We consider a wireless transmission scheme based on randomized space-time spreading (STS) systems over massive multiple-input multiple-output (MIMO) channels. In the systems, the signals are spread by spreading matrices over time and antenna domains at the transmitter. We propose that the spreading matrices are generated from binary pseudo-noise (PN) and mutual quasi-orthogonal sequences, by partitioning each of the sequences into subsequences treated as real and imagination parts of rows or columns of a spreading matrix. We give a likelihood ascent search (LAS) detector for the STS systems and analyze its computational complexity. The number of multiplication and division operations for the LAS detector does not depend on its iterative process and the number of chips in the bit period. We use Monte Carlo method to solve the bit error rates (BERs) of the STS systems and to count numbers of evaluating bits in the LAS detectors. We choose the system parameters, such as the number of chips in the bit period and the transmission bit rates, according to BER performance and/or the numbers of evaluating bits attained from Monte-Carlo method. With the spreading matrices, the detection, and the suitable parameters, the STS systems achieve BERs near to their single-bit performance, which is the BER of a STS system with a single bit spread by orthonormal sequences at each transmitting antenna. We also compare our systems with V-BLAST-like spatial multiplexing systems with BPSK signals to show the improvement of the BER performance.
['Dianjun Chen']
A Randomized Space-Time Spreading Scheme for Massive MIMO Channels