Energy Efficiency and Asymptotic Performance Evaluation of Beamforming Structures in Doubly Massive MIMO mmWave Systems

Future cellular systems based on the use of millimeter waves will heavily rely on the use of antenna arrays both at the transmitter and at the receiver. For complexity reasons and energy consumption issues, fully digital precoding and postcoding structures may turn out to be unfeasible, and thus suboptimal structures, making use of simplified hardware and a limited number of RF chains, have been investigated. This paper considers and makes a comparative assessment, both from a spectral efficiency and energy efficiency point of view, of several suboptimal precoding and postcoding beamforming structures for a cellular multiuser MIMO (MU-MIMO) system with large number of antennas. Analytical formulas for the asymptotic achievable spectral efficiency and for the global energy efficiency of several beamforming structures are derived in the large number of antennas regime. Using the most recently available data for the energy consumption of phase shifters and switches, we show that fully-digital beamformers may actually achieve a larger energy efficiency than lower-complexity solutions, as well as that low-complexity beam-steering purely analog beamforming may in some cases represent a good performance-complexity trade-off solution.Comment: Submitted to IEEE Transactions on Green Communications and Networkin

Downlink Achievable Rate Analysis for FDD Massive MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems with large-scale transmit antenna arrays, often called massive MIMO, are a very promising direction for 5G due to their ability to increase capacity and enhance both spectrum and energy efficiency. To get the benefit of massive MIMO systems, accurate downlink channel state information at the transmitter (CSIT) is essential for downlink beamforming and resource allocation. Conventional approaches to obtain CSIT for FDD massive MIMO systems require downlink training and CSI feedback. However, such training will cause a large overhead for massive MIMO systems because of the large dimensionality of the channel matrix. In this dissertation, we improve the performance of FDD massive MIMO networks in terms of downlink training overhead reduction, by designing an efficient downlink beamforming method and developing a new algorithm to estimate the channel state information based on compressive sensing techniques. First, we design an efficient downlink beamforming method based on partial CSI. By exploiting the relationship between uplink direction of arrivals (DoAs) and downlink direction of departures (DoDs), we derive an expression for estimated downlink DoDs, which will be used for downlink beamforming. Second, By exploiting the sparsity structure of downlink channel matrix, we develop an algorithm that selects the best features from the measurement matrix to obtain efficient CSIT acquisition that can reduce the downlink training overhead compared with conventional LS/MMSE estimators. In both cases, we compare the performance of our proposed beamforming method with traditional methods in terms of downlink achievable rate and simulation results show that our proposed method outperform the traditional beamforming methods

Design of Joint Spatial and Power Domain Multiplexing Scheme for Massive MIMO Systems

Massive Multiple-Input Multiple-Output (MIMO) is one of the key techniques in 5th generation wireless systems (5G) due to its potential ability to improve spectral efficiency. Most of the existing works on massive MIMO only consider Time Division Duplex (TDD) operation that relies on channel reciprocity between uplink and downlink channels. For Frequency Division Duplex (FDD) systems, with continued efforts, some downlink multiuser MIMO scheme was recently proposed in order to enable “massive MIMO” gains and simplified system operations with limited number of radio frequency (RF) chains in FDD system. However these schemes, such as Joint Spatial Division and Multiplexing (JSDM) scheme and hybrid precoding scheme, only focus on multiuser transmission in spatial domain. Different from most of the existing works, this paper proposes Joint Spatial and Power Multiplexing (JSPM) scheme in FDD systems. It extends existing FDD schemes from spatial division and multiplexing to joint spatial and power domain to achieve more multiplexing gain. The user grouping and scheduling scheme of JSPM is studied and the asymptotic expression for the sum capacity is derived as well. Finally, simulations are conducted to illustrate the effectiveness of the proposed scheme

Uplink Beam Management for Millimeter Wave Cellular MIMO Systems with Hybrid Beamforming

Hybrid analog and digital BeamForming (HBF) is one of the enabling transceiver technologies for millimeter Wave (mmWave) Multiple Input Multiple Output (MIMO) systems. This technology offers highly directional communication, which is able to confront the intrinsic characteristics of mmWave signal propagation. However, the small coherence time in mmWave systems, especially under mobility conditions, renders efficient Beam Management (BM) in standalone mmWave communication a very difficult task. In this paper, we consider HBF transceivers with planar antenna panels and design a multi-level beam codebook for the analog beamformer comprising flat top beams with variable widths. These beams exhibit an almost constant array gain for the whole desired angle width, thereby facilitating efficient hierarchical BM. Focusing on the uplink communication, we present a novel beam training algorithm with dynamic beam ordering, which is suitable for the stringent latency requirements of the latest mmWave standard discussions. Our simulation results showcase the latency performance improvement and received signal-to-noise ratio with different variations of the proposed scheme over the optimum beam training scheme based on exhaustive narrow beam search.Comment: 7 pages; 6 figures; accepted to an IEEE conferenc