Joint Transceiver and Large Intelligent Surface Design for Massive MIMO mmWave Systems
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- 20 October 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Wireless Communications
- Vol. 20 (2) , 1052-1064
Abstract
Large intelligent surface (LIS) has recently emerged as a potential low-cost solution to reshape the wireless propagation environment for improving the spectral efficiency. In this paper, we consider a downlink millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) system, where an LIS is deployed to assist the downlink data transmission from a base station (BS) to a user equipment (UE). Both the BS and the UE are equipped with a large number of antennas, and a hybrid analog/digital precoding/combining structure is used to reduce the hardware cost and energy consumption. We aim to maximize the spectral efficiency by jointly optimizing the LIS’s reflection coefficients and the hybrid precoder (combiner) at the BS (UE). To tackle this non-convex problem, we reformulate the complex optimization problem into a much more friendly optimization problem by exploiting the inherent structure of the effective (cascade) mmWave channel. A manifold optimization (MO)-based algorithm is then developed. Simulation results show that by carefully devising LIS’s reflection coefficients, our proposed method can help realize a favorable propagation environment with a small channel matrix condition number. Besides, it can achieve a performance comparable to those of state-of-the-art algorithms, while at a much lower computational complexity.Keywords
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Funding Information
- National Science Foundation of China (61829103, 61871091)
- Natural Science Foundation of China for Outstanding Young Scholars (61722109)
This publication has 41 references indexed in Scilit:
- Enabling High-Quality Untethered Virtual Reality2017
- Fundamentals of Massive MIMO2016
- 28 GHz Millimeter-Wave Ultrawideband Small-Scale Fading Models in Wireless Channels2016
- Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna ArraysIEEE Journal on Selected Areas in Communications, 2016
- Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO SystemsIEEE Journal of Selected Topics in Signal Processing, 2016
- MIMO Precoding and Combining Solutions for Millimeter-Wave SystemsIEEE Communications Magazine, 2014
- Millimeter-wave massive MIMO: the next wireless revolution?IEEE Communications Magazine, 2014
- Millimeter Wave Channel Modeling and Cellular Capacity EvaluationIEEE Journal on Selected Areas in Communications, 2014
- Millimeter-Wave Enhanced Local Area Systems: A High-Data-Rate Approach for Future Wireless NetworksIEEE Journal on Selected Areas in Communications, 2014
- State of the Art in 60-GHz Integrated Circuits and Systems for Wireless CommunicationsProceedings of the IEEE, 2011