Visual reconstruction
Convex Optimization
Radio Frequency Integrated Circuits and Technologies
Radio Frequency Integrated Circuits and Technologies
MIMO transceiver design via majorization theory
Foundations and Trends in Communications and Information Theory
Minimum BER beamforming in the RF domain for OFDM transmissions and linear receivers
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A fast approach for overcomplete sparse decomposition based on smoothed l0 norm
IEEE Transactions on Signal Processing
Spectrum sharing in wireless networks via QoS-aware secondary multicast beamforming
IEEE Transactions on Signal Processing
Analog antenna combining for maximum capacity under OFDM transmissions
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Adaptive blind deconvolution of linear channels using Renyi's entropy with Parzen window estimation
IEEE Transactions on Signal Processing
Entropy minimization for supervised digital communications channelequalization
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Transmit beamforming for physical-layer multicasting
IEEE Transactions on Signal Processing - Part I
Symbol-based space diversity for coded OFDM systems
IEEE Transactions on Wireless Communications
Multi-Stage Beamforming for Coded OFDM with Multiple Transmit and Multiple Receive Antennas
IEEE Transactions on Wireless Communications
Pre-DFT Processing for MIMO-OFDM Systems with Space-Time-Frequency Coding
IEEE Transactions on Wireless Communications
Mobile WiMAX systems: performance and evolution
IEEE Communications Magazine
Hi-index | 35.68 |
In this paper, we study beamforming schemes for a novel MIMO transceiver, which performs adaptive signal combining in the radio-frequency (RF) domain. Assuming perfect channel knowledge at the receiver side, we consider the problem of designing the transmit and receive RF beamformers under orthogonal frequency division multiplexing (OFDM) transmissions. In particular, a general beamforming criterion is proposed, which depends on a single parameter α. This parameter establishes a tradeoff between the energy of the equivalent SISO channel (after Tx-Rx beamforming) and its spectral flatness. The proposed cost function embraces most reasonable criteria for designing analog Tx-Rx beamformers. Hence, for particular values of α the proposed criterion reduces to the minimization of the mean square error (MSE), the maximization of the system capacity, or the maximization of the received signal-to-noise ratio (SNR). In general, the proposed criterion results in a nonconvex optimization problem. However, we show that the problem can be rewritten as a convex cost function subject to a couple of rank-one constraints, and hence it can be approximately solved by semidefinite relaxation (SDR) techniques. Since the computational cost of SDR for this problem is rather high, and building on the observation that the minima of the original problem must be solutions of a pair of coupled eigenvalue problems, we propose yet another simple and efficient gradient search algorithm which, in practice, provides satisfactory solutions with a moderate computational cost. Finally, several numerical examples show the good performance of the proposed technique for both uncoded and 802.11a-coded transmissions.