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This paper studies a multiple-input multiple-output (MIMO) broadcast relay channel (BRC), in which a multiple-antenna base station (BS) communicates with multiple-antenna users through an infrastructure-based multiple-antenna relay station (RS). Applying dirty paper coding (DPC) at the BS and linear processing at the RS, our aim is to find the input covariance matrices and the RS beamforming matrix that maximize the system sum-rate. To solve this non-convex problem, a more tractable dual multiple access relay channel (MARC) is investigated and an alternating-minimization algorithm is proposed. Furthermore, the mapping from the resulting covariance matrices for the MARC to the covariance matrices for the BRC is derived. Unlike other existing single-antenna-user schemes, our solution is applicable to a more general network with any number of antennas at the users. Compared with two such single-antenna-user schemes, simulations show that the proposed scheme outperforms the all-pass relay design and performs similarly to the SVD-relay design. Moreover, the proposed design performs close to the sum-rate upper bound with the performance gap decreasing with increasing number of antennas per user. It is also observed that having more antennas at the RS than at the BS is desirable for better system performance. [ABSTRACT FROM PUBLISHER]

This paper presents an analysis of frequency-offset estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Tracking of the frequency offset between a transmitter and a receiver is often aided by transmitting pilots embedded in the data payload of a packet. The extension to multiple-antenna OFDM systems means that spatial beamforming will occur when transmitting pilots from all antennas simultaneously, which can reduce the robustness of frequency-offset estimation. This paper presents a thorough analysis of the spatial beamforming problem, and shows how the spatial correlation of the MIMO channel impacts performance. Simulation results are presented for both synthetic and measured channels, which agree well with the theoretical results. [ABSTRACT FROM AUTHOR]

Full-diversity full-rate (FDFR) space-time codes achieve both high data rate and good reliability at the cost of high decoding complexity. In this paper, we propose a low-complexity MIMO scheme that achieves both full diversity and full rate over flat fading channels for a sufficiently large number of transmit and receive antennas. The proposed scheme is constructed by applying energy spreading transforms (EST's) to multiple data streams and spatially multiplexing the streams to multiple transmit antennas. Simulation results show that the proposed FDFR scheme outperforms the threaded algebraic space-time (TAST) code, which is a FDFR code based on maximum likelihood (ML) detection, when the number of transmit antennas (with the same number of receive antennas) are three and four. However, its detection complexity is only that of a decision-feedback detector. [ABSTRACT FROM PUBLISHER]