On the Impact of Reconfigurable Antenna Arrays in Cognitive Radio

Technological advances in radio-frequency (RF) front-ends, such as reconfigurable antenna arrays, afford a new "hardware" dimension for dynamic spectrum access in cognitive wireless networks. In this paper, we study the impact of reconfigurable antenna arrays on maximizing the spectral efficiency of multiple input multiple output (MIMO) wireless communication links. Physical wireless channels exhibit spatial correlation and there is growing experimental evidence that sparse multipath is a key source of such correlation. We propose a model for sparse multipath channels and show that sparsity affords a new dimension over which MIMO capacity can be optimized: the distribution or configuration of the sparse statistically independent degrees of freedom (DoF) in the available spatial signal space dimensions. We provide an explicit characterization of the optimal capacity-maximizing channel configurations as a function of the operating SNR. We then develop a framework for realizing the optimal channel configuration at any SNR by systematically adapting the antenna spacings at the transmitter and the receiver. In contrast to a fixed-array MIMO system in which the multiplexing gain is lost at low SNRs, such adaptively reconfigurable MIMO systems deliver the maximum multiplexing gain at all SNRs. Surprisingly, three canonical array configurations are sufficient for near-optimum performance over the entire SNR range. Numerical results based on a realistic physical model are presented and implications of this work for cognitive radio and dynamic spectrum access are discussed