In this paper, we address the problem of joint optimal threshold-based relaying and maximum likelihood (ML) detection in network-coded cooperative systems. The purpose of using threshold-based relaying is to circumvent the impact of error propagation, which could lead to degrading the system diversity. For simplicity, we consider a simple network comprising two source nodes and one relay node. The relay operates in the decode-and-forward (DF) mode and employs binary network coding. The communication between the two source nodes is bidirectional, resulting in a two-way relay channel. We assume binary phase shift keying (BPSK) signaling. For a given log-likelihood ratio (LLR)-based threshold used at the relay, we derive the ML detector at the destination assuming that the destination has full knowledge of the locations of the blocked bits at the relay. We then derive an expression for the corresponding end-to-end (E2E) bit error rate (BER) performance, which is used to find the optimal threshold. We also derive two practical discontinuous transmission detectors at the destination for the purpose of identifying whether the relay is forwarding or not. The performance of one of the detectors is similar to that when the destination knows the locations of the blocked bits, whereas the performance of the other detector suffers some performance degradation. We present several numerical examples that illustrate the efficacy of the proposed scheme as compared to existing schemes.

One of the main challenges in cognitive radio (CR) communications lies in the system robustness to uncertainties. In this paper, we examine the impact of the noise power uncertainty on the performance of various detectors in CR networks. We consider both single and multiple CR nodes. For the single CR case, we compare the performance of the energy and likelihood ratio test (LRT) detectors in the presence of noise uncertainties. It is shown that both detectors perform about the same. We shall also investigate cooperative spectrum sensing based on soft-information combining, where the cooperating CR nodes experience different noise power uncertainties. We then propose a simple detection scheme that is more robust to noise variations and uncertainties than the conventional detection schemes. Numerical results are presented to verify the theory and demonstrate the robustness improvement of the proposed detection scheme.

This paper proposes two blind carrier frequency offset (CFO) estimation schemes for differentially modulated orthogonal frequency division multiplexing (OFDM) systems. The proposed schemes estimate the fractional part of the CFO with only two consecutive OFDM blocks, and they exploit two implicit properties associated with differentially modulated OFDM (DOFDM) systems, i.e., the channel keeps constant over two consecutive OFDM blocks, and the DOFDM systems employ an M-ary phase-shift keying constellation. One of the schemes is based on the finite alphabet (FA) constraint and the other one is based on the constant modulus (CM) constraint. They provide a trade-off between the performance and computational complexity. Furthermore, the FA based scheme can achieve better performance at high signal-to-noise ratios at the expense of some additional computational complexity as compared to the existing CM based subspace scheme. The constrained Cramer-Rao lower bound is also derived. Several numerical examples are presented to validate the efficacy of the proposed schemes.

In this paper, we propose a joint carrier frequency offset (CFO) and channel estimation method for the uplink channel of orthogonal frequency division multiple access (OFDMA) systems. The proposed method includes two steps. In the first step, the variable projection (VP) method based on the least squares (LS) criterion is used for CFO estimation. In each iteration of the VP method, the CFOs and channel coefficients are updated separately, which distinguishes the VP method from an existing non-separated minimum mean square error (MMSE) method in which the CFOs and channel coefficients are treated together as a whole. In the second step, the channel is estimated by employing the robust MMSE method. The simulation results show that, compared with the non-separated MMSE method, the proposed method has faster convergence rate in terms of CFO estimation and achieves better channel estimation performance in most of the cases. The computational complexity of the proposed scheme is also lower than that of the non-separated MMSE method for large number of users at high signal-to-noise ratios.

This paper proposes two blind carrier frequency offset (CFO) estimation schemes for differentially modulated orthogonal frequency division multiplexing (OFDM) systems. The proposed schemes estimate the fractional part of the CFO with only two consecutive OFDM blocks, and they exploit two implicit properties associated with differentially modulated OFDM (DOFDM) systems, i.e., the channel keeps constant over two consecutive OFDM blocks, and the DOFDM systems employ an M-ary phase-shift keying constellation. One of the schemes is based on the finite alphabet (FA) constraint and the other one is based on the constant modulus (CM) constraint. They provide a trade-off between the performance and computational complexity. The constrained Cramer-Rao lower bound is also derived. Several numerical examples are presented to validate the efficacy of the proposed schemes.

This paper proposes an extended Kalman filter (EKF)-based and training symbol aided carrier frequency offset (CFO) estimation scheme for the uplink OFDM systems. Typically, in EKF-based estimation scheme, the measurement equation is a function of the CFO and channel coefficients. Therefore, a vector EKF has to be employed to estimate all the unknowns, which may sometime result in convergence problems. To avoid these problems, the proposed scheme uses a scalar EKF. The user signals are first separated by using multiple-access interference cancellation. Then, the unknown channel coefficients in the measurement equation are replaced with a non-linear function of the CFO so that the scalar EKF can be employed. The observation noise power is analyzed and its approximation is used in the EKF algorithm. Several numerical examples are presented to validate the efficacy of the proposed scheme. It is shown that the proposed scheme can achieve the Cramer-Rao lower bound (CRLB) when the number of users is small, whereas it degrades when the number of users increases. We also compare its computational complexity with several existing schemes.

In this paper, we propose a joint carrier frequency offset (CFO) and channel estimation scheme based on the well known variable projection (VP) method for the uplink channel of orthogonal frequency division multiplexing (OFDM) systems. The CFOs and channel coefficients are estimated by minimizing the least-squares (LS) cost function through a numerical optimization technique. In each iteration, the CFOs and channel coefficients are updated separately, which distinguishes the VP method from an existing method in which the CFOs and channel coefficients are treated together as a whole. We demonstrate through several numerical examples the superiority of the proposed scheme in terms of convergence speed, computational complexity and estimation performance with regard to CFO estimation. However, the proposed scheme does not provide reliable estimation for the channel coefficients. We will investigate this problem further in our future research work.

This paper presents a new blind carrier frequency offset (CFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) systems with constant modulus (CM) signaling. Both single-input single-output (SISO) systems and multiple-input multiple-output (MIMO) systems with orthogonal space-time block coding are considered. The proposed scheme is based on the reasonable assumption that the channel frequency response changes slowly in the frequency domain, which implies that the channel frequency response on two consecutive sub- carriers is approximately the same. Based on this assumption, cost functions are derived in closed-form, which minimize the difference between the signal power of two neighboring subcarriers. The identifiability of the proposed scheme is mathematically proved, which implies that minimizing the derived cost function gives an approximate estimate of the CFO. We demonstrate that the proposed scheme provides an excellent trade-off between complexity and performance as compared to prominent existing estimation schemes.

This paper studies the performance of the concatenation of an outer channel code with an orthogonal spacetime block code (STBC), where the outer code can be a convolutional code (CC) or a trellis-coded modulation (TCM) code. In particular, we derive upper bounds on the bit error rate (BER) for this concatenation scheme with receive antenna selection. In our analysis, we assume that 1) the receiver uses only L out of the available M receive antennas, where, typically, L < M, 2) the selected antennas are those that maximize the instantaneous received signal-to-noise ratio (SNR), 3) the channel state information is perfectly known at the receiver, 4) the underlying channel is fully interleaved, and 5) the underlying orthogonal STBC is full-rate. We derive an explicit upper bound on the BER for the above concatenation scheme for any N, M and L, where N denotes the number of transmit antennas. We show that the diversity order, with antenna selection, is the same as that of the full complexity system, whereas the deterioration in SNR is upper bounded by 10 log10 (M/L) dB. We also derive a tighter upper bound on the BER for the Alamouti scheme when the receiver uses the best antenna, i.e., L = 1. These upper bounds can be extended in a straightforward manner to other types of outer codes and fading channels, including fast, block and slow fading channels. Finally, we present simulation results that validate our analysis.

In this paper, we present a comprehensive performance analysis of combined convolutional coding and space-time block coding with receive antenna selection. In our analysis we assume that the receiver uses only L out of the available M receive antennas, where, typically, L /spl les/ M. The selected antennas are those that maximize the instantaneous received signal-to-noise ratio (SNR). We derive explicit upper bounds on the bit error rate (BER) performance of the above concatenation scheme for any N, M and L, where N denotes the number of transmit antennas. We show that the diversity order, with antenna selection, is maintained as the same as that of the full complexity system, whereas the deterioration in SNR is upper bounded by 10log/sub 10/(M/L) dB. We also derive two tighter upper bound on the BER for generalized orthogonal STBC and the Alamouti scheme when L = 1. Finally, we present simulation results that validate our analysis.

In this paper, we derive upper bounds on the bit error rate performance of orthogonal space-time block codes (STBCs) with receive antenna selection. We show that the diversity order is maintained as that of the full complexity system, whereas the deterioration in SNR is upper bounded by 10 log10(M/L) dB where M is the number of available receive antennas and L is the number of selected antennas.

In this correspondence, we present a comprehensive performance analysis of orthogonal space-time block codes (STBCs) with receive antenna selection. For a given number of receive antennas M, we assume that the receiver uses the best L of the available M antennas, where, typically, L/spl les/M. The selected antennas are those that maximize the instantaneous received signal-to-noise ratio (SNR). We derive explicit upper bounds on the bit-error rate (BER) performance of the above system for any M and L, and for any number of transmit antennas. We show that the diversity order, with antenna selection, is maintained as that of the full complexity system, whereas the deterioration in SNR is upper-bounded by 10log/sub 10/(M/L) decibels. Furthermore, we derive a tighter upper bound for the BER performance for any N and M when L=1, and derive an expression for the exact BER performance for the Alamouti scheme when L=1. We also present simulation results that validate our analysis.