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Multiple Output-Orthogonal Frequency Division Multiplexing Systems with Carrier Frequency Offset Estimation and Correction

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Multiple Output-Orthogonal Frequency Division Multiplexing Systems with Carrier Frequency Offset Estimation and Correction Journal of Computer Science 10 (2): 198-209, 2014 ISSN: 1549-3636 © 2014 Science Publications doi:10.3844/jcssp.2014.198.209 Published Online 10 (2) 2014 (http://www.thescipub.com/jcs.toc) ANALYSIS OF REDUCTION IN COMPLEXITY OF MULTIPLE INPUT- MULTIPLE OUTPUT-ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING SYSTEMS WITH CARRIER FREQUENCY OFFSET ESTIMATION AND CORRECTION Sabitha Gauni and Kumar Ramamoorthy Department of Electronics and Communication Engineering, Faculty of Engineering and Technology, SRM University, Kattankulathur, India Received 2013-09-10; Revised 2013-09-19; Accepted 2013-11-13 ABSTRACT Orthogonal Frequency Division Multiplexing (OFDM) is a promising research area in Wireless Communication for high data rates. The Multiple Input-Multiple Output (MIMO) technology when incorporated with the OFDM system promise a significant boost in the performance. But, the MIMO- OFDM systems are very sensitive to Carrier Frequency Offset (CFO) as it deteriorates the system performance with the rise of Inter-Carrier-Interference (ICI). A theoretical analysis to evaluate the performance of Orthogonal Frequency Division Multiplexing (OFDM) systems is done here, under the combined influence of phase offset and frequency offset over rayleigh, Weibull and Nakagami fading channels using Binary Phase Shift Keying (BPSK) Modulation. The analysis of increase in Bit Error Rate (BER) caused by the presence of phase offset and frequency offset is evaluated assuming Gaussian probability density function. Hence the estimation and correction of CFO plays a vital role in MIMO- OFDM systems. A method for CFO estimation and correction is analyzed in the MIMO-OFDM system with 16-QAM modulation. In non-pilot-aided systems the CFO acquisition is done using Maximum Likelihood Estimation (MLE) algorithm. The proposed scheme uses the same block for CFO correction of MIMO- OFDM symbols. Since the same phase calculation block is used for the ML estimation along with the acquisition, the computational cost and the complexity of implementation is reduced. Keywords: Carrier Frequency Offset (CFO), Orthogonal Frequency Division Multiplexing (OFDM), Maximum Likelihood Estimation (MLE), Multiple Input Multiple Output (MIMO), Additive White Gaussian Noise (AWGN) 1. INTRODUCTION at the transmitter and receiver in rich scattering environments and at sufficiently high Signal to Noise Orthogonal Frequency Division Multiplexing Ratios (SNR). This results in Multiple-Input Multiple- (OFDM) is used in order to achieve high data rate in Output (MIMO) configuration, which results in Wireless transmission. The use of multiple antennas at increasing the diversity gain on time-variant and both the transmitter and receiver offers higher data rates frequency-selective channels. The features like robustness compared to single antenna systems. The system against multi-path fading, high spectral efficiency, has capacity can be enhanced by the use of antenna arrays made OFDM more popular than the conventional single Corresponding Author: Sabitha Gauni, Department of Electronics and Communication Engineering, Faculty of Engineering and Technology, SRM University, Kattankulathur, India Science Publications 198 JCS Sabitha Gauni and Kumar Ramamoorthy / Journal of Computer Science 10 (2): 198-209, 2014 carrier systems. The MIMO techniques aims to improve modulated. The modulated signal is represented as given the power efficiency by maximizing spatial diversity using in Equation (1): Space-time block codes. MIMO OFDM systems are also sensitive to Carrier 1 N− 1 X() n=∑ X()() k exp i2 π kn / N V n =…− 0,1, .N 1 (1) Frequency Offset (CFO), due to the Doppler shifts or N k= 0 unmatched oscillators and Inter-Carrier-Interference (ICI). The study deals with a new frequency offset Due to the multipath propagation, the signal can be correction scheme for MIMO-OFDM systems. The reflected, diffracted or diffused depending on the nature of frequency acquisition is performed by first estimating the the wave and the obstacle. The channel impulse response frequency offset using some simple comparisons and -jθ(n) then the phase compensation is done in the frequency of a multipath fading channel is modeled as. |h(n) e domain. After simple comparisons in the frequency Assuming that frequency synchronization is achieved at domain, the proposed scheme makes correction to the receiver side, the received signal can be represented in OFDM symbols and compensates using MLE algorithm. the frequency domainis given by Equation (2): MLE algorithm is considered for the frequency correction scheme in the study as it is a highly efficient R(k)= X(k)H(k) + N (2) non-data-aided synchronization method. It shares a common block with the frequency tracking algorithm. where, N is an independent identically distributed (i.i.d) The computational cost and implementation complexity complex Gaussian noise component with zero mean and is reduced to a great extent, by sharing the same phase unit variance. The amplitude of H (k) is modeled as a calculation block with the acquisition step. This scheme rayleigh, Weibull and Nakagami fading distribution with does not require any pilot symbol as it uses the the corresponding PDFs. information brought by OFDM symbols; hence high bandwidth efficiency can be achieved. 3. BER ANALYSIS IN THE PRESENCE OF Gauni et al . (2012) analyzed the OFDM system with Phase and frequency offsets. OFFSETS Qatawneh (2013) compared the different modulation Here BER analysis is discussed in the presence of types based MIMO systems. phase and frequency offsets in detail. Ullah et al . (2012) proposed the design of transmitter using LS code of length 8190 bits which can 3.1. Carrier Frequency Offset measure multipath delay of minimum 0.13 μs and The absolute value of the actual CFO, fε, is either maximum 520 μs. fraction or an integer multiple of subcarrier spacing, ∆f, Ahmed et al . (2010) presented the maximum ∆ likelihood estimation, Bayesian using Jeffrey prior and or the sum of them. If fε is normalized to f, then the the extension of Jeffrey prior information for estimating resulting normalized CFO of the channel can be the parameters of Weibull distribution of life time. generally expressed as in Equation (3): Kumaran et al . (2013) analyzed the performance of f OFDM based bidirectional relay network which employs ε=ε =δ+∈ (3) ∆ Physical Layer Network Coding (PLNC) in the presence f of phase noise. δ ∈≤0.5 Suresh et al . (2012) proposed a novel method to where, is an integer and , where: estimate fine symbol timing error for MB-OFDM based frequency offset UWB system which will be suitable for MB-OFDM ε = receivers for UWB positioning and UWB subcarrier spacing communication. The effect of an integer CFO on OFDM system is different from the influence of a fractional CFO. In the 2. OFDM SYSTEM MODEL event that δ ≠ 0 and ∈ = 0, symbols transmitted on a Consider an OFDM system with N sub-carriers. Let certain subcarrier, e.g., subcarrier k, will shift to another X (k) be the k th OFDM data block to be transmitted with subcarrier Kδ, given by Equation (4): N subcarriers. These data blocks are used to modulate N orthogonal subcarriers. Then, using IDFT input signal is kδ=+δ k mod N − 1 (4) Science Publications 199 JCS Sabitha Gauni and Kumar Ramamoorthy / Journal of Computer Science 10 (2): 198-209, 2014 Since the focus is on the ICI effect, we consider the It has two parameters: A shape parameter, µ and a normalized CFO, ε assuming that no ICI is caused by an second parameter controlling spread, Ω. The PDF of the integer CFO. The nature of ε is considered to be a received signal amplitude in a Nakagami fading channel Gaussian process, statistically independent of the input is given as Equation (8): 2 signal with zero mean and variance σ 3. To obtain the 2m1− 2 probability of error, we consider the PDF of ε as x x 2mm m Equation (5): α α fx() = exp − ∀> x0 (8) Γ()m Ωm Ω 1 ε2 f()ε= exp − ∀ε> 0andf() ε= 0 for ε< 0 (5) σ π σ2 ε 2 2 ε In the Nakagami fading channel, when the fading 3.2. Fading Channels parameter, m = 1 this channel becomes a rayleigh fading The effect of the wireless channel on the channel. The analysis of the system performance with transmitted signals is multiplicative, where the Nakagami fading model is usually more tractable than multiplicative term is assumed to be a complex Rician fading. Gaussian random variable. 4. PERFORMANCE ANALYSIS OF OFDM 3.3. Rayleigh Fading Channel SYSTEMS WITH FREQUENCY OFFSET If the channel coefficient has zero mean, then such a channel is considered as rayleigh fading since the 4.1. BER Expressions for Frequency Offset absolute value of the received amplitude is a rayleigh Due to spectral overlapping, OFDM systems are random variable. sensitive to frequency offset. The orthogonality among The PDF of the received signal amplitude in a the subcarriers is destroyed due to frequency offset, rayleigh fading channel is given by Equation (6): resulting in ICI, this causes degradation in the system performance. Hence estimation of the frequency offset is 2 =x − x ∀> necessary to improve the system performance. f (x)2 exp 2 2 x 0 (6) σα2 σα The recovered signal, dk on subcarrier k is given by Equation (9): σ2 where, x has a rayleigh distribution, is the variance of d= I S (9) received signal amplitude and α is the fading parameter. k 0 k where, Io is the attenuation and phase rotation of the 3.4. Weibull Fading Channel th desiredsignal, Sk is the k transmitted signal. The Weibull distribution is related to a number of From (1), it is clear that the dominant signal on the k th other probability distributions; in particular, it subcarrier is I o Sk. Hence, the magnitude mean of the interpolates between the exponential distribution (k =1) dominant signal on the k th subcarrier is given by and the rayleigh distribution (k = 2).
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