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In this paper, we consider a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system operating over frequency-selective fading channels. We propose a novel scheme for joint carrier-frequency offset (CFO) and channel estimation based on the expectation-maximization (EM) algorithm. Furthermore, the Cramer-Rao bounds (CRBs) for both CFO and channel estimators are exploited to evaluate the performance of the proposed scheme. Computer simulations show that the proposed algorithm achieves almost ideal performance compared with the CRBs for both channel and frequency offset estimations.

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In this study the authors design the optimal rate capacity approaching irregular low-density parity-check code ensemble over binary erasure channel, by using practical semi-definite programming approach. The method does not use any relaxation or any approximate solution unlike previous works. The simulation results include two parts. First, we present some codes and their degree distribution functions that their rates are close to the capacity. Second, the maximum achievable rate behaviour of codes in our method is illustrated through some figures.

In this paper, we propose an Amplify-and-Forward (AF) Orthogonal Frequency Division Multiplexing (OFDM) relay scheme that each relay superimposes its own pilot symbol (PS) such that, individual relay channels can be estimated at the destination. We derive optimal PS designs including both Modification Diagonal Matrix (MDM) and superimposed PS at each relay. These designs are based on channel Mean SquareError (MSE) minimization and Inter-Relay Interference (IRI) elimination, equivalently. It is shown that the number of relays should satisfy the condition, M < N 2(2L−1) , where N and L are the OFDM size and channel order, respectively, and a is the maximum integer part of a. Both Least-Square (LS) and linear minimum MSE channel estimators are derived. Furthermore, the estimator according to uncertain data and approximate computations is derived from an efficient convex optimization problem.