Search

In this paper, we aim to solve the multiuser multi-input multi-output (MIMO) downlink beamforming problem where one multi-antenna base station broadcasts data to many users. Each user is assigned multiple data streams and has multiple antennas at its receiver. Efficient solutions to the joint transmit-receive beamforming and power allocation problem based on iterative methods are proposed. We adopt the group maximum signal-to-interference-plus-noise-ratio (SINR) filter bank (GSINR-FB) as our beamformer which exploits receiver diversity through cooperation between the data streams of a user. The data streams for each user are subject to an average SINR constraint, which has many important applications in wireless communication systems and serves as a good metric to measure the quality of service (QoS). The GSINR-FB also optimizes the average SINR of its output. Based on the GSINR-FB beamformer, we find an SINR balancing structure for optimal power allocation which simplifies the complicated power allocation problem to a linear one. Simulation results verify the superiority of the proposed algorithms over previous works with approximately the same complexity. [ABSTRACT FROM PUBLISHER]

The computational complexity and peak-to-average power ratio (PAPR) of conventional precoded orthogonal frequency division multiplexing (OFDM) systems can be reduced using a T-OFDM precoded system based on the Walsh–Hadamard matrix. The present paper proposes a novel precoding scheme for further reducing the computational complexity and PAPR of T-OFDM. In the proposed scheme, the precoding matrix is combined with an inverse discrete Fourier transform to construct a new transform matrix at the transmitter. Notably, the transform matrix is both unitary and circulant, with each column being a perfect Gaussian integer sequence containing just four non-zero elements of \\pm 1,\pm j\. A low-complexity receiver is additionally constructed for the proposed precoding scheme. A closed-form expression is derived for the bit error rate (BER) in T-OFDM and the proposed precoding scheme under frequency-selective fading channels. The simulation results for the BER are shown to be in good agreement with the mathematical derivations. In addition, it is demonstrated that T-OFDM and the proposed scheme have an equivalent BER performance when their precoding matrices are designed in such a way as to obtain full frequency diversity. However, the proposed scheme has a better PAPR performance and a lower computational complexity than T-OFDM. [ABSTRACT FROM PUBLISHER]

Linear-assignment Gel'fand-Pinsker coding (LA-GPC) is a coding technique for channels with interference known only at the transmitter, where the known interference is treated as side-information (SI). As a special case of the LA-GPC, dirty paper coding has been shown to be able to achieve the optimal interference-free rate for SI channels with perfect channel state information at the transmitter (CSIT). In the cases where only the channel distribution information at the transmitter (CDIT) is available, LA-GPC also has good (sometimes optimal) performance in a variety of fast and slow fading SI channels. In this letter, we design filters in the nested lattice based coding to make it achieve the same rate performance as the LA-GPC in multiple-input multiple-output (MIMO) channels. Compared with the random Gaussian codebooks used in previous works, our resultant coding schemes have algebraic structures and can be implemented in practical systems. Simulations in slow-fading channels are provided, and near interference-free error performance is obtained. The proposed coding schemes can serve as the fundamental building blocks to achieve the promised rate performance of MIMO Gaussian broadcast channels with CDIT or perfect CSIT. [ABSTRACT FROM AUTHOR]