Reconfigurable antennas and link adaptation algorithms for MIMO-OFDM wireless systems

Abstract

In this work, we study and analyze the performance of physical layer algorithms for adaptive multiple input-multiple output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems that employ a new class of adaptive antenna systems known as reconfigurable antennas. These antennas are capable of adaptively modifying their radiation characteristics and thus leverage pattern diversity to affect how the transmitter and receiver perceive the wireless channel. We propose a low complexity spatial adaptive modulation and coding (AMC) algorithm that uses the advantages of pattern reconfigurable antennas in concert with link adaptation to improve MIMO-OFDM link throughput. The algorithm operates in two main stages; first, it searches for the antenna configuration that yields the highest post processing signal-to-noise ratio (ppSNR) and, then, applies AMC to improve spectral efficiency. The performance of the proposed scheme is experimentally evaluated for a 2 × 2 MIMO-OFDM wireless system in an indoor environment.

Reducing codebook loss with reconfigurable receive antennas

“…However, the receiver must estimate the S channel vectors in order to evaluate the best channel vector/beamformer pair. Hence reconfigurable systems must perform extra channel estimation and efficient approaches to this overhead are discussed in [22]. We assume a total transmit power, P t = E [| z | 2 ], and the noise power is E [| n | 2 ] = σ 2 , where E [.]…”