This work conceives techniques for the design of hybrid precoders/combiners for optimal bit allocation in frequency selective millimeter wave (mmWave) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, toward transmission rate maximization. Initially, the optimal fully digital ideal precoder/ combiner design is derived together with a closed-form expression for the optimal bit allocation in the above system. This is followed by the development of a framework for optimal transceiver design and bit allocation in a practical mmWave MIMO-OFDM implementation with a hybrid architecture. It is demonstrated that the pertinent problem can be formulated as a multiple measurement vector (MMV)-based sparse signal recovery problem for joint design of the RF and baseband components across all the subcarriers, and an explicit algorithm is derived to solve this using the simultaneous orthogonal matching pursuit (SOMP). To overcome the shortcomings of the SOMP-based greedy approach, an MMV sparse Bayesian learning (MSBL)-based state-of-the-art algorithm is subsequently developed, which is seen to lead to improved performance due to the superior sparse recovery properties of the Bayesian learning framework. Simulation results verify the efficacy of the proposed designs and also demonstrate that the performance of the hybrid transceiver is close to that of its fully-digital counterpart.

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This work proposes novel techniques toward the design of optimal pilot sequences to perform channel estimation in block transmission systems over wideband frequency selective wireless fading channels. The framework developed is based on minimization of the Bayesian Cramér-Rao bound (BCRB) for the mean squared error (MSE) of the channel state information (CSI) estimate. Optimal pilot signals are determined for the four predominant classes of block transmission systems, viz. single carrier zero padding (SC-ZP), multi-carrier zero padding (MC-ZP), single carrier cyclic prefix (SC-CP) and multicarrier cyclic prefix (MC-CP) systems. This makes the techniques developed general in nature and thus applicable in a wide variety of block transmission systems. As part of this study, succinct expressions and results are also derived to characterize the error rate performance, incorporating also the effect of CSI estimation error resulting due to the proposed algorithms. Finally, numerical results obtained via Monte-Carlo simulation are presented to illustrate and compare the CSI acquisition performance of optimal pilot designs with that of conventional designs and also validate the theoretical analysis for the error rate performance. INDEX TERMS Block transmission system, mean square error (MSE), bit error rate (BER), diversity, minimum mean square error (MMSE), maximum likelihood (ML), zero forcing (ZF)