvesting receiver with a low resistive batteries with toxic materials. In recent years, far-field radio- load; employing an SDR makes our research meaningful for frequency (RF) wireless power transfer (WPT) is being studied simultaneous wireless information and power transfer (SWIPT). as a possible solution to these challenges [2]. It would allow We analyze the effect of clipping and non-linear amplification at the SDR on multisine waveforms. Our experiments suggest that powering sensors on demand, and supercapacitors could suf- when the DC input power at the transmitter is constant, high fice for temporary energy storage, thus averting sensors from peak-to-average power ratio (PAPR) multisines are unsuitable becoming hazardous waste after their working life. for RF WPT over a flat-fading channel, due to their low average radiated power. The results indicate that the end-to-end efficiency is positively correlated to the average RF power of the waveform, A. Motivation and that it reduces with increasing PAPR. Consequently, digital modulations such as phase-shift keying (PSK) and quadrature Commercial products for short-range (about an inch) and amplitude modulation (QAM) yield better end-to-end efficiency mid-range (about 1 − 2 m) WPT are already available. While than multisines. Moreover, the end-to-end efficiency of PSK and the former is solely based on magnetic induction coupling, the QAM signals is invariant of the transmission bit rate. An in- latter works on magnetic resonance-based inductive coupling depth analysis of the end-to-end efficiency of WPT reveals that the transmitter efficiency is lower than the receiver efficiency. [3], which relies on resonating a secondary/primary coil for Furthermore, we study the impact of a reflecting surface on WPT. The former comes with its own specifications [4] and the end-to-end efficiency of WPT, and assess the transmission a separate Qi standard [5] adopted by the Wireless Power quality of the information signals by evaluating their error Consortium, while the latter is regulated by the AirFuel vector magnitude (EVM) for SWIPT. Overall, the experimental alliance [6]. Both these competing technologies have their own observations of end-to-end efficiency and EVM suggest that, while employing an SDR transmitter with fixed DC input power, a benefits and limitations [7]–[10]. However, these are devoid of baseband quadrature PSK signal is most suitable for SWIPT at providing mobility or long-range operation. Far-field RF WPT large, among PSK and QAM signals. has the potential to overcome these issues. Index Terms—Wireless power transfer (WPT), simultaneous It has conventionally been believed that RF WPT concepts wireless information and power transfer (SWIPT), RF energy would be unable to deliver sufficient energy to sensors for their harvesting, software-defined radio (SDR), non-linear distortion. operation, due to the undeniably huge over-the-air propagation arXiv:2012.01108v1 [eess.SP] 2 Dec 2020 losses. However, the energy consumption of simple devices for sensing and computing has fallen drastically over the I.INTRODUCTION years in accordance to the Koomey’s law [11], which has HE fifth generation (5G) of mobile communications is reignited the research interest in RF WPT of late. Furthermore, T expected to network trillions of sensors into the so-called the wireless communications research community has been Manuscript received November 16, 2019; revised June 18, 2020 and keen on developing and harnessing simultaneous wireless September 11, 2020; accepted November 30, 2020. Date of publication Month information and power transfer (SWIPT) [12], which allows ??, 2021; date of current version December 3, 2020. This work was partially convenient reuse of spectrum and energy, since many sensors supported by the Ulla Tuominen foundation and the Academy of Finland under the grants 310991/326448 and 315858. (Corresponding author: Nachiket are targets for both transmissions anyway. Ayir). A central research theme in the evolution of WPT and The authors are with the Faculty of Information Technology and Com- SWIPT systems is their power efficiency [2]. This is because munication Sciences, Tampere University, Finland (e-mail: {nachiket.ayir, taneli.riihonen, markus.allen}@tuni.fi, [email protected]). the true technical challenge in WPT is to reduce the required This paper is an expanded version from the IEEE MTT-S International transmission power and overall energy losses enough so that Microwave Symposium (IMS 2019), Boston, MA, USA, June 2-7, 2019. [1] the technology could be considered economically viable, sus- Color versions of one or more of the figures in this article are available online at https://ieeexplore.ieee.org tainable and safe. Likewise, in this work, we study the end- Digital Object Identifier 10.1109/TMTT.XXXX.XXXXXXX to-end WPT efficiency that is the ratio of the direct current 2 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021

1.5 2.5 1m distance 2m distance DC RF PUSRP waveform samples + power Pout data 2 data USB 3.0

1 interface DC DC + 1.5 PPA data Pout USB 2.0

USB Power interface (W) data (mW)

Meter RF out DC out 1

Tx P DC DC supply Rx

DC P Microcontroller 0.5 PUSRP PPA Channel ADC IQ RF-to-DC 0.5 PA PA DC Modulator Pout internal external 0 0 Vector signal transceiver 40 42 44 46 48 50 52 54 56 40 42 44 46 48 50 52 54 56 Software-defined radio USRP gain setting (dB) USRP gain setting (dB) (a) general block diagram (b) measured average transmit RF power (c) measured average harvested DC power

RF Fig. 1. Block diagram of the presented RF WPT system along with an example of measured average transmit RF power (Pout ) and the corresponding average DC harvested DC power (Pout ) for two transmitter–receiver distance values, while varying the gain setting of the USRP. The baseband signal is a 200 kHz DC complex tone with unit amplitude. The total DC power consumption at the transmitter (Pin ) decreases marginally from 12.4 W to 11.4 W as the USRP RF gain setting is increased from 40 dB to 57 dB. The decrease in Pout can be attributed to the saturation of the external PA at higher USRP gain settings.

DC (DC) power harvested at a receiver (Pout ) to all the DC power [30], assiduously summarized in [13]. Besides mathematical DC supplied to a transmitter (Pin ): modeling, the physical design of a rectenna (a portmanteau for the combination of a receiver antenna and an RF diode- DC based rectifier) operating at 2.4 GHz, by designing Schottky Pout ηDC-to-DC = = ηDC-to-RF · ηRF-to-RF · ηRF-to-DC, (1) diode-based voltage rectifiers, is presented in [31], [32]. P DC in The researchers in [13], [19], [20], [29] have reported that which is further split into the RF waveform generation ef- a high peak-to-average power ratio (PAPR) co-phased multi- ficiency at the source transmitter (ηDC-to-RF), the overall RF sine waveform is suitable for transmission over a flat-fading transmission efficiency between antenna connectors (ηRF-to-RF), channel. Most of these studies employ power oscillators or and the power conversion efficiency at the destination energy scientific instruments like vector signal transceivers (VSTs) or harvesting (EH) receiver (ηRF-to-DC). arbitrary waveform generators as transmitters to generate high- PAPR multisine signals. Besides these, switched-mode power B. Literature Review amplifiers, such as current-mode class D converters, could also generate high-PAPR signals in a single-stage transmitter. The large body of recent academic research on WPT, SWIPT, and RF EH has already developed solid theoretical Furthermore, to evade the challenges associated with high- foundations for many key aspects such as rectifier design, PAPR signal generation in a single transmitter, spatial com- waveform design, beamforming algorithms, link-level analy- bining techniques have been explored [33], [34]. While [33] sis, and optimization. Comprehensive surveys of such research determines the phases for multiple distinct sinusoids transmit- works are readily available in [13]–[18]. A major part of the ted by an external source, [34] employs multiple synchronized transmitters to generate a high-PAPR signal at the receiver. current literature focuses mainly on optimizing ηRF-to-DC. For instance, the authors in [19] experimentally deduce that mul- The designs in [13], [19], [20] that lead to the claim tisine signals are optimal for maximizing ηRF-to-DC in compar- of high-PAPR signals being suitable for RF WPT over a ison to orthogonal frequency-division multiplexing (OFDM) flat-fading channel do not demonstrate experimentally the signals, chaotic signals, harmonic signals, etc. effect of the presence of a non-linear power amplifier (PA) Moreover, there are major theoretical contributions on rec- at the transmitter. Though the experimental setup and the tifier modeling, relying on approximations of the Shockley measurement results in [29] capture any potential effect of diode equation [20], [21] or data-based curve-fitting [22] the PA non-linearity, the effect of the PA non-linearity and of to mathematically characterize the non-linearity of diodes. ηDC-to-RF are not explicitly studied and highlighted. The idea of rectifier modeling has been further extended to Ideally, efficient diode-based EH would require the received address problems like waveform design under the availability signals to have as high PAPR as possible (with an impulse of complete [20], [23] or limited [24], [25] knowledge of the train being the ultimate waveform), while in applications such channel state information (CSI). as SWIPT, employing alternative RF signal generation and In the complete absence of CSI, the impact of fading and amplification architectures is challenging in the first place. transmit diversity on signal design for WPT has been studied Moreover, the problem with maximizing PAPR is that it in [26]. Additionally, in the case of imperfect CSI, the problem disregards the limited output range of the digital-to-analog of simultaneously powering multiple non-linear rectifier-based converter (DAC) of any digital transmitter, as well as the non- sensors with RF power by employing robust beamforming at linearity which arises as the amplitude peaks of a high-PAPR the transmitter was studied in [27], [28]. waveform drive the PA into saturation, thereby distorting the The research on communication and signal design for op- shape of the actual transmitted waveform. With their envelope timizing the end-to-end transmission in RF WPT is already a distorted, the multisine waveforms might not remain optimal flourishing area with many noteworthy contributions [20], [29], for WPT anymore. In literature, there is thus clearly a dearth AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 3 of research studies that explain the impact of using a practical and transceiver adapter module (NI 5791R), as transmitters. software-defined radio (SDR) transmitter for RF WPT. Contrarily, a USRP is a de-facto standard prototyping device In literature, we encounter several studies that have devel- for wireless test-beds as it is both low-cost and represents the oped WPT [31], [35]–[41] and SWIPT [42], [43] test-beds for limitations of a practical transmitter in a real-world setup. varying purposes, from simply charging a battery to studying It should be noted that the observation in the second point the effects of the factors influencing system performance. above is in contrast with that in [29], where the researchers However, this research direction is still fairly in its nascent show that CSI-adaptive multisine waveforms outperform PSK stage and provides opportunity for original contributions. and QAM in terms of the energy harvested. The reasons for this disparity are explained in Section IV in detail, but briefly C. Contributions and Organization stated they stem in general from the differences in receiver- side equipment and resistive loads in the two research setups. All the aforementioned test-beds operate in the 915 MHz or The remainder of this article is organized as follows. In 2.4 GHz industrial, scientific, and medical (ISM) bands using the next section, we study the various impairments, which the a Universal Software Radio Peripheral (USRP) or the rather multisine signals suffer from before transmission from a digital expensive VST hardware. For our study, we employ a USRP radio transmitter, through theoretical analysis and simulations. while operating in the 863 − 873 MHz European unlicensed Next, we present the details of the test-beds employed in this band1. The block diagram of our test-bed along with a few study in Section III. We conducted experiments employing our preliminary results is presented in Fig. 1. These would be test-beds to determine η , η , η and EVM explained in detail in Sections III and IV, respectively. DC-to-DC DC-to-RF RF-to-RF for different test waveforms. The details of these experiments The novel contributions of this paper are as follows. and their key observations are reported in Section IV. Finally, 1) We present an original GNU Radio-based prototype test- we present the conclusions of this work in Section V. bed for end-to-end (i.e., DC-to-DC) RF WPT comprising a USRP transmitter and an energy harvesting receiver II.DIGITAL TRANSMISSIONOF MULTISINE SIGNALS with a diode-based rectifier as illustrated in Fig. 1. Our Let us analyze the detrimental effects of the practical lim- test-bed allows us to study ηDC-to-DC and ηDC-to-RF, while investigating the use of a digital radio for transmission. itations of digital transmission on multisine signals following DC stage-by-stage the common IQ modulator architecture. 2) We show that with a fixed Pin and the resistive loads in the orders of a few hundred ohms, ordinary communi- Without loss of generality, we assume that the digital cation signals such as PSK and QAM are more suitable baseband signal to be transmitted is a complex-valued N-tone for RF WPT than the co-phased multisine waveforms multisine waveform given by with high PAPR that are tailored for EH only. Under the x(t) = xI(t) + j xQ(t) same P DC constraint, when the transmitter is a digital in N IQ modulator (which is the case with an SDR), we X = A exp (j 2πf t + j φ ) , (2) observe that the high-PAPR multisines get either clipped n n n n=1 or severely distorted by the digital radio transmitter, thus diminishing their efficacy in RF WPT. where An, fn and φn represent the amplitude, the baseband 3) Our experimental results demonstrate the novel fact that frequency and the phase of the nth tone, respectively. A typically receiver efficiency is better than transmitter multisine waveform can approximate (or, if N → ∞, exactly represent) any periodic signal x(t), when interpreted as a efficiency (ηRF-to-DC > ηDC-to-RF). Moreover, while the latter remains roughly constant for given amplifier gain Fourier series, which justifies the assumption. setting so that it can be improved only by transmitter The process of generation of an analog RF signal from design, the former can be enhanced during operation by discrete IQ samples is well known, so we avoid explaining it delivering more power to the energy harvesting receiver here. While generating an RF waveform from discrete multi- through beamforming or reducing propagation distance. sine samples, a digital radio introduces non-linear distortions 4) We evaluate the effect of imperfections in an SDR in the signal. These distortions would alter the shape (and transmitter on the quality of RF signal transmission hence the PAPR) of the modulated RF waveform owing to in terms of error vector magnitude (EVM). The study which it may not remain suitable for RF WPT over a flat- reveals that DAC clipping deteriorates the EVM of fading channel. The sources of the distortions, in a digital multisine signals as their amplitude increases. On the radio, include the DAC and amplification by the internal PA other hand, the EVM for communication signals turns (PAI). The former introduces distortion due to clipping effect out to be fairly invariant of their bit rate. and quantization, while the latter introduces distortion because of non-linear input–output transfer characteristics. Let us study With respect to the first point above, the other known test- these through mathematical analysis and simulations. beds for RF WPT/SWIPT such as [31], [42] (and also [29] partly) employ expensive scientific instruments, such as Na- tional Instruments (NI) FlexRIO (PXI-7966R) FPGA module A. Clipping and Limited Resolution in Digital-to-Analog Con- version 1The conclusions of this work are applicable to other ultra-high frequency (UHF) bands as well, whenever bandwidth is not large. Some related results Any DAC employed in digital radios has inherently some for the American 902 − 928 MHz ISM band have been presented in [1]. limited output range for discrete IQ samples; we set it to ±1 4 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021 herein without loss of generality. Consequently, any sample of We consider the following assumptions2 to simplify the xI(t) or xQ(t) with magnitude greater than one is truncated to analysis: An = A, fn = nf0, φn = φ. With these assumptions, one. The resultant analog baseband waveform generated from we can express the co-phased N-tone multisine in (2) as the digital baseband samples is of the form N X x(t) = A · exp (j φ) exp (j 2πnf0t) , (10) x¯(t) =x ¯I(t) + j x¯Q(t) (3) n=1 for which in each branch (B ∈ {I, Q}) where the in/quadrature-phase (I/Q) components are given as  sin (Nπf t) · cos ((N + 1)πf t + φ) +1, xB(t) ≥ 1, x (t) = A · 0 0 , (11)  I sin (πf t) x¯B(t) = −1, xB(t) ≤ −1, (4) 0  sin (Nπf0t) · sin ((N + 1)πf0t + φ) xB(t), otherwise. xQ(t) = A · . (12) sin (πf0t) The bar signifies the clipping of the original waveform which It is evident from (11) that the exact time instants at which would generate non-linear distortion. The resultant RF wave- x (t) gets clipped can only be found by numerical analysis, form is given by I which is as follows. Without any loss of generality, consider √ x (t) 0 < t ≤ xˆ(t) = 2 Re {x¯(t) · exp (j 2πfc t)} , (5) a single period of the multisine waveform I from T , where T = 1/f0. Let t1, t2, . . . tM be the time instants where Re{.} represents the real part of a complex number and between which xI(t) is clipped and not clipped by the DAC, fc denotes the carrier frequency of the transmission. such that 0 < t1 < t2 < ··· < tM < T . Thus, we have Whether the analog baseband waveform would get clipped ( 1, t ∈ [0, t1], [t2, t3],..., [tM ,T ], or not depends on the amplitudes of the individual baseband |x¯I(t)| = sinusoids (An), for which we can find two cases as follows. |xI(t)|, t ∈ (t1, t2), (t3, t4),..., (tM−1, tM ). 1) Case I: If An, n = 1, 2,...,N, are low enough to (13) prevent clipping, then the shape and, hence, the PAPR of From (13), it is clear that the peak power of x¯I(t) would be the waveform remain intact. In this case, the resultant RF one and that its average power can be computed as waveform before power amplification is given by 1 h E{x¯2(t)} = t + (t − t ) + ... + (T − t )+ (14) I T 1 3 2 M √ N X Z t2 Z t4 Z tM xˆ(t) = 2 An cos (2π(fc + fn) t + φn) (6) 2 2 2 i xI (t)dt + xI (t)dt + ... + xI (t)dt . n=1 t1 t3 tM−1 with a peak power of The peak power and average power for x¯Q(t) can be computed  N on similar lines and are, thus, omitted here. The total average = 2 (P A )2, when for n = 1, 2,...,N,  n=1 n power of a complex signal x¯(t) is given by 2  {xˆ (t)}peak φn ≡ −2π(fc + fn) tpeak mod 2π, N 2 2 2  P 2 E{|x¯(t)| } = E{x¯I (t)} + E{x¯Q(t)}. (15) < 2 ( n=1 An) , otherwise, (7) On simplifying (5) and considering a clipped baseband where {.}peak represents the peak value of a real signal and multisine waveform, the RF signal can be expressed as t is the peak time instant at which all the phases align. peak √   The corresponding average power is given by xˆ(t) = 2 · cos(2πfct) · x¯I(t) − sin(2πfct) · x¯Q(t) , (16) N 2 2 X 2 and the corresponding average power is given as E{xˆ (t)} = E{|x(t)| } = An. (8) 2 2 n=1 E{xˆ (t)} = E{x¯ (t)} − E{2 · sin(4πfct) · x¯I(t)x ¯Q(t)} 2 2 We observe that the average power of the RF waveform + E{cos(4πfct) · (¯xI (t) − x¯Q(t))}, (17a) depends on the amplitudes of the individual tones. Thus, lowering A to avoid clipping and preserve the PAPR will which becomes n ( lower the average radiated RF power. The PAPR of the RF = E{x¯2(t)}, φ = π , E{xˆ2(t)} 4 (17b) waveform in this case becomes ≈ E{x¯2(t)}, otherwise. 2 (PN A )2 PAPR ≤ n=1 n (9) We observe that the average power of the RF waveform PN 2 n=1 An is approximately equal to the average power of the clipped baseband waveform in general case. It is exactly equal when and depends on the values of φn as specified in (7). 2) Case II: If the values of An are such that the resultant 2The assumptions made in Case II stem from our observation that the amplitude of xB(t) is greater than one, then the DAC limits channel response is essentially frequency-flat in the bandwidth of interest (868 − 872 MHz). This is shown in Fig. 5. For a flat-fading channel, the amplitude of xB(t) to one. In this case, the average power uniform power allocation across the frequencies of a multisine signal is and, consequently, the PAPR of the RF waveform xˆ(t) can be recommended [13]. Hence, we can keep the magnitudes and phases the same computed by piecewise integration. across frequencies to attain a high-PAPR signal. AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 5 PAPR EVM (dB)

A A (a) (b) (c) Fig. 2. Simulation-based plots showcasing the impact of varying the amplitude A of N-tone multisines on the (a) average power E{xˆ2(t)}, (b) PAPR and (c) EVM of the RF waveform (before PAI), for different values of N. the third term in (17a) would integrate to zero. We found that since the clipping is so severe that we are left with a π this case arises when φ = 4 , which yields xI(t) = xQ(T −t). waveform similar to a square wave at baseband irrespec- Due to clipping, the RF waveform would achieve its peak tive of N. Considering multisine signals with same input power at time instants when both |x¯ (t)| = |x¯ (t)| = 1. average power (A = √1 ), we observe that E{xˆ2(t)} I Q N Substituting these in (16), we observe that during those instants decreases with increasing N, with a single sinusoid the RF waveform will have a peak power of four. Thus, for baseband signal achieving the highest E{xˆ2(t)}. the case of a clipped multisine, the PAPR of the RF waveform 2) The variation of PAPR of the RF waveform w.r.t. A is 1 can be computed as shown in Fig. 2b. While A ≤ N , the multisines are not π 4 4 clipped and, thus, PAPR = 2N. In fact, φ = 4 ensures PAPR = ≈ . (18) E{xˆ2(t)} E{x¯2(t)} that clipping does not occur even for A slightly in excess of 1/N; the effect being profound for higher N. Beyond The second source of distortion is the limited resolution of that A, the PAPR begins to increase until it reaches a the DAC which results in quantization errors that may creep in maximum and then tapers off. This observation is against if the fast varying tails of the multisine signals lie in between the expectation that the PAPR would decrease, since the any two quantization levels. onset of clipping restricts the amplitude of xB(t) to one while E{xˆ2(t)} keeps increasing, as seen before. B. Simulations and Observations 3) The above contradiction can be explained as follows. Let us observe the impact of both the aforementioned effects While DAC clipping limits the amplitude of xB(t) on the PAPR, the average RF power, and the error vector mag- to one, the corresponding RF waveform peaks when nitude (EVM) of multisine waveforms before amplification by x¯I(t) =x ¯Q(t) = 1 simultaneously, which occurs after- 4 the PAI, through MATLAB simulations. For the simulations, ward at higher A. Then onwards the peak power value π 3 of the RF waveform stays fixed at four while E{xˆ2(t)} we set An = A and φn = 4 . The results are as shown in Fig. 2. In the subfigures therein, we have plotted the responses keeps increasing and thereby reducing the PAPR. As A of multisines with different N ∈ {1, 2, 4, 8, 16}, for varying goes on increasing further, E{xˆ2(t)} converges to two, 1 and thus from (18), the PAPR converges to two. A. As reference markers, we have used two cases: A = N and A = √1 . The former ensures that x (t) < 1, thus evading 4) Next, we evaluate the impact of DAC clipping and N B any clipping by the DAC, while the latter assures that the quantization on the EVM of the x(t). We adopt the digital samples of all the multisine signals will have the same standard definition of EVM, given as average power. This allows for a fair performance comparison. s 2 The observations, and their explanations, are as follows. E{|x(t) − x¯(t)| } EVM = 2 . (19) 1) Fig. 2a shows the variation of the average RF power. E{|x(t)| } 2 We observe that E{xˆ (t)} does not increase linearly The results are shown in Fig. 2c, where we have plotted 1 with A. The slope of the curve increases up to A = N , the EVM in logarithmic scale for different N and and then decreases. The reduction in the rate of increase varying A. We observe that while A ≤ 1 , the EVM 2 N of E{x¯ (t)} is due to the onset of DAC clipping after is very small. In this region, the only source of error 1 A = N . The inset figure depicts that increasing A is the quantization process. The low EVM suggests that 2 further eventually saturates E{x¯ (t)} to two. This occurs a typical 12-bit DAC is capable of handling the fast varying tails of a multisine signal. Now, for A > 1 , 3The optimal way to obtain an N-tone multisine in a digital radio is by N π the sharp increase in the EVM shows how detrimental is setting φn = 4 , which results in xI(t) = xQ(T −t). Moreover, the wireless channel is essentially almost flat for the signal bandwidth under consideration 4 (cf. Section IV-A). So, we choose a common phase for all the harmonics to As evident in (11), the complexity of xB (t) prevents us from determining obtain a co-phased multisine signal, as recommended in [20], [29], [30]. these time instants theoretically, and so we rely on simulations. 6 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021

Serial data from power meter ZY1273 USB NI Serial data from Power meter PXIe-5645R power meter ZY1273 USB VST Power meter Harvested energy data

USB 3.0 USB 2.0 ZY1273 USB USB 3.0 USB 2.0 Power meter

PAE +43.5 dB PAE Wired channel PA +43.5 dB E Wired channel USB 3.0 +43.5 dB NI NI data RF waveform RF waveform USRP-2900 NI USRP-2900 Digital Digital USRP-2900 RF power baseband DC supply baseband DC supply samples Powercast P2110B DC supply samples meter RF RF (a) test-bed for measuring ηDC-to-DC (b) test-bed for measuring Pout , ηDC-to-RF and the (c) test-bed for measuring Pin EVM Fig. 3. The USRP-based test-beds for evaluating the end-to-end, transmitter and channel efficiencies in RF WPT, and for assessing the quality of the transmitted RF signal in terms of the EVM.

the clipping caused by the DAC. Here again, comparison that the RF signal at the receiver input exceeds the detection based on same input average power reveals that the EVM threshold (−15 dBm) of the energy harvester. An overview of performance degrades with increasing N. the test-bed is shown in Figs. 1a and 3. While the current setup Based on these results, we conclude that, before amplifi- in Fig. 3 appears to be more deconstructed for experimental cation by the PAI, a single-tone signal has both the highest testing, we did so on purpose for evaluating power transfer average RF power and the lowest EVM. Moreover, adding efficiencies as well as the EVM for test waveforms.5 To the more sinusoids to achieve a high-PAPR signal tends to lower best of the authors’ knowledge, our test-bed is the first Linux- the average RF power and also degrades the EVM performance based GNU Radio RF WPT setup in a C++ development due to the clipping effect of the DAC. While lowering A environment. The hardware configurations of the equipment helps to avoid clipping, it eventually results in lower average used in our test-bed are summarized in Table I. transmit power and becomes detrimental to ηDC-to-RF (and thus η ). Most research works referenced in [13] consider DC-to-DC A. Setup for Evaluating the End-to-End Efficiency ηDC-to-DC that the average power of all the multisine waveforms is kept equal for a fair comparison. This does not help much While measuring ηDC-to-DC, the transmitter section consists in practice either since digital waveforms with higher PAPR of a computer, a USB power meter and an SDR. The computer but same average power would be clipped by the DAC. The feeds the digital baseband samples to the SDR through a resultant analog baseband waveforms would neither have the USB 3.0 interface. Moreover, the computer supplies DC power P DC same average power nor the same PAPR. ( USRP) to the SDR, which is measured by the USB power The analog RF waveform generated by the USRP is ampli- meter placed in series between the computer and the SDR. The USB power meter communicates the real-time power fied by the PAI and an external PA (PAE) before transmission over a wireless medium. The detrimental impacts of PAs on consumption data over a USB 2.0 interface to the computer, high-PAPR signals are well known and hence avoided here for where it is logged for further analysis. The SDR generates the modulated RF signal, which is further amplified by the PAE to brevity. While operating the PAI with a large back-off assures RF linear amplification, it also results in lower average radiated Pout , for wireless transmission through a whip antenna. A sep- arate bench DC supply powers the PAE and reports the power RF power. We shall see in Section IV that this eventually DC consumption data (PPA ) to the computer. So, the total power leads to lower ηDC-to-RF, and thus lower ηDC-to-DC. DC DC DC consumption at the transmitter side is Pin = PUSRP + PPA . The receiver side comprises a multi-band whip antenna, an III.TEST-BEDFOR RFWIRELESS POWER TRANSFER off-the-shelf6 RF energy harvester board, with its supporting We now explain the test-bed developed for this work. The circuitry, and a computer. The harvester is equipped with primary purpose of our test-bed is to evaluate ηDC-to-DC of a diode-based rectifier that converts the incident RF energy RF WPT for digital baseband test waveforms. Moreover, we aim to analyze the impact of different stages of power 5A true SWIPT system that characterizes both power and data is the next transfer—RF signal generation, channel propagation, and en- step in our research, wherein we intend on testing both the time-splitting (TS) and power-splitting (PS) approaches at the receiver. In comparison with ergy harvesting—on ηDC-to-DC. Employing an SDR for trans- Fig. 1a, a SWIPT system would incorporate an additional block at the receiver- mission makes our research worthwhile mainly for SWIPT. side which comprises an RF switch (resp. TS) or a power splitter (resp. Thus, we also observe the impact of transmitter imperfections PS). The VST would then be used for information decoding and aiding in computing the bit error rate of the communication link. Alternatively, a SWIPT on the quality of the transmitted signal by evaluating EVM. system can comprise a separate communication receiver and a few energy As the test-bed’s SDR, we have opted for NI USRP-2900, harvesting sensors. While employing a single digital baseband waveform, we where the PA has a tunable gain that can be set with the can examine the efficacy of data communication with the communication I receiver while monitoring the end-to-end WPT efficiency of the sensors. USRP gain setting (G) value, and the maximum output power 6We use off-the-shelf components in our experiments to attain a fair idea is around 20 dBm. We also incorporate a PAE, which ensures about the viability of RF WPT in real-world applications. AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 7

RF (Pin ) into DC. It is accompanied by a discrete analog- TABLE I to-digital converter (ADC) and a microcontroller that con- HARDWARE CONFIGURATION FOR THE TEST-BED. tinuously measures the instantaneous DC voltage across an Component Product details onboard resistor R. The microcontroller continuously reports Lenovo ThinkPad T470p, 32GB RAM, Core Computer the instantaneous DC power data to the computer over a i7 processor, Linux OS, GNU C++ compiler USB 2.0 interface. The computer logs this information to SDR National Instruments USRP-2900 DC USB power meter YZXStudio ZY1273 calculate the average harvested DC power (Pout ) for each transmission interval. Based on these measurements, we com- External PA Mini-Circuits ZHL-4240+ DC DC Antenna Siretta Delta 6A multi-band whip antenna pute ηDC-to-DC = Pout /Pin . The setup for measuring ηDC-to-DC is shown in Fig. 3a. Network analyzer Anritsu S820E RF energy harvester Powercast P2110B [44] ADC Texas Instruments 16-Bit ADS1115 B. Setup for Evaluating the Transmitter Efficiency η DC-to-RF Microcontroller Arduino Nano (Microchip ATmega328) and the EVM of the Transmitted Signal VST National Instruments PXIe-5645R While measuring ηDC-to-RF, the transmitter section up to the RF power meter Rohde & Schwarz NRP-Z11 PAE remains unchanged w.r.t. the above one, and we obtain information on P DC as explained before. The receiver side TABLE II in OPERATIONAL PARAMETERS FOR THE EXPERIMENTS. now comprises a VST and a computer. The PAE output is connected to the VST input by a coaxial cable. The VST Parameter Details captures the RF waveform and provides the digital IQ samples Frequency band 863 − 873 MHz (unlicensed) RF f = 868 to the computer for evaluating the EVM and Pout . Based on Carrier frequency c MHz RF DC Sampling rate 40 MHz these measurements, we compute ηDC-to-RF = Pout /Pin . The Baseband fundamental frequency f = 200 kHz setup for measuring ηDC-to-RF is shown in Fig. 3b. 0 Number of tones in multisine N ∈ {1, 2, 4, 8, 16} ( 2,N = 1 C. Setup for Evaluating the Channel Efficiency ηRF-to-RF PAPR [4, 2N] (0.5 steps), N > 1 RF In order to compute ηRF-to-RF, the measurement data for Pout USRP gain setting G ∈ [40, 57] dB is obtained as explained above. To obtain the measurement PAE gain 43.5 dB RF data for Pin , the receiver side comprises a multi-band whip Resistive load R = 286 Ω antenna, an RF power meter and a computer. The RF power RF meter measures Pin at the antenna port, and reports the data RF RF the cost of a significant performance loss when having multi- to the computer. Thus, we compute ηRF-to-RF = P /P . The in out antenna transmitters or a frequency-selective channel [29]. setup for measuring ηRF-to-RF is presented in Figs. 3b and 3c.

D. Differences With Similar Test-beds IV. EXPERIMENTAL DATA-DRIVEN ANALYSIS OF Our RF WPT test-bed implementation differs from [29], RFWPTEFFICIENCY [31] in being just a simple open-loop system. The prac- In this section, we present the various experimental results tical implementations in [29], [31] comprise CSI feedback and corroborate the observations with theory. The parameters to the transmitter to optimize the weights of the sinusoids for the experiments are summarized in Table II. The range in a multisine waveform, which results in enhanced energy of G is determined by the setup: upper limit by the input harvesting performance. However, the CSI feedback in the threshold power for the PAE (−5 dBm), and lower limit by aforementioned reference implementations is retrieved over DC the minimum acceptable Pout . Our harvester board comprises a wired channel and not wirelessly. In addition, the channel an onboard resistor R = 286 Ω. Thus, it is important to note estimation is performed at the same VST as the transmitter. that all the measurement results presented here are valid for We believe that, although they represent seminal work as good resistance values of the order of a few hundred ohms. The research exercises, the manner in which the feedback was harvester board also comprises a DC-to-DC boost converter, obtained may not be very practical in certain cases. which we do not employ in this work as we focus on accessing The targets of WPT/SWIPT are typically simple sensor the rectifier performance.7 nodes that work on few hundred microwatts’ power or even All the wireless experiments were performed in an anechoic much less. In a practical scenario, such nodes may not be chamber to avoid unnecessary interference with the neighbor- able to perform complex tasks such as channel estimation ing licensed GSM band. We also placed a reflector within the and transmit the CSI back to the transmitter in real time with anechoic chamber to simulate a real wireless multipath propa- their limited energy reserves and computing capability. In view gation environment with two cases. Moreover, the transmitter– of such practical constraints, it is reasonable to pursue the receiver distance (D) and the location of the reflector were approach of operating over a narrow bandwidth (flat-fading also varied to observe different levels of attenuation. The channel) with uniform power allocation for the sinusoids of experiment setup is shown in Fig. 4. the multisine signal, which then eliminates the need for CSI feedback and also performs equally well as the adaptive de- 7The RF-to-DC efficiency of multisine waveforms for varying loads in the signs [20], [29]. However, this simplicity in operation comes at presence of a DC-to-DC boost converter has been studied in [45]. 8 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021

(a) D = 1 m, Anechoic (b) D = 1 m, Case 1 (c) D = 1 m, Case 2 (without reflector) (with reflector) (with reflector)

(d) D = 2 m, Anechoic (e) D = 2 m, Case 1 (f) D = 2 m, Case 2 (without reflector) (with reflector) (with reflector) Fig. 4. Anechoic chamber setup for RF WPT experiments. Fig. 6. Anechoic chamber setup for measuring ηDC-to-DC. The position of the reflecting surface and the transmitter–receiver distance D are varied to experiment with varying channel conditions. 0 Without reflector -5 With reflector: Case 1 only slightly in our frequency band of operation for all the With reflector: Case 2 three cases. Even with best effort, it was not possible to set -10 -20 up any significant frequency selectivity for the channel. -15 -30 In accordance with other research works on this topic [29], -40 -20 [30], we have also chosen similar values for N in our experi- 868 869 870 871 872 ments. Consequently, the maximum bandwidth, of undistorted -25 multisine signals, in our experiments would be 3.2 MHz -30 (868.2 − 871.4 MHz). Accordingly, we have highlighted the channel response from 868 − 872 MHz separately in Fig. 5, -35 where it can be seen to be flat-fading. Consequently, we can -40 Channel response (dB) set the amplitude An and the phase φn to be the same for all the sinusoids of a multisine signal, which concurs with the -45 recommendations in [29], [30], [46] for a flat-fading channel. -50 864 866 868 870 872 B. End-to-End Efficiency of Multisine Waveforms versus G Frequency (MHz) We measured ηDC-to-DC specifically for various multisine Fig. 5. Channel response in the frequency band of operation. signals; their baseband expression is obtained by setting π An = A, fn = n f0 and φn = 4 in (2). Herein we present our observations for N = 1, 2, 4, 8, and 16. Each transmission A. Channel Sounding lasted for around 10 s and we computed the average ηDC-to-DC In order to determine the weighing coefficients of various of each waveform from three such transmissions. components of a multisine signal, we need to determine the The measurement results are shown in Fig. 7. As a reference channel response in the frequency band of operation. For this case, we have chosen a quadrature phase-shift keying (QPSK) purpose, we conducted channel sounding with the aid of a baseband signal√ (two bits per symbol) given by x(t) =x ¯(t) = microwave network analyzer. The setup is similar to the one (±1 ± j)/ 2 that renders a bit rate of 1 Mbps. We measured shown in Fig. 4 with the inclusion of the network analyzer. ηDC-to-DC for six cases in total (D = 1 m and D = 2 m With D = 1 m, we measured the channel response both in for the three cases shown in Fig. 5); however for brevity, we the absence and presence of a reflecting surface. In the latter only present herein the results for the two cases without the case, the position of reflector was also varied, with respect to reflector. Moreover, it is clear from the plots in Fig. 7 that the transmitter and receiver, to ascertain the sensitivity of the the observations for the two propagation distances are similar, channel response to it. The results of the channel sounding and differ only by a constant attenuation factor due to the experiment are presented in Fig. 5. channel being flat-fading. Thus, the forthcoming discussions In Fig. 5, the center curve represents the reference case are common for both the cases. with no reflecting surfaces around the transmitter and the Fig. 7a depicts the end-to-end performance of the multisine receiver. The highest curve portrays the channel response when signals when A = 1. We observe that for N ≥ 2, all the reflector is deliberately placed at the best position with the multisine signals yield almost similar efficiency, which constructive scattering found between the transmitter and the is lower than the efficiency of a single-tone signal. The receiver (Case 1), while the lowest curve shows the channel reference QPSK signal achieves the highest efficiency at all response when the reflector is placed farther than the previous G values. Thus with A = 1, adding more sinusoids gives no position (Case 2) to find worst-case destructive scattering. Yet improvement in performance. This can be attributed to the the primary observation is that the channel response varies heavy clipping at the DAC as N increases, which diminishes AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 9

-40 -40 -40

PAPR A -45 -45 -45 4.0 1 4.5 0.8890 D = 1 m -50 -50 -50 5.0 0.7745 5.5 0.6780 6.0 0.5985 D = 1 m -55 -55 -55 6.5 0.5350 7.0 0.4845 7.5 0.4455 D = 2 m -60 QPSK -60 -60 8.0 0.4165 N=1 8.5 0.3950 D = 1 m: Solid lines N=2 D = 2 m: Dashed lines 9.0 0.3760 -65 -65 -65 D = 2 m N=4 9.5 0.3535 End-to-end efficiency (dB) End-to-end efficiency (dB) N=8 End-to-end efficiency (dB) 9.0 0.3230 8.5 0.2985 -70 N=16 -70 -70 8.0 0.2500 40 42 44 46 48 50 52 54 56 40 42 44 46 48 50 52 54 56 40 42 44 46 48 50 52 54 56 USRP gain setting (dB) USRP gain setting (dB) USRP gain setting (dB) (a) PAPR reduced due to clipping when A = 1 (b)√ PAPR reduced due to clipping when A = (c) varying PAPR with N = 4 1/ N and A = 1/N Fig. 7. Measurement results for the end-to-end WPT efficiency of co-phased N-tone multisine waveforms by varying the amplitude A and the USRP gain setting G. The QPSK reference waveform x(t) = ±0.707 ± 0.707j has an absolute magnitude of one, and thus is immune to DAC clipping.

the average RF power (before the PAI stage) as observed in channel is actually the average RF power that is transmitted the simulation results of Fig. 2a. and not the PAPR of the RF waveform. Moreover, it is evident Next, for a fair comparison, we measured ηDC-to-DC when from Fig. 7c that the maximum ηDC-to-DC is achieved with the baseband test waveforms have same average input power A = 1, when the average RF power is maximal as seen in (A = √1 ) before the PA stage, and when they are unclipped Fig. 2a. This further validates our finding. This is in general N I 1 true for any value of N. (A = N ). We observe in Fig. 7b that in both the cases as N increases, ηDC-to-DC goes on reducing as the high-PAPR We can now present a general analysis of the variation of multisine signals fare far worse than a single-tone signal. In ηDC-to-DC w.r.t. G, which holds true for all the four cases. For G the latter case, we observe that scaling down the amplitude to between 40 dB and 51 dB, ηDC-to-DC (in decibels) rises linearly preserve the shape of the waveform only worsens the ηDC-to-DC for all the test waveforms. This region represents the combined performance, since it reduces the average radiated RF power linear amplification region of PAI and PAE. For G > 51 dB, Finally, for a given N, we examine the effect of varying the the PAI still operates in the linear amplification region, but PAPR of the RF waveform (before the PAI stage) on ηDC-to-DC. the output RF power of the USRP gradually drives the PAE Here we present the observations for N = 4, wherein we vary into saturation, thence saturating ηDC-to-DC. the PAPR from 4 to 8 by successively decrementing A from A remarkable observation is that the QPSK reference signal 1 1 to 4 and the results are shown in Fig. 7c. We observe that, outperforms all the multisine signals at all G values. A QPSK as we try to increase the PAPR from four to 2N, ηDC-to-DC baseband signal has a consistent average RF power of one, as decreases and this is true at the whole range of G. This per (5) and (17), before the PAI stage. Moreover, its average implies that even with the PAPR retained at 2N, the unclipped RF power is greater than that of any multisine with N ≥ 2, multisine signal is not able to achieve higher ηDC-to-DC even at as shown in Fig. 2a, for A ≤ 1. Consequently, the average higher G values. On the contrary, it has the lowest efficiency radiated RF power after amplification by the PAs is also higher at all G values. From these observations, we can conclude for the QPSK signal than for any multisine with N ≥ 2. that reducing the amplitude of the multisine signal to avoid This reaffirms our hypothesis that it is the average radiated clipping and then relying on the PAs for amplification may RF power of the waveform, and not its PAPR, that dominates not be suitable while considering ηDC-to-DC in RF WPT. the end-to-end efficiency of RF WPT when employing a digital The above results show that, for a system employing low radio transmitter over a flat-fading channel. resistive load, employing high-PAPR signals to optimize RF Interestingly, a QPSK baseband signal and a single-tone WPT over a flat-fading channel, as suggested in [2], [13], [31], complex sinusoid signal with A = 1 have the same baseband may not be suitable while employing a digital radio and thence average power, and thus are expected to provide the same for SWIPT too. Let us identify the probable cause for this average radiated RF power, and consequently similar ηDC-to-DC. result based on our simulation results in Fig. 2. If we compare The inferior performance of N = 1 sinusoid signal in Fig. 7 the plots for A = √1 and A = 1 from Fig. 7b, we clearly 4 4 can be attributed to the practical limitations of a USRP. Due to see that A = 1 yields much lesser η than A = √1 at digital pre-processing, its DAC appears to be truncating real 4 DC-to-DC 4 all G values even though we can observe in Fig. 2b that the (and imaginary) components of a complex sinusoidal signal 1 PAPR of the RF waveform is higher with A = 4 than with whose magnitude is closer to one. Thus, the QPSK signal is A = √1 . If we now compare the average RF power of the two unaffected by this limitation of the DAC. Consequently, P RF 4 out cases from Fig. 2a, the explanation seems obvious: It is much for the the reference QPSK signal is higher than for N = 1 1 1 lower with A = than with A = √ . This implies that, while case, which explains the difference in the resultant ηDC-to-DC. 4 4 employing a digital radio, the factor that dominates the end- All the above observations are in contrast with those pre- to-end efficiency performance of RF WPT over a flat-fading sented in literature [29]. The explanation for the disparity is 10 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021

-40 -25 D = 1 m, -8 RF-to-DC -26 -45 D = 1 m -10 -27 1 Mbps QPSK -50 -28 -12 20 Mbps QPSK -29 1 Mbps 8PSK -55 D -14 20 Mbps 8PSK = 1 m 1 Mbps QPSK -30 1 Mbps QPSK 1 Mbps 8QAM 20 Mbps QPSK 20 Mbps QPSK -16 D = 2 m, -31 20 Mbps 8QAM -60 1 Mbps 8PSK 1 Mbps 8PSK RF-to-DC 1 Mbps 16QAM DC-to-RF 20 Mbps 8PSK 20 Mbps 8PSK -32 -18 1 Mbps 8QAM 20 Mbps 16QAM 1 Mbps 8QAM -65 -33 20 Mbps 8QAM Channel efficiency (dB) 20 Mbps 8QAM End-to-end efficiency (dB) D = 2 m -20 1 Mbps 16QAM 1 Mbps 16QAM -34 -70 20 Mbps 16QAM D 20 Mbps 16QAM = 2 m -22 -35 40 42 44 46 48 50 52 54 56 Transmitter & Receiver efficiency (dB) 40 42 44 46 48 50 52 54 56 40 42 44 46 48 50 52 54 56 USRP gain setting (dB) USRP gain setting (dB) USRP gain setting (dB) (a) End-to-end efficiency of information signals for (b) Transmitter and Receiver efficiency of informa- (c) Channel efficiency of information signals for varying USRP gain settings tion signals for varying USRP gain settings varying USRP gain settings Fig. 8. Experimental observations for the end-to-end efficiency, transmitter efficiency and channel in RF WPT in terms of G for QPSK, 8-PSK, 8-QAM and 16-QAM information signals at different bit rates. The corresponding receiver efficiency is computed using (1). The efficiencies were evaluated for D = 1 m and 2 m, in the absence of a reflector.

TABLE III baseband QPSK, 8-PSK, 8-QAM and 16-QAM signals are 1, OPERATIONAL PARAMETERS FOR THE EXPERIMENTS. 1, 0.75, and 0.56, respectively. The operational parameters are Parameter Details presented in Table III. Given a 10 MHz channel bandwidth, Frequency band 863 − 873 MHz (unlicensed) we limit the bit rate of the baseband signals to 20 Mbps. Carrier frequency fc = 868 MHz The results for the η performance of 1 Mbps and Sampling rate 40 MHz DC-to-DC Baseband signals QPSK, 8-PSK, 8-QAM, 16-QAM 20 Mbps bit rate communication signals for varying G are Bit rate 1 Mbps, 20 Mbps, 40 Mbps depicted in Fig. 8a. We observe that for a given bit rate, say USRP gain setting G ∈ [40, 57] dB 1 Mbps, ηDC-to-DC reduces as the modulation order increases. So, a QPSK-modulated signal has better ηDC-to-DC than 8-PSK as follows. The end-to-end efficiency of RF WPT is affected and 8-QAM signals, which in turn fare better than a 16-QAM by numerous parameters such as the average power and PAPR signal. In addition, we observe that for a given baseband of the waveform, CSI conditions, waveform shape, practical modulation, ηDC-to-DC is invariant of the bit rate. In general, limitations of the SDR hardware, the energy harvester circuit ηDC-to-DC increases linearly with G in the combined linear and the load. While we focus on ηDC-to-DC, the work in [29] region of amplification of the two PAs, up to G = 51 dB, focuses on ηRF-to-RF and ηRF-to-DC. Consequently, we have the and then ηDC-to-DC begins to saturate as the PAE operates in DC the saturation region. Moreover, the observations are similar Pin fixed in our work, while [29] keeps the RF transmit power the same. Thus, the radiated power levels are very different for both propagation distances. in the two works. Moreover, the researchers in [29] use a fabricated rectifier circuit, while we utilize an off-the-shelf evaluation board for an EH receiver. Apart from these, the D. Transmitter, Channel and Receiver Efficiency of Commu- other important difference is the load. The results in [29] are nication Signals versus G based on a resistive load of 10 kΩ and 12 kΩ, while we Let us now examine the end-to-end efficiency of commu- employ R = 286 Ω. The impact of variation in the resistive nication signals in detail by evaluating η , η and load on η of RF WPT is presented in [46], where the DC-to-RF RF-to-RF RF-to-DC η separately. First, we determine η by employing observations for η concur with our observations for RF-to-DC RF-to-DC RF-to-DC the VST as a receiver as explained Section III-B, with the test- multisine efficiencies with low resistive load. bed depicted in Fig. 3b. The results are shown in Fig. 8b. The The observation that a QPSK signal provides even better maximum attainable η is about −8.7 dB (13.5%). The η than multisine signals pits them as a potential candi- DC-to-RF DC-to-DC remaining observations are similar to those in Section IV-C. date waveform for SWIPT. Based on these results, we continue η our further analysis of RF WPT considering only baseband Afterwards, we evaluate RF-to-RF (path loss) in RF WPT. η signals that are already being used for information transfer. The test-bed for evaluating RF-to-RF is presented in Fig. 3c. The results are presented in Fig. 8c. We observe that all the signals experience similar path loss even at 20 Mbps bit rate, C. End-to-End Efficiency of Communication Signals versus G which corresponds to 10 MHz, 6.67 MHz and 5 MHz band- In what follows, we concentrate on QPSK, 8-PSK, 8-QAM width for undistorted QPSK, 8-PSK/8-QAM and 16-QAM and 16-QAM signals and determine their performance in signals, respectively. This observation concurs with the one RF WPT/SWIPT.√ In particular,√ the constellation√ √ points of in Section IV-A about the channel being almost flat-fading. 8-QAM are ±j/ 2, ±1/ 2, and ±1/ 2 ± j/ 2. These However, once the PAE starts operating in the saturation mode digital baseband signals are defined such that they avoid any (G > 51 dB), we observe deviations in ηRF-to-RF, significantly clipping by the DAC. Thus, the average power of the digital so for the 20 Mbps QPSK signal. This arises because of the AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 11 non-linear distortions that lead to spectral regrowth and subject F. Efficiency versus Transmitter–Receiver Distance and Vary- the signals to a frequency-selective channel. ing Channel Conditions Based on the available measurement data, we compute the Next, we observe the impact of varying D on the various corresponding ηRF-to-DC using (1) and the results are as shown efficiencies of an RF WPT system at once. We measured DC RF RF DC in Fig. 8b. The primary observation, which has been missed Pin ,Pout ,Pin and Pout for a 1 Mbps QPSK waveform by in the previous literature, is that ηRF-to-DC < ηDC-to-RF. For varying the position of the receiver from D = 1 m to 3.5 m, D = 1 m, the maximum ηRF-to-DC is around −7 dB (about and the results are depicted in Fig. 10. In accordance with the RF 8 20%), when Pin ≈ 6 dBm . A remarkable observation in observation in [48], we notice that ηRF-to-DC is dependent on RF RF Fig. 8b is that, in the linear amplification region, the slopes of D, and hence on Pin . As Pin reduces, ηRF-to-DC decreases as the curves for D = 1 m and 2 m are dissimilar. This implies well. Fig. 10 provides us with a view of the viability of RF that ηRF-to-DC of the employed harvester increases rapidly at WPT. We observe that for a distance of 3 m, our test-bed is RF lower Pin levels. The remaining observations are similar to able to harvest about 0.1 mW of DC power, while for 1 m those in Section IV-C. The receiver efficiency is similar to the separation the harvested power is higher than 1 mW. Figure 10 RF observations in [13] for the given Pin levels. However, due also provides us with a visual depiction of the relation between to the high path losses, characterization of ηRF-to-DC at higher the three efficiencies: ηRF-to-RF  ηDC-to-RF < ηRF-to-DC. RF Pin is not feasible in our RF WPT experiments and needs to Let us now observe the impact of a reflecting surface on be studied separately. ηDC-to-DC performance in RF WPT for all the six cases shown Another significant observation is that although the digital in Fig. 6 and discussed in Section IV-A. We employ a 1 Mbps samples of QPSK and 8-PSK waveforms have the same aver- QPSK-modulated signal for this experiment. In Fig. 11, we age power, the former has superior ηDC-to-DC (resp. ηDC-to-RF, observe a significant improvement of about 3 − 4 dB in ηRF-to-DC) performance for most G values. Conversely, 8-PSK ηDC-to-DC for Case 1 and a deterioration of about 2 − 3 dB and 8-QAM waveforms have similar ηDC-to-DC (resp. ηDC-to-RF, is seen in Case 2 when D = 1 m. For D = 2 m, an ηRF-to-DC) performance at all G values, even though the digital improvement of around 4 − 5 dB is observed in Case 1 with samples of the latter have lower average power. These obser- respect to the reference case, while the diminution in Case 2 is vations can again be attributed to the practical limitations of approximately 1 dB. The observations suggest that a properly DC the USRP in handling the real (and imaginary) values of a positioned reflector can effectively double Pout in RF WPT. complex sample, whose magnitude is close to one. In a dynamic real-world scenario, multiple such reflecting Overall, from the foregoing experiments, we observe that surfaces, both fixed and mobile, may be present between the transmitter and the energy harvesting receiver, and thus their a QPSK modulated signal provides the best ηDC-to-DC perfor- mance at all bit rate and G values, and thus it seems to be the impact on ηDC-to-DC must be taken into account while designing most suitable choice from the RF SWIPT perspective so far. the optimal waveforms for RF WPT/SWIPT.

G. Performance Analysis of PSK and QAM Modulations Apart from the experiments, utilizing a digital radio for E. End-to-End Efficiency of Communication Signals versus WPT is worthwhile mainly if we target SWIPT. Consequently, Transmission Bit Rate we ought to determine the impact of varying G and bit A common observation in Fig. 8 is that all the efficiencies rates on the quality of the transmission signals to find the are invariant of the transmission bit rate. Thus, let us explore modulation that would be suitable for information transfer. To do so, we have measured the EVM of communication further the dependence of ηDC-to-DC to the information signals’ bit rate. The setup employed is the one in Section IV-B, and the signals. The operational parameters are those noted in Ta- operational parameters are as presented in Table III, with the ble III, unless mentioned otherwise. For each of these measure- 7.2 × notable changes being in the values of the bit rate (100 kbps, ments, we captured million samples (6 repetitions 50 × 200 kbps, 320 kbps, 500 kbps, 1 Mbps, 2 Mbps, 3.2 Mbps, batches/repetition 24000 samples/batch) of each transmitted 5 Mbps, 10 Mbps and 20 Mbps) and G (40 dB, 45 dB, 50 dB signal and computed the EVM. It must be noted that the and 55 dB). The results are shown in Fig. 9. oscillator at the USRP transmitter is not extremely stable resulting in carrier frequency offset (CFO), which needs to The primary observation is that the end-to-end efficiency be compensated before computing the EVM. The justification of all the information signals is indeed fairly independent of for the observations in Fig. 12 is based on the analysis of the transmit their bit rate. It must be noted that we examine the constellation of the captured samples (not shown herein). bit rate here. The harvested energy, however, can be strongly 1) EVM versus G: The EVM response of 1 Mbps and dependent on the receive data rate [47]. The other observations 20 Mbps information signals for varying G is shown in are similar to those in Fig. 8a. These observations lead us to Fig. 12a. To begin, we observe that, except for the QPSK- conclude that for SWIPT, the choice of bit rate (for digitally modulated signals, all the other information signals have modulated transmission) would not be limited by η . DC-to-DC similar EVM irrespective of the bit rates. Let us present a brief explanation for these EVM curves. 8In comparison, the rectennas in [31] and [32] offer maximum efficiency In the case of QPSK signals, the effect of CFO is observed RF of about 12% and 15% respectively, for Pin ≈ −20 dBm at 2.4 GHz. to be more prominent in the samples for 20 Mbps signal, such 12 IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. XX, NO. XX, MONTH 2021

-35 QPSK 40 dB 45 dB 50 dB 55 dB 8PSK 40 dB 45 dB 50 dB 55 dB 40 8QAM 40 dB 45 dB 50 dB 55 dB -40 -40 DC-to-RF 16QAM 40 dB 45 dB 50 dB 55 dB D = 1 m 30 -45 PDC -45 in 20 PRF -50 DC-to-DC RF-to-RF out PRF -50 10 in -55 PDC

Power (dBm) out -60 0 -55 RF-to-DC Case 1 End-to-end efficiency (dB) End-to-end efficiency (dB) -65 Without reflector -10 D = 2 m Case 2 -60 -70 0.1 0.2 0.5 1 2 5 10 20 1 1.5 2 2.5 3 3.5 40 42 44 46 48 50 52 54 56 Bit rate (Mbps) Distance (m) USRP gain setting (dB)

Fig. 9. End-to-end efficiency of information sig- Fig. 10. Evaluation of the RF WPT performance of Fig. 11. End-to-end efficiency of a QPSK modu- nals for varying bit rates. a QPSK-modulated signal for varying D, in terms lated signal for varying channel conditions. of various efficiencies.

30 30 1 Mbps QPSK 1 Mbps 8QAM QPSK 50dB 8QAM 50dB 20 Mbps QPSK 20 Mbps 8QAM QPSK 55dB 8QAM 55dB 25 1 Mbps 8PSK 1 Mbps 16QAM 25 8PSK 50dB 16QAM 50dB 20 Mbps 8PSK 20 Mbps 16QAM 8PSK 55dB 16QAM 55dB

20 20

15 15 EVM (%) EVM (%)

10 10

5 5

40 42 44 46 48 50 52 54 56 0.1 0.2 0.5 1 2 5 10 20 USRP gain setting (dB) Bit rate (Mbps) (a) EVM of information signals for varying USRP gain settings (b) EVM of information signals for varying bit rates Fig. 12. The measured EVM of the communication signals at different bit rates and G values. The complex baseband symbols were captured by the VST, and compensated for the CFO, before evaluating the EVM. Overall, the QPSK signal yields the lowest EVM for any given bit rate and G. that it could not be completely compensated, thus resulting This occurs due√ to the distinct√ power levels 8-QAM symbols: in higher EVM. Overall, for the 1 Mbps QPSK signal, the 0.5 (when ±1/ 2 or ±1j/ 2), while one for others. Con- EVM is fairly low for G ≤ 50 dB with a slight increase sequently, before the PAI stage, the RF signals correspond- after that, while for the 20 Mbps QPSK signal, the EVM ing to symbols with higher average power will have higher stays consistently low till G = 45 dB and increases rapidly amplitude. So long as the RF signals are linearly amplified thereafter. The higher EVM for the 20 Mbps QPSK signal (G < 51 dB), the EVM√ will be low.√ Thereafter, the RF signals can attributed to the increased wideband noise that creeps in corresponding to ±1/ 2 ± 1j/ 2 already saturate the PAI at higher G values. due to their higher amplitudes, while the others continue to be Coming to 8-PSK signals, we observe in Fig. 12a that the linearly amplified. At the baseband, this translates to a gradual EVM remains high until G = 51 dB and reduces marginally shifting of the 8-QAM constellation towards the 8-PSK one. thereafter. The constellation plots reveal that the reason for Nonetheless, for G > 55 dB, the RF signals corresponding the high EVM is the distinct rotation of different constellation to all the 8-QAM symbols eventually saturate the PAI. This points. We observe that for G < 51 dB, symbols within a explains the increase in EVM for G between 50–55 dB and quadrant tend to merge due to CFO. This impact of the CFO the subsequent flattening of the curve as seen in Fig. 12a. starts reducing gradually thereafter due to which the symbols Finally, the case of 16-QAM signals is similar to 8-QAM, begin to realign with the standard 8-PSK constellation, and as can be observed from Figs. 12a. The corresponding expla- the EVM decreases. nation is same as well. If we now focus on the overall plot, Next, for 8-QAM signals, we observe that the EVM initially we observe that for any G, the QPSK-modulated signal yields increases gradually with G up to 50 dB, and then shows a the lowest EVM for both the transmission bit rates. sharp increase. As G increases, we notice that the 8-QAM 2) EVM versus Bit Rate: Next, we evaluated the EVM constellation begins to shift towards an 8-PSK constellation. performance of the information signals by varying their bit AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 13

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Mitcheson, “Prototyping and experi- mization techniques, software-defined radios, simul- mentation of a closed-loop wireless power transmission with channel taneous wireless information and power transfer. acquisition and waveform optimization,” in Proc. IEEE Wireless Power Transfer Conference (WPTC), May 2017. [32] A. Georgiadis, G. Vera Andia, and A. Collado, “Rectenna design and optimization using reciprocity theory and harmonic balance analysis for Taneli Riihonen (S’06–M’14) received the D.Sc. electromagnetic (EM) energy harvesting,” IEEE Antennas and Wireless degree in electrical engineering (with distinction) Propagation Letters, vol. 9, pp. 444–446, May 2010. from Aalto University, Helsinki, Finland, in August [33] Y. Ma, Z. Luo, C. Steiger, G. Traverso, and F. Adib, “Enabling 2014. He is currently an Assistant Professor (tenure deep-tissue networking for miniature medical devices,” in Proc. track) at the Faculty of Information Technology Conference of the ACM Special Interest Group on Data Communication and Communication Sciences, Tampere University, (SIGCOMM), Aug. 2018. [Online]. Available: http://doi.acm.org/10. Finland. He held various research positions at Aalto 1145/3230543.3230566 University School of Electrical Engineering from [34] A. J. S. Boaventura, A. Collado, A. Georgiadis, and N. B. Carvalho, September 2005 through December 2017. He was a “Spatial power combining of multi-sine signals for wireless power Visiting Associate Research Scientist and an Adjunct transmission applications,” IEEE Transactions on Microwave Theory Assistant Professor at Columbia University in the and Techniques, vol. 62, no. 4, pp. 1022–1030, Apr. 2014. City of New York, USA, from November 2014 through December 2015. [35] E. Davut, O. Kazanci, A. Caglar, D. Altinel, M. B. Yelten, and G. K. He has been nominated eleven times as an Exemplary/Top Reviewer of Kurt, “A test-bed based guideline for multi-source energy harvesting,” various IEEE journals and is serving as an Editor for IEEE WIRELESS Proc. 10th International Conference on Electrical and Electronics in COMMUNICATIONS LETTERS since May 2017. He has previously served as Engineering , Nov. 2017. an Editor for IEEE COMMUNICATIONS LETTERS from October 2014 through [36] M. Cansiz, D. Altinel, and G. K. Kurt, “Effects of different modulation January 2019. He received the Finnish technical sector’s award for the best techniques on charging time in RF energy-harvesting system,” IEEE doctoral dissertation of the year and the EURASIP Best PhD Thesis Award Transactions on Instrumentation and Measurement, vol. 69, no. 9, pp. 2017. His research activity is focused on physical-layer OFDM(A), multi- 6904–6911, Sep. 2020. antenna, relaying and full-duplex wireless techniques with current interest in [37] S. Nikoletseas, T. P. Raptis, A. Souroulagkas, and D. Tsolovos, “Wireless the evolution of beyond 5G systems. power transfer protocols in sensor networks: Experiments and simula- tions,” Journal of Sensor and Actuator Networks, vol. 6, no. 2, Apr. 2017. [38] K. Li, C. Yuen, and S. Jha, “Fair scheduling for energy harvesting WSN Markus Allen´ was born in Ypaj¨ a,¨ Finland, on in smart city,” in Proc. 13th ACM Conference on Embedded Networked October 28, 1985. He received the B.Sc., M.Sc. Sensor Systems, Nov. 2015. and D.Sc. degrees in communications engineering [39] H. Dai, X. Wang, A. X. Liu, F. Zhang, Y. Zhao, and G. Chen, from Tampere University of Technology, Finland, in “Omnidirectional chargability with directional antennas,” in Proc. 24th 2008, 2010 and 2015, respectively. He is currently IEEE International Conference on Network Protocols, Nov. 2016. with the Faculty of Information Technology and [40] P. S. Yedavalli, T. Riihonen, X. Wang, and J. M. Rabaey, “Far-field RF Communication Sciences at Tampere University as wireless power transfer with blind adaptive beamforming for Internet of a University Instructor. His current research inter- Things devices,” IEEE Access, vol. 5, pp. 1743–1752, Feb. 2017. ests include software-defined radios, 5G-related RF measurements and digital signal processing for radio transceiver linearization. AYIR et al.: WAVEFORMS AND END-TO-END EFFICIENCY IN RF WIRELESS POWER TRANSFER USING DIGITAL RADIO TRANSMITTER 15

Marcelo Fabian´ Trujillo Fierro achieved the Bach- elor’s degree in electronics at Universidad Mayor in Santiago de Chile, and the M. Sc. in electrical engineering from Tampere University of Technology. From May until November 2018 he worked in the department of Electronics and Communications En- gineering, Tampere University of Technology, Fin- land. His Master degree’s thesis was based in the designing and developing of a research test-bed in the wireless power transfer area by using software defined radios. His areas of interest are a wide scope of different wireless communications technologies such as, cellular networks, IoT, 5G and WPT.