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This paper proposes low overhead training techniques for a wireless communication system equipped with a Multifunctional Reconfigurable Antenna (MRA) capable of dynamically changing beamwidth and beam directions. A novel microelectromechanical system (MEMS) MRA antenna is presented with radiation patterns (generated using complete electromagnetic full-wave analysis) which are used to quantify the communication link performance gains. In particular, it is shown that using the proposed Exhaustive Training at Reduced Frequency (ETRF) consistently results in a reduction in training overhead. It is also demonstrated that further reduction in training overhead is possible using statistical or MUSIC-based training schemes. Bit Error Rate (BER) and capacity simulations are carried out using an MRA, which can tilt its radiation beam into one of = 4 or 8 directions with variable beamwidth (≈ 2 / ). The performance of each training scheme is quantified for OFDM systems operating in frequency selective channels with and without Line of Sight (LoS). We observe 6 dB of gain at BER = 10 −4 and 6 dB improvement in capacity (at capacity = 6 bits/sec/subcarrier) are achievable for an MRA with = 8 as compared to omni directional antennas using ETRF scheme in a LoS environment.Index Terms-MIMO, MUSIC, training, beam forming, reconfigurable antenna, antenna array, microelectromechanical systems (MEMS).

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In this paper, we present the architecture of a highly configurable multi-input multi-output (MIMO) orthogonal frequency division multiple access (OFDMA) platform. The platform is designed to support experimentation with various communication algorithms, thus allowing an intimate understanding of the performance of complex algorithms under real-life constraints. The hardware used is the wireless open access research platform (WARP) which facilitates rapid prototyping utilizing the FPGA and multi radio interfaces available.