Multiuser precoding and channel estimation for hybrid millimeter wave MIMO systems

Abstract

In this paper, we develop a low-complexity channel estimation for hybrid millimeter wave (mmWave) systems, where the number of radio frequency (RF) chains is much less than the number of antennas equipped at each transceiver. The proposed channel estimation algorithm aims to estimate the strongest angle-of-arrivals (AoAs) at both the base station (BS) and the users. Then all the users transmit orthogonal pilot symbols to the BS via these estimated strongest AoAs to facilitate the channel estimation. The algorithm does not require any explicit channel state information (CSI) feedback from the users and the associated signalling overhead of the algorithm is only proportional to the number of users, which is significantly less compared to various existing schemes. Besides, the proposed algorithm is applicable to both non-sparse and sparse mmWave channel environments. Based on the estimated CSI, zero-forcing (ZF) precoding is adopted for multiuser downlink transmission. In addition, we derive a tight achievable rate upper bound of the system. Our analytical and simulation results show that the proposed scheme offer a considerable achievable rate gain compared to fully digital systems, where the number of RF chains equipped at each transceiver is equal to the number of antennas. Furthermore, the achievable rate performance gap between the considered hybrid mmWave systems and the fully digital system is characterized, which provides useful system design insights. I. INTRODUCTIONHigher data rates, large bandwidth, and higher spectral efficiency are necessary for the fifth-generation (5G) wireless communication systems to support various emerging applications [1]. The combination of millimeter wave (mmWave) communication [2]-[5] with massive multiple-input multipleoutput (MIMO) [6]-[8] is considered as one of the promising candidate technologies for 5G communication systems with many potential and exciting opportunities for research [7], [9]- [13]. For example, the trade-offs between system performance, hardware complexity, and energy consumption [2], [14] are still unclear. From the literature, it is certain that the conventional fully digital MIMO systems, in which each antenna connects with a dedicated radio frequency (RF) chain, are impractical for mmWave systems due to the prohibitively high cost, e.g. tremendous energy consumption of high resolution analog-to-digital convertors/digital-to-analog convertors (ADC/DACs) and power amplifiers (PAs). Therefore, several mmWave hybrid systems were proposed as compromised solutions which strike a balance between hardware complexity and system performance [11], [15]-[18]. Specifically, the use

Multi-User Precoding and Channel Estimation for Hybrid Millimeter Wave Systems

“…In the large numbers of antennas regime, based on (24) and (29), it is interesting to observe that with an increasing Rician K-factor υ, the performance upper bounds of the two considered systems will coincide. Intuitively, as the Rician Kfactor increases, the LOS component becomes the dominant element of the communication channel, as shown in Equation (1). Therefore, the BS analog beamforming matrix based on the estimated strongest AoA will allocate a smaller portion of the transmitted signal energy to the scattering component.…”

“…In fact, there are plenty of implementation challenges for mmWave massive MIMO communication systems. For example, the trade-offs between system performance, hardware complexity 1 , and energy consumption [2], [14] are still unclear. From the literature, it is certain that conventional fully digital MIMO systems, in which each antenna connects with a dedicated radio frequency (RF) chain, are impractical for mmWave systems due to the prohibitively high cost, e.g.…”

Performance Analysis of Multi-Cell Millimeter-Wave Massive MIMO Networks With Low-Precision ADCs

“…Therefore, channel estimation using overlapped beam patterns and rate adaptation has been proposed in [34] and a limited feedback hybrid channel estimation has been studied in [35]. To overcome the drawback of the feedback-based mechanism in these methods, a low-complexity channel estimation method has been proposed in [36].…”

Channel Estimation For The Multiuser Multipanel Massive Multiple Input Multiple Output System

“…Thus, one of the significant issues is the number of RF chains in the massive MIMO systems, which poses many challenges to the practical implementation [5]. The use of hybrid array structures is a solution is proposed for reducing the RF chains [8][9][10]. In these structures, the number of RF chains is reduced compared to the conventional massive MIMO system, to reduce the power consumption and the structural complexity.…”