Sparse code multiple access (SCMA) is a competitive non-orthogonal multiple access technique for the fifth generation (5G) wireless communications. The SCMA codebook design is a very essential problem. This paper presents a constellation-rotation-based method for designing codebooks for downlink SCMA system. The basic idea is to make the minimum Euclidean distance of the main-constellation as larger as possible, so as to achieve good BER (bit error rate) performance. By constructing proper sub-constellations and Latin matrix, it is able to achieve a good shaping gain. Simulation results show that the proposed SCMA codebooks provides good BER performance in both additive white Gaussian noise (AWGN) and flat fading channels.

The cell-free massive multiple-input multiple-out (MIMO) is an appealing architecture for supporting integrated sensing and communication (ISAC), since its macro diversity can resist the large-scale fading and enhance the detection probability. This letter focuses on user-centric cell-free massive MIMO ISAC system, which is jointly designed with the vector orthogonal frequency division multiplexing integrated signal. We set the sum-rate of the proposed ISAC system as the unified metric, and investigate a joint user scheduling and power allocation scheme. We effectively relax the non-convex resource allocation issue as a linear fractional program. Subsequently, we introduce a low-complexity branch and bound algorithm based on piecewise concave overestimating functions, which can efficiently maximize the sum-rate. Simulation results demonstrate that our proposed system provides superior sum-rate performance than the centralized and classical cell-free counterparts.

Millimeter-wave cell-free and user-centric massive multiple input multiple output (MIMO) systems are promising, due to the reliable ultra-high data rate services. Thus, it is a significant issue to design low-complexity hybrid precoders. In this paper, a simplified sum-mean-square-error (SMSE) is used to design hybrid precoders, based on the array gain and spatial macro-diversity. Then, a heuristic hybrid pre-coding scheme is proposed, with two analog design algorithms that are with or without the knowledge of statistical information. The influence of the imperfect state information of beams is theoretically analyzed, from the instantaneous and ergodic aspects, verifying the robustness of the proposed scheme. Simulation results show that our proposed low-complexity hybrid precoder can be easily realized with acceptable bit error rate (BER) and sum-rate performances, especially when the total transmit power is small.

Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios. This paper proposes a doubly-iterative sparsified minimum mean square error (DI-S-MMSE) turbo equalizer, which iteratively exchanges the extrinsic information between a soft-input-soft-input (SISO) MMSE estimator and a SISO decoder. Our proposed equalizer does not suffer from short loops and approaches the performance of the near-optimal symbol-wise maximum a posteriori (MAP) algorithm. To exploit the inherent sparsity of OTFS system, we resort to graph theory to investigate the sparsity pattern of the channel matrix, and propose two sparsification guidelines to reduce the complexity of calculating the matrix inverse at the MMSE estimator. Then, we apply two iterative algorithms to MMSE estimation, i.e., the Generalized Minimal Residual (GMRES) and Factorized Sparse Approximate Inverse (FSPAI) algorithms. The former is used at the initial turbo iteration, whose global convergence is proven in our equalizer, while the latter is used at the subsequent turbo iterations with the help of our proposed guidelines. Simulation results demonstrate that our equalizer can achieve a good bit-error-rate (BER) performance regardless of the fractional Doppler, and only has a linear order of complexity.

This paper investigates the performances of multiuser downlink opportunistic beamforming (OBF) systems in both Rayleigh and Rician fading channels with the limited feedback information. The statistical characteristics of the equivalent channels show how OBF affects the channel gain. The optimal OBF weight is derived to achieve the maximum capacity. Moreover, the relationship between the capacity and feedback information is analyzed in details. In order to meet different quality of service requirements, we propose two transmission mechanisms that are, respectively, based on maximum-capacity and fairness criterions. Since the closed-form expression of the bit error ratio (BER) is hard to obtain, the upper and lower bounds of BER are derived to approximate the theoretical values. Finally, numerical results are presented to validate our analysis and provide further insights.

Cell-free massive multiple-input–multiple-output (MIMO) network is appealing since the distributed architecture provides spatial diversity to reduce the large-scale fading effect significantly. This article presents a cell-free massive MIMO joint communication and radar (JCR) system, which simultaneously provides qualified communication and robust target detection services. We apply vector orthogonal frequency division multiplexing integrated signals into the proposed cell-free JCR systems, which can achieve well-behaved performances, e.g., high spectral efficiency, superior detection resolution, and accurate latency/Doppler estimation results. Moreover, a low-complexity alternative grid searching method is designed, and the latency and Doppler estimation rates of the proposed system are derived, which gives the lower bounds of estimation performance. The beamforming weights and power allocation results are calculated by using the alternative Lagrange multiplier algorithm. Simulation results demonstrate that the proposed system outperforms the classical centralized JCR case in terms of ambiguity function, bit error rate, false alarm, and detection probabilities, verifying the efficiency of the proposed system.