Optimal Bit Allocation-Based Hybrid Precoder-Combiner Design Techniques for mmWave MIMO-OFDM Systems

Manjeer Majumder,Harshit Saxena,Aditya K Jagannatham,Suraj Srivastava

doi:10.1109/access.2021.3070921

Manjeer Majumder, Harshit Saxena + Show 2 more

Open Access

https://doi.org/10.1109/access.2021.3070921

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Journal: IEEE Access	Publication Date: Jan 1, 2021
Citations: 48	License type: CC BY 4.0

Affiliation: Indian Institute of Technology Kanpur

Abstract

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.

Highlights

Millimeter-wave wireless communication has attracted significant attention due to the availability of vast spectral bands that can in turn enable ultra-high data rates in 5G networks [1]–[3]
The transmission rate of the proposed multicarrier optimal bit allocation algorithm based on the fully-digital optimal precoder/ combiner is compared with that of the hybrid precoder/ combiner designs obtained using the multicarrier simultaneous orthogonal matching pursuit (SOMP) and MMV sparse Bayesian learning (MSBL) approaches outlined in sections Algorithm 1 and V
The variation in the performance of multicarrier MSBL and SOMP algorithms for the hybrid precoder/ combiner design with the number of radio frequency (RF) chains NRF has been demonstrated through simulation results

Summary

INTRODUCTION

Millimeter-wave (mmWave) wireless communication has attracted significant attention due to the availability of vast spectral bands that can in turn enable ultra-high data rates in 5G networks [1]–[3]. Majumder et al.: Optimal Bit Allocation-Based Hybrid Precoder-Combiner Design Techniques infeasible as it necessitates a dedicated radio frequency (RF) chain, DAC/ ADC for each antenna element [13], [14] This arises due to the increased cost, area, and complexity of RF components operating in the mmWave regime, coupled with the high power consumption of the ADCs that are required to operate at a very high sampling rate. To the best of our knowledge, as can be seen from the table above, none of the existing works have considered the problem of hybrid precoder/ combiner design with optimal bit allocation for mmWave MIMO-OFDM systems toward bit-rate maximization, which forms the focus of this work. The organization of the paper and notation are described

ORGANIZATION The rest of the paper is organized as follows

PROBLEM FORMULATION

SIMULATION RESULTS

CONCLUSION