MmWave Massive MIMO Based Wireless Backhaul for 5G Ultra-Dense Network

Ultra-dense network (UDN) has been considered as a promising candidate for future 5G network to meet the explosive data demand. To realize UDN, a reliable, Gigahertz bandwidth, and cost-effective backhaul connecting ultra-dense small-cell base stations (BSs) and macro-cell BS is prerequisite. Millimeter-wave (mmWave) can provide the potential Gbps traffic for wireless backhaul. Moreover, mmWave can be easily integrated with massive MIMO for the improved link reliability. In this article, we discuss the feasibility of mmWave massive MIMO based wireless backhaul for 5G UDN, and the benefits and challenges are also addressed. Especially, we propose a digitally-controlled phase-shifter network (DPSN) based hybrid precoding/combining scheme for mmWave massive MIMO, whereby the low-rank property of mmWave massive MIMO channel matrix is leveraged to reduce the required cost and complexity of transceiver with a negligible performance loss. One key feature of the proposed scheme is that the macro-cell BS can simultaneously support multiple small-cell BSs with multiple streams for each smallcell BS, which is essentially different from conventional hybrid precoding/combining schemes typically limited to single-user MIMO with multiple streams or multi-user MIMO with single stream for each user. Based on the proposed scheme, we further explore the fundamental issues of developing mmWave massive MIMO for wireless backhaul, and the associated challenges, insight, and prospect to enable the mmWave massive MIMO based wireless backhaul for 5G UDN are discussed.Comment: This paper has been accepted by IEEE Wireless Communications Magazine. This paper is related to 5G, ultra-dense network (UDN), millimeter waves (mmWave) fronthaul/backhaul, massive MIMO, sparsity/low-rank property of mmWave massive MIMO channels, sparse channel estimation, compressive sensing (CS), hybrid digital/analog precoding/combining, and hybrid beamforming. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=730653

Architectures for Hybrid Precoding and Combining Techniques in Massive MIMO Systems Operating in the mmWave Band

Hybrid precoding and combining techniques in millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems with various array architectures have attracted significant interest as a promising technology for the development of 6G wireless communication systems. This approach presents numerous advantages, including reduced complexity, cost, and power consumption, when compared to traditional analog precoding methods. In this chapter, we investigate hybrid precoding and combining techniques for massive MIMO systems operating in the millimeter-wave (mmWave) band, with a focus on different architectures, such as full array (FA), subarray (SA), and hybrid array (HA) architectures. We discuss the system model of each architecture. Additionally, we solve the hybrid precoding and combining optimization problem to maximize the spectral efficiency of each architecture. We then propose iterative hybrid precoding and combining algorithms for all architectures, as well as compare their performance to that of traditional hybrid design methods to demonstrate that the proposed algorithms achieve superior performance with lower complexity and hardware requirements

A review on Precoding Techniques For mm-Wave Massive MIMO Wireless Systems

The growing demands for high data rate wireless connectivity shed lights on the fact that appropriate spectrum regions need to be investigated so that the expected future needs will be satisfied. With this in mind, the research community has shown considerable interest in millimeter-wave (mm-wave) communication. Generally, hybrid transceivers combining the analog phase shifter and the RF chains with digital signal processing (DSP) systems are used for MIMO communication in the fifth generation (5G) wireless networks. This paper presents a survey for different precoding or beamforming techniques that have been proposed in the literature. These beamforming techniques are mainly classified based on their hardware structure into analog and digital beamforming. To reduce the hardware complexity and power consumption, the hybrid precoding techniques that combine analog and digital beamforming can be implemented for mm-wave massive MIMO wireless systems. The performance of the most common hybrid precoding algorithms has been investigated in this paper

Joint Hybrid Precoder and Combiner Design for mmWave Spatial Multiplexing Transmission

Millimeter-wave (mmWave) communications have been considered as a key technology for future 5G wireless networks because of the orders-of-magnitude wider bandwidth than current cellular bands. In this paper, we consider the problem of codebook-based joint analog-digital hybrid precoder and combiner design for spatial multiplexing transmission in a mmWave multiple-input multiple-output (MIMO) system. We propose to jointly select analog precoder and combiner pair for each data stream successively aiming at maximizing the channel gain while suppressing the interference between different data streams. After all analog precoder/combiner pairs have been determined, we can obtain the effective baseband channel. Then, the digital precoder and combiner are computed based on the obtained effective baseband channel to further mitigate the interference and maximize the sum-rate. Simulation results demonstrate that our proposed algorithm exhibits prominent advantages in combating interference between different data streams and offer satisfactory performance improvement compared to the existing codebook-based hybrid beamforming schemes