Antenna Subarray Formation Research Articles

Joint Beamforming and Antenna Subarray Formation for Nonregenerative MIMO Relay Networks

Antenna subarray formation (ASF) is a complexity-reducing technique for multiple-input–multiple-output (MIMO) receivers. For nonregenerative MIMO relay networks, we propose a joint beamforming and ASF scheme in this paper, which maximizes the achievable rate subject to transmit power constraints at the source and the relay, as well as a limited number of nonzero elements in the ASF matrix. By relaxing the constraint of limited number of nonzero elements in the ASF matrix, we decouple the joint beamforming and ASF design problem into three problems and propose to alternatively optimize beamforming matrices at the source, the relay, and the ASF matrix. We also propose a gradient projection (GP) algorithm to solve nonlinear programming of the relay beamforming design problem. Simulation results demonstrate that the proposed joint beamforming and ASF scheme outperforms the antenna selection (AS) scheme.

Joint Optimization of Transmission and Antenna Subarray Formation Receiving for MIMO SWIPT Systems

To reduce hardware complexity of multiple-input multiple-output system with the simultaneous wireless information and power transfer scheme, we propose joint transmission and antenna subarray formation (ASF) receiving optimization scheme which maximizes the achievable rate under the transmit power constraint and the energy harvesting constraint. By relaxing the constraint that ASF matrix should contain limited number of nonzero elements, we employ alternating optimization method to alternatively optimize the transmit covariance matrix and the ASF matrix. We also propose the capacity-loss-based and maximum absolute values algorithms to recover the above constraint on the ASF matrix. It is shown from the simulation results that the proposed schemes outperform the conventional antenna selection scheme.

Joint Beamforming and Antenna Subarray Formation for MIMO Cognitive Radios

The antenna subarray formation (ASF) is a promising technique for multiple-input multiple-output (MIMO) receiver. For MIMO cognitive radio systems, we propose a joint beamforming and ASF scheme in this letter which maximizes the cognitive achievable capacity subject to the peak transmit power constraint at the secondary transmitter, peak interference power constraint at the primary receiver, and the limited number of nonzero elements in the ASF matrix. To solve the joint optimization problem, we propose a relax-and-recover scheme. Simulation results have shown that the proposed scheme outperforms the conventional antenna selection scheme.

Maximising capacity of MIMO systems with receive antenna subarray formation

Antenna subarray formation is a novel RF pre-processing technique that reduces hardware complexity of multiple-input multiple-output systems while alleviating the performance degradation of conventional antenna selection techniques. With this method, each RF chain is allocated to a linear combination of the responses of a subset of the available antenna elements, which is performed in the radio frequency domain. A novel, analytical, suboptimal algorithm is introduced for receive antenna subarray formation based on instantaneous channel information that maximises the effective channel capacity.

Capacity Performance of Adaptive Receive Antenna Subarray Formation for MIMO Systems

Antenna subarray formation is a novel RF preprocessing technique that reduces the hardware complexity of MIMO systems while alleviating the performance degradations of conventional antenna selection schemes. With this method, each RF chain is not allocated to a single antenna element, but instead to the complex-weighted and combined response of a subarray of elements. In this paper, we derive tight upper bounds on the ergodic capacity of the proposed technique for Rayleigh i.i.d. channels. Furthermore, we study the capacity performance of an analytical algorithm based on a Frobenius norm criterion when applied to both Rayleigh i.i.d. and measured MIMO channels.

A Receive Antenna Subarray Formation Algorithm for MIMO Systems

Antenna selection techniques have been proposed to reduce the hardware complexity of MIMO wireless systems, while being efficient in terms of information rate achieved. Recently, an alternative method has been introduced to maximize the capacity of multiple antenna systems with reduced available RF chains, called antenna subarray formation. The method is based on the grouping of properly weighted antenna elements and initially was implemented with the use of an evolutionary optimization technique using the link capacity as a cost function. In this paper we propose an analytic algorithm for the subarray formation concept allowing for a more compact and tractable implementation