Sparse orthogonal matrices are proposed to improve the convergence property of expectation propagation (EP) for sparse signal recovery from compressed linear measurements subject to known dense and ill-conditioned multiplicative noise. As a typical problem, this letter addresses generalized spatial modulation (GSM) in over-loaded and spatially correlated multiple-input multiple-output (MIMO) systems. The proposed sparse orthogonal matrices are used in precoding and constructed efficiently via a generalization of the fast Walsh-Hadamard transform. Numerical simulations show that the proposed sparse orthogonal precoding improves the convergence property of EP in over-loaded GSM MIMO systems with known spatially correlated channel matrices.

The conventional generalized spatial modulation (GSM) simultaneously activates multiple transmit antennas in order to improve the spectral efficiency of the original SM. In this letter, to lessen the hardware burden of the multiple RF chains, we provide a new scheme that is designed by combining the GSM scheme using only two active antennas with quaternary quasi-orthogonal sequences of a length of two. Compared with the other SM schemes, the proposed scheme has significant benefits in average error performances and/or their hardware complexities of the RF systems.

The generalized spatial modulation (GSM) is a new transmission technique that can realize high-performance multiple-input multiple-output (MIMO) communication systems with a low RF complexity. This paper presents an efficient sphere decoding method used to perform the symbol detection for the generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems. In the proposed method, the cost metric is modified so that it does not include the cancellation of the nonexistent interference. The modified cost metric can be computed by formulating a detection tree that has a regular structure representing the transmit antenna combinations as well as the symbol vectors, both of which are detected efficiently by finding the shortest path on the basis of an efficient tree search algorithm. As the tree search algorithm is performed for the regular detection tree to compute the modified but mathematically-equivalent cost metric, the efficiency of the sphere decoding is improved while the bit-error rate performance is not degraded. The simulation results show that the proposed method reduces the complexity significantly when compared with the previous method: for the 6×6 64QAM GSM-MIMO system with two active antennas, the average reduction rate of the complexity is as high as 45.8% in the count of the numerical operations.

In this paper, we propose a new spatial modulation (SM) scheme based on quaternary quasi-orthogonal sequences (Q-QOSs), referred to as Q-QOS-SM. First, the conventional SM and generalized-SM (GSM) schemes are reinterpreted as a new transmission scheme based on a spatial modulation matrix (SMM), whose column indices are used for the mapping of spatial-information bits unlike the conventional ones. Next, by adopting the SMM comprising the Q-QOSs, the proposed Q-QOS-SM that guarantees twice the number of spatial bits at a transmitter compared with the SM with a constraint of transmit antennas, is designed. From the computer-simulation results, the Q-QOS-SM is shown to achieve a greatly improved throughput compared with the conventional SM and GSM schemes, especially, for a large number of the receive antennas. This finding is mainly because the new scheme offers a much higher minimum Euclidean distance than the other schemes.