Enhancing Spectral Utilization by Maximizing the Reuse in LTE Network

Yuva Kumar S.∗, Vanlin Sathya†, Sreenath Ramanath∗ ∗Lekha Wireless Solutions, Bangalore, India † University of Chicago, Illinois, USA. e-mail: ∗[yuva.kumar, sreenath]@lekhawireless.com, †[email protected]

Abstract—Need for increased spectral efficiency is key to D2D pairs. The challenges involved in enabling D2D com- improve quality of experience for next generation wireless ap- munications are resource allocation, interference management, plications like online gaming, HD Video, etc.,. In our work, handovers, power control, session management, etc. There can we consider a LTE Device-to-device (D2D) network where LTE UEs have primary access to the spectrum and D2D pairs have be chances where the spectral reuse (in order to efficiently secondary access. To enhance spectral efficiency, BS can offload offload the BS traffic using D2D) might not be possible beyond the traffic by activating multiple D2D pairs within the serving a certain extent (which will result in more interference to the cell. This ensures that the same radio resource will be reused existing cellular users). To overcome this, it is also possible across the primary LTE UEs and different D2D pairs. In this that one can intelligently allocate the neighboring BS spectrum context, we propose to enable more D2D secondary users in the serving cell, by utilizing neighboring BS spectrum to fairly co- and efficiently reuse the spectrum among D2Ds. Efficient exist with neighboring LTE primary users. We model the system spectrum reuse and co-existence with existing technology is and show via extensive simulations, that the above configuration one of the key research topics. As the mobile operators demand guarantees good throughput for the D2D pairs in the serving cell for more spectrum, telecom regulatory bodies have been while ensuring that the primary LTE throughput demand is not considering release of unused spectrum which has been used compromised. Index Terms—LTE, Device-to-device (D2D), Cognitive Spec- in applications such as radars, television, military applications, trum Access. etc., to operators using cognitive radio technology. During the course of migration there is a need to come up with an alternate I. Introduction mechanism to manage the heavy traffic demands. The work presented in this paper looks into aspects of Due to heavy penetration of smartphone and tablets, we enhancing overall spectral efficiency. It is proposed that the have seen a steady rise in the usage of the mobile applications operator will intelligently use the neighboring BS radio re- (like YouTube, online gaming, Facebook, Netflix, WhatsApp, sources for assigning it to the additional D2D pairs. Here etc.) everyday by the cellular users. This situation forces the neighboring BS will be primary user and additional D2D mobile/cellular operators to increase or reuse the available pairs will be the secondary users. Primary user wouldn’t spectrum. Due to the high capital expenditure (CAPEX) on be affected by secondary user transmission because of the the spectrum used, reusing the existing (available) spectrum relatively large path loss distance. This will boost overall will be a good solution. In this context, one of the feasible system throughput. Hence, our work focuses on reusing the solutions would be to deploy more small cells (like Femto neighboring spectrum to small cell and D2D in such a way that or Pico) under a single Macro base station (BS), which will the overall spectrum efficiency is maximized. As operators are boost the overall spectrum efficiency with the increase of co- reusing the neighboring BS spectrum among small cells and channel co-tier interference. An alternate solution to offload D2Ds with shorter transmission power in the serving cell, it’ll arXiv:1907.05201v1 [cs.NI] 20 Jun 2019 mobile traffic at the Macro BS and boost the spectral usage not interfere with the primary transmissions in the neighboring efficiency is to enable/activate more device to device (D2D) cell. Hence enabling the additional spectrum for small cell and communication within the coverage of the BS. In LTE, D2D D2D in a cognitive manner as discussed will tremendously communications allow UEs to communicate directly without increase the overall spectral reuse efficiency. the intervention of eNodeB (eNB). D2D technology has been This paper is organized as follows. Section II describes suggested as a method by the 3GPP for offloading the users the overview of the state of art in D2D communications. traffic and increase the overall spectral efficiency. It also LTE and D2D co-existence is described in Section III. The has been included in LTE release 12, as a guidance for system is modelled and analyzed in Section IV. Numerical implementing. and simulation results are provided in Section V and the D2D is one of the most promising technology towards 5G conclusions are provided in Section VI. for improving resource utilization, enhancing UE throughput and extending battery lifetime. Due to its short-range com- II. Related Work munication, D2Ds have the potential to reuse the same radio Telecom industry and research community works on boost- resource with different transmission power across different ing the spectrum efficiency by deploying more small cells and D2D under a single Macro BS. To attain a good SINR authors in [1], [2] deployed small cells inside the build- ings by considering Macro-Femto interference. Also, authors proposed an efficient placement and dynamic power control SON (Self organizing Network) algorithm which optimally plan the small cells deployment and dynamically adjusts the transmission power of small cell based on the occupancy of Macro users in the interference zone terrain. To solve this, two Mixed Integer Programming (MIP) methods were proposed, namely: Minimize number of small cells method Fig. 1. Different Region inside a Base Station Cell which guarantees SINR threshold (SINRth) -2dB for all indoor users and optimal small cell power allocation method which guarantees SINRth (- 4 dB) for indoor users with the Macro users SINR degradation lesser than 2dB. The authors in [3] A. System Model consider a scenario having both Uplink (UL) and Downlink (DL) traffic for UEs and D2Ds with the assumption that they In LTE, cellular geographical area of the BS can be divided use different Resource Blocks (RBs) in a given Transmission in to three regions as shown in Fig. 1 and is explained as Time Interval (TTI). They had proposed a semi distributed follows. algorithm for allocation of the RBs. The RBs are divided • Region A: This is defined as the field near to the BS and between D2Ds and UE in a centralized fashion. In which the can be characterized with high power in the Downlink transmission power for D2Ds are assigned in a distributed (DL). manner. Author did not use the same RB to UE and D2D • Region B: This is defined as the field between region A links hence the overall reuse spectrum is not efficient. While and C, where the D2D links can work effectively without solving the RB allocation problem, the authors have assumed much interference to or from UE and BS. that the D2D links transmit at maximum power. Spectral reuse • Region C: This is defined as the field far from BS and can be improved by controlling the transmission power. D2D can be characterized with high power in Uplink (UL) to transmission with dedicated resource and power control is reach BS from the UE. considered in [4]. Inter operator spectrum sharing is a well-studied problem We consider such an LTE network, with a BS serving a in cellular networks [5], [6]. Unlike cellular spectrum sharing, set U of UEs as shown in Fig. 2. UEs will have both UL this work is a first of its kind, which shows the benefits and DL demand. A set L is the number of D2D links having of co-existence of LTE and D2D in a traditional cellular spectral demand. The BS operates in hybrid mode (traditional licensed band system. Fair co-existence among traditional cellular or cognitive) depending on the traffic load. Serving cellular technologies like LTE and Wi-Fi is one of the key BS is centrally coordinated with neighboring BSs. We assume research areas. In this co-existence scenario, co-operative and that a BS has the information such as the number of active non co-operative channel selection, scheduling [7], mobility users, traffic demand, location of the users (using position management [8] are key challenges. In [9] more D2D links reference signal (PRS)), etc. One UE will be served at a given are enabled by utilizing the unlicensed spectrum, appropriately TTI consuming all the RBs. We assume traffic at the BS is designing LTE-Unlicensed (LTE-U) protocol (i.e., changing according to Poisson Point Process (PPP). When traffic at the the listen before talk (LBT) mechanism). But traditionally BS increases, to overcome the resource crunch, D2D links the LTE-U LBT protocol is designed for collision avoidance are initiated in the serving cell by reusing the spectrum of techniques among UEs. Hence, fair co-existence among Wi- the serving BS using cognitive underlay approach. Enabling Fi, LTE-U and D2D is one of the key research challenges. D2D links with the spectrum of the serving BS will be In [10], [11] enabling D2D using underlay approach has been challenging in Region A and Region C due to high DL and well studied. In [12], [13] authors discuss about efficient usage UL interference. Hence, in our work we enable D2Ds with of unlicensed spectrum in a cognitive fashion. An analytical the serving BS spectrum in Region B, where the serving BS model for evaluating the baseline performance of the two interference impact will be less. A utility function defines the different radio access technologies are provided. number of allowed D2D links in the region B, while ensuring In our work, we propose to efficiently reuse the neighboring the quality of link between UE and BS in the serving cell. cell spectrum to enable more D2D links to fairly co-exist with If the number of D2D links permitted by the utility function primary cellular users. is less than the L, database based underlay CR-D2D links are initiated within the serving BS. CR-D2D links will be enabled III. Proposed Work using the available spectrum from the neighboring BSs in any In this section, we first describe the system model and then region (i.e., Region A, B or C). Number of permissible CR- propose the cognitive algorithm for enhancement of spectral D2D links without affecting the link quality of the neighboring reuse in a given TTI. BSs and UEs is determined by the utility function. Fig. 2. D2D System Model with Cognitive Radio Access

B. LTE - D2D Interference Modeling where Gd and Ld are the channel fading for the D2D link, According to [14], interference in large wireless networks Pd is the transmission power of D2D, N is the overall noise can be modelled according to a PPP. In a more generalized in the system, Iu is the interference caused by UE scheduled form, [15] models interference caused by low power nodes in the TTI of interest Id/dr is the interference caused by the such as D2D and homogeneous interference caused by UE as a other D2D links which are scheduled in the TTI of interest. gamma distribution function. Let X denote an exclusion region around the desired receiver with radius R. This region might C. LTE Cognitive Radio D2D Algorithm be quite small, just a few meters in radius, and is designed to avoid the case where the low-power node is co-located with LTE Cognitive Radio D2D (LTE-CR-D2D) algorithm al- the target receiver. Let us consider that the interference is locates maximum number of D2D links which could be associated with a PPP given by ψ and the transmitting power served in a particular TTI. LTE-CR-D2D algorithm ensures of the D2D link is given by Pd, and the transmitter density by throughput fairness to all D2D links. The system throughput λ. The received interference power at the UEs caused by the is a measure of the system performance which changes based low power D2D nodes for a given TTI is given by, on the transmit power of the source and the interference in the X G L P system. For computing the system throughput in each TTI, we I = d d d (1) formulate an utility function as deﬁned in Eqns. (6) and (8). d l(R ) d∈ψ\X d Average rate of a link is given by For interferer d, large-scale fading L follows a log-normal d E{ln(1 + SINR)} (5) distribution with σ, while the small-scale fading distribution Gd is Γ[dg, θg]. l(Rd) is a non-singular path-loss model. Sim- Aim of this utility function is to maximize the logarithmic ilarly, interference caused by the UE to the D2D for a given sum of the average rates of all the D2D links given as TTI is given by: X GuLuPu Maximize log(E{ln(1 + SINRdr )}) (6) Iu = (2) l(Ru) r∈L

Where Gu is the small-scale fading, Lu is the large-scale For a given bandwidth B and spectral eﬃciency η(SINRdr ) r fading, Pu is transmit power. l(Ru) is a non-singular path-loss corresponding to D2D d with SINR SINRdr , using LTE CQI model. table [16] average rate of a link can also be represented as, Then, Signal to Noise plus Interference Ratio (SINR) of R r = Bη (7) UE u is given by: d (SINRdr )

GBS LBS PBS Which gives utility function as SINRu = (3) X N + Id Maximize log(Rdr ) (8) where, GBS and LBS are the channel fading from BS to UE, r∈L PBS is the transmission power of BS, N is the overall noise LTE-CR-D2D algorithm ensures that the maximum number of in the system, Id is the interference caused by all D2D links D2D links are being served in the serving cell. It also ensures which are scheduled in the TTI of interest. that the SINR of the UE doesn’t fall below a permissible limit, SINR of the receiver dr in the D2D link d is given by: which is deﬁned as a function of SINRth.

Gd Ld Pd Overview of the LTE-CR-D2D algorithm is presented in SINRdr = (4) Algorithm 1. N + Iu + Id/dr Algorithm 1 LTE-CR-D2D Algorithm TABLE I imulation parameters Input : PoissonArrival, SINRth S Output : maxUtility, maxUtilitycr, D2Dserved, CRD2Dserved Parameter Value Pmax(Maximum D2D Tx power) 0.1 W 1: L ← PoissonArrival d PBS (BS Tx power) 39.8 W 2: for k =1 to L do Number of UEs in each BS 50 D2D Arrival Rate (λ) in serving BS 20 3: Calculate SNRu using path-loss model Bandwidth used in each BS 10 MHZ (i.e., 50 RB) 4: SINR Calculate serving cell u using (3) UE deployment Random k 5: maxUtility ← utility Traﬃc Downlink 6: if SINRu < SNR − SINRth then LTE Mode FDD 7: break; SINRth 0,2,4,6,8 dB Path loss model for cellular link 128.1 + 37.6log10(d[km]) 8: end if Path loss model for D2D link 148 + 40log10(d[km]) 9: if (maxUtilityk < maxUtilityk−1) then 10: break; Spectrum Efficiency for SINR 8dB th 11: end if 25 w/o CRD2D 12: D2Dserved ← k w CRD2D 13: end for 20 14: if (D2Dserved < L) then 15: for k = D2Dserved+1 to L do 16: Calculate SNRu using path-loss model 15 17: Calculate neighboring cell SINRu using (3) k 18: maxUtilitycr ← utility 10 19: if SINRu < SNR − SINRth then

20: break; No of D2D links got served 21: end if 5 k k−1 22: if (maxUtilitycr < maxUtility ) then 23: break; 0 24: end if 0 10 20 30 40 50 60 70 80 90 100 No Of Trials 25: CRD2Dserved ← k 26: end for Fig. 3. Number of D2D got served in the Serving BS for SINR 8dB 27: end if th

Algorithm 2 Utility Function • Link Blocking Rate, is defined as the number of D2D Input : k Output : utility links not getting served at a given TTI in the serving 1: for r =1 to k do cell. 2: Calculate SINRdr using (4) • Spectrum Efficiency Gain is the attained throughput of 3: Calculate Rdr using (7) the system by spectrum reuse. 4: end for For a Poisson arrival rate of 20, Fig. 3, 4 shows the number Xk of D2D links which reused the spectrum at SINRth 8dB and 5: utility = log(R r ); d 6dB respectively. When the SINR is minimum (for eg: 6 dB) r=1 th 6: return utility; the algorithm allows less number of D2D links to be initiated in the serving BS to prevent the overall system performance degradation. Hence remaining D2D links are blocked (as IV. Experimentation and Results shown in Fig. 6) as it may create interference to the existing UE in the serving cell. When there is a increase in SINRth The system model which is described in Section III is (i.e., 8 dB) we observe more D2D links being served as shown simulated using MATLAB. We consider a system having two in Fig. 3, and consequently lesser D2D links are blocked as BSs which is of 30m height and the coverage of each BS shown in Fig. 5. Figs. 3, 4, 5 and 6 show how the number is 500m. Other simulation parameters are as shown in Table of D2D links reusing the spectrum is influenced by utilizing I. The D2D arrivals are modeled according to a Poisson either only the serving cell spectrum or by utilizing both the Point Process with λ as the arrival rate. SINRth is used as the serving cell spectrum in conjunction with the neighboring permissible threshold for UEs to ensure throughput of the UE spectrum. It can be observed that the D2D links initiated while is maintained. Performance of the spectrum reuse is evaluated utilizing the serving cell spectrum alone are not sufficient to using the following parameters. satisfy the traffic demands. Hence, one can intelligently use • Spectral Efficiency η, is defined as the number of D2D the neighboring cell spectrum to enable more D2Ds links. links which reused the spectrum per TTI. Fig. 7 shows the variation of UEs throughput as we vary CDF of UEs in BS interest Spectrum Efficiency for SINR 6dB th 1 14 w/o CRD2D 0.9 w CRD2D

13 0.8 0dB 0.7 2dB 4dB 12 6dB 0.6 8dB

11 0.5 CDF

0.4 10 0.3

No of D2D links got served 9 0.2

0.1 8 0 5 6 7 8 9 10 11 12 Throughput (bps) 105 7 0 10 20 30 40 50 60 70 80 90 100 No Of Trials Fig. 7. CDF of UEs throughput

Fig. 4. Number of D2D got served in the Serving BS for SINRth 6dB

the SINRth according to Algorithm 1. This SINRth is the

Blocking Rate for SINR 8dB overall permissible degradation of the UEs SINR in each TTI. th 25 w/o CRD2D When the degradation is 0 dB (i.e., no drop in original the w CRD2D SINR of the UE is allowed), very few allowable D2D links

20 are initiated and the UEs throughput is maximum aswell. As the SINRth increases, number of D2D links which can be served also increases and hence UEs throughput decreases 15 due to interference from more D2D links as shown in Fig. 8. As the SINRth varies from 0 dB to 8 dB in steps of 2 dB,

10 UEs throughput decreases gradually for 2, 4, 6 and 8 dB with respect to 0dB. It can be noted that, even if we compromise No of blocked D2D links the SINRu as high as 8 dB, there is no drastic degradation in 5 UEs throughput. As shown in Fig. 8 and 10, an increase in the number

0 of D2D links will increase the overall system performance. 0 10 20 30 40 50 60 70 80 90 100 No Of Trials To visualize the advantage from a cognitive aspect, our LTE- CR-D2D algorithm intelligently reuses the spectrum (radio re-

Fig. 5. D2D Blocking Rate in the Serving BS for SINRth 8dB sources) from the neighboring base station (i.e., inter operator spectrum sharing) and enable more D2D links (as shown in Fig. 10), while at the same time the spectrum is used by the Blocking Rate for SINR 6dB th primary users in the neighboring BS. Since the D2D links are 30 w/o CRD2D faraway from the neighboring base station, it will not impact w CRD2D the neighboring BS throughput (as shown in Fig. 9). 25

20 V. Conclusion

15 In this paper, we contend that cognitive radio based D2D communication has the potential to increase the spectrum

10 eﬃciency and cellular network capacity. CRD2D intelligently No of blocked D2D links uses all the available spectrum inside the serving cell, by

5 utilizing neighboring BS spectrum to fairly coexist with neighboring LTE UEs. Simulation results showed that the spectral reuse and throughput of the overall system increased 0 0 10 20 30 40 50 60 70 80 90 100 No Of Trials signiﬁcantly without compromising on the throughput of the UEs in the serving and neighboring cells. We also analyzed the spectrum eﬃciency of the D2D with and without CR Fig. 6. D2D Blocking Rate in the Serving BS for SINR 6dB th capability. References

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Fig. 10. CDF of CR-D2Ds throughput