Limited Feedback Massive MISO Systems with Trellis Coded Quantization for Correlated Channels

In this paper, we propose trellis coded quantization (TCQ) based limited feedback techniques for massive multiple-input single-output (MISO) frequency division duplexing (FDD) systems in temporally and spatially correlated channels. We exploit the correlation present in the channel to effectively quantize channel direction information (CDI). For multiuser (MU) systems with matched-filter (MF) precoding, we show that the number of feedback bits required by the random vector quantization (RVQ) codebook to match even a small fraction of the perfect CDI signal-to-interference-plus-noise ratio (SINR) performance is large. With such large numbers of bits, the exhaustive search required by conventional codebook approaches make them infeasible for massive MISO systems. Motivated by this, we propose a differential TCQ scheme for temporally correlated channels that transforms the source constellation at each stage in a trellis using 2D translation and scaling techniques. We derive a scaling parameter for the source constellation as a function of the temporal correlation and the number of BS antennas. We also propose a TCQ based limited feedback scheme for spatially correlated channels where the channel is quantized directly without performing decorrelation at the receiver. Simulation results show that the proposed TCQ schemes outperform the existing noncoherent TCQ (NTCQ) schemes, by improving the spectral efficiency and beamforming gain of the system. The proposed differential TCQ also reduces the feedback overhead of the system compared to the differential NTCQ method.Comment: 13 pages, 18 figures, IEEE Transactions on Vehicular Technology, accepted for publicatio

A Survey on MIMO Transmission with Discrete Input Signals: Technical Challenges, Advances, and Future Trends

Multiple antennas have been exploited for spatial multiplexing and diversity transmission in a wide range of communication applications. However, most of the advances in the design of high speed wireless multiple-input multiple output (MIMO) systems are based on information-theoretic principles that demonstrate how to efficiently transmit signals conforming to Gaussian distribution. Although the Gaussian signal is capacity-achieving, signals conforming to discrete constellations are transmitted in practical communication systems. As a result, this paper is motivated to provide a comprehensive overview on MIMO transmission design with discrete input signals. We first summarize the existing fundamental results for MIMO systems with discrete input signals. Then, focusing on the basic point-to-point MIMO systems, we examine transmission schemes based on three most important criteria for communication systems: the mutual information driven designs, the mean square error driven designs, and the diversity driven designs. Particularly, a unified framework which designs low complexity transmission schemes applicable to massive MIMO systems in upcoming 5G wireless networks is provided in the first time. Moreover, adaptive transmission designs which switch among these criteria based on the channel conditions to formulate the best transmission strategy are discussed. Then, we provide a survey of the transmission designs with discrete input signals for multiuser MIMO scenarios, including MIMO uplink transmission, MIMO downlink transmission, MIMO interference channel, and MIMO wiretap channel. Additionally, we discuss the transmission designs with discrete input signals for other systems using MIMO technology. Finally, technical challenges which remain unresolved at the time of writing are summarized and the future trends of transmission designs with discrete input signals are addressed.Comment: 110 pages, 512 references, submit to Proceedings of the IEE

Cell-Free Millimeter-Wave Massive MIMO Systems with Limited Fronthaul Capacity

Network densification, massive multiple-input multiple-output (MIMO) and millimeter-wave (mmWave) bands have recently emerged as some of the physical layer enablers for the future generations of wireless communication networks (5G and beyond). Grounded on prior work on sub-6~GHz cell-free massive MIMO architectures, a novel framework for cell-free mmWave massive MIMO systems is introduced that considers the use of low-complexity hybrid precoders/decoders while factors in the impact of using capacity-constrained fronthaul links. A suboptimal pilot allocation strategy is proposed that is grounded on the idea of clustering by dissimilarity. Furthermore, based on mathematically tractable expressions for the per-user achievable rates and the fronthaul capacity consumption, max-min power allocation and fronthaul quantization optimization algorithms are proposed that, combining the use of block coordinate descent methods with sequential linear optimization programs, ensure a uniformly good quality of service over the whole coverage area of the network. Simulation results show that the proposed pilot allocation strategy eludes the computational burden of the optimal small-scale CSI-based scheme while clearly outperforming the classical random pilot allocation approaches. Moreover, they also reveal the various existing trade-offs among the achievable max-min per-user rate, the fronthaul requirements and the optimal hardware complexity (i.e., number of antennas, number of RF chains)

Dynamic Sounding for Multi-User MIMO in Wireless LANs

Consumer electronic (CE) devices increasingly rely on wireless local area networks (WLANs). Next generation WLANs will continue to exploit multiple antenna systems to satisfy the growing need for WLAN system capacity. Multiple-input multiple-output (MIMO) antenna systems improve the spectral efficiency and single user throughput. Multi-user MIMO (MU-MIMO) systems exploit the spatial separation of users for increasing the sum-throughput. In an MU-MIMO system, efficient channel sounding is essential for achieving optimal performance. The system analysis in this paper provides insights into the rate at which to perform channel sounding. This paper shows that optimal sounding intervals exist for single user transmit beamforming (SU-TxBF) and MU-MIMO, and proposes a low-complexity dynamic sounding approach for practical MU-MIMO WLAN deployments. The proposed approach adjusts the sounding interval adaptively based on the real-time learning outcomes in the given radio environment. Using real over-the-air channel measurements, significant throughput improvements (up to 31.8%) are demonstrated by adopting the proposed dynamic sounding approach, which is compliant with IEEE 802.11ac.Comment: IEEE Transactions on Consumer Electronics, 201

5G Cellular User Equipment: From Theory to Practical Hardware Design

Research and development on the next generation wireless systems, namely 5G, has experienced explosive growth in recent years. In the physical layer (PHY), the massive multiple-input-multiple-output (MIMO) technique and the use of high GHz frequency bands are two promising trends for adoption. Millimeter-wave (mmWave) bands such as 28 GHz, 38 GHz, 64 GHz, and 71 GHz, which were previously considered not suitable for commercial cellular networks, will play an important role in 5G. Currently, most 5G research deals with the algorithms and implementations of modulation and coding schemes, new spatial signal processing technologies, new spectrum opportunities, channel modeling, 5G proof of concept (PoC) systems, and other system-level enabling technologies. In this paper, we first investigate the contemporary wireless user equipment (UE) hardware design, and unveil the critical 5G UE hardware design constraints on circuits and systems. On top of the said investigation and design trade-off analysis, a new, highly reconfigurable system architecture for 5G cellular user equipment, namely distributed phased arrays based MIMO (DPA-MIMO) is proposed. Finally, the link budget calculation and data throughput numerical results are presented for the evaluation of the proposed architecture.Comment: Submitted to IEEE ACCESS. It has 18 pages, 17 figures, and 5 table

Spectrum and Energy Efficient Beamspace MIMO-NOMA for Millimeter-Wave Communications Using Lens Antenna Array

The recent concept of beamspace multiple input multiple output (MIMO) can significantly reduce the number of required radio-frequency (RF) chains in millimeter-wave (mmWave) massive MIMO systems without obvious performance loss. However, the fundamental limit of existing beamspace MIMO is that, the number of supported users cannot be larger than the number of RF chains at the same time-frequency resources. To break this fundamental limit, in this paper we propose a new spectrum and energy efficient mmWave transmission scheme that integrates the concept of non-orthogonal multiple access (NOMA) with beamspace MIMO, i.e., beamspace MIMO-NOMA. By using NOMA in beamspace MIMO systems, the number of supported users can be larger than the number of RF chains at the same time-frequency resources. Particularly, the achievable sum rate of the proposed beamspace MIMO-NOMA in a typical mmWave channel model is analyzed, which shows an obvious performance gain compared with the existing beamspace MIMO. Then, a precoding scheme based on the principle of zero-forcing (ZF) is designed to reduce the inter-beam interferences in the beamspace MIMO-NOMA system. Furthermore, to maximize the achievable sum rate, a dynamic power allocation is proposed by solving the joint power optimization problem, which not only includes the intra-beam power optimization, but also considers the inter-beam power optimization. Finally, an iterative optimization algorithm with low complexity is developed to realize the dynamic power allocation. Simulation results show that the proposed beamspace MIMO-NOMA can achieve higher spectrum and energy efficiency compared with existing beamspace MIMO.Comment: To appear in IEEE Journal on Selected Areas in Communications. Simulation codes are provided to reproduce the results presented in this paper: http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.htm

Low-Complexity Recursive Convolutional Precoding for OFDM-based Large-Scale Antenna System

Large-scale antenna (LSA) has gained a lot of attention recently since it can significantly improve the performance of wireless systems. Similar to multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) or MIMO-OFDM, LSA can be also combined with OFDM to deal with frequency selectivity in wireless channels. However, such combination suffers from substantially increased complexity proportional to the number of antennas in LSA systems. For the conventional implementation of LSA-OFDM, the number of inverse fast Fourier transforms (IFFTs) increases with the antenna number since each antenna requires an IFFT for OFDM modulation. Furthermore, zero-forcing (ZF) precoding is required in LSA systems to support more users, and the required matrix inversion leads to a huge computational burden. In this paper, we propose a low-complexity recursive convolutional precoding to address the issues above. The traditional ZF precoding can be implemented through the recursive convolutional precoding in the time domain so that only one IFFT is required for each user and the matrix inversion can be also avoided. Simulation results show that the proposed approach can achieve the same performance as that of ZF but with much lower complexity

Boosting Fronthaul Capacity: Global Optimization of Power Sharing for Centralized Radio Access Network

The limited fronthaul capacity imposes a challenge on the uplink of centralized radio access network (C-RAN). We propose to boost the fronthaul capacity of massive multiple-input multiple-output (MIMO) aided C-RAN by globally optimizing the power sharing between channel estimation and data transmission both for the user devices (UDs) and the remote radio units (RRUs). Intuitively, allocating more power to the channel estimation will result in more accurate channel estimates, which increases the achievable throughput. However, increasing the power allocated to the pilot training will reduce the power assigned to data transmission, which reduces the achievable throughput. In order to optimize the powers allocated to the pilot training and to the data transmission of both the UDs and the RRUs, we assign an individual power sharing factor to each of them and derive an asymptotic closed-form expression of the signal-to-interference-plus-noise for the massive MIMO aided C-RAN consisting of both the UD-to-RRU links and the RRU-to-baseband unit (BBU) links. We then exploit the C-RAN architecture's central computing and control capability for jointly optimizing the UDs' power sharing factors and the RRUs' power sharing factors aiming for maximizing the fronthaul capacity. Our simulation results show that the fronthaul capacity is significantly boosted by the proposed global optimization of the power allocation between channel estimation and data transmission both for the UDs and for their host RRUs. As a specific example of 32 receive antennas (RAs) deployed by RRU and 128 RAs deployed by BBU, the sum-rate of 10 UDs achieved with the optimal power sharing factors improves 33\% compared with the one attained without optimizing power sharing factors

Achieving Phase Coherency and Gain Stability in Active Antenna Arrays for Sub-6 GHz FDD and TDD FD-MIMO: Challenges and Solutions

Massive MIMO has been the subject of intense interest in both academia and industry for the past few years. 3GPP standardization for cellular systems have adopted the principles of massive MIMO and categorized the use of large rectangular planar arrays at the base station as full-dimension MIMO (FD-MIMO) to operate in both TDD and FDD. Operating a large antenna array base station requires the system to overcome several implementation challenges caused by hardware impairments making practical solutions non-ideal and expensive to deploy at scale. It is important to learn from existing challenges and solutions in order to prepare for larger scale deployment for example with cell free massive MIMO. Hence in this paper, we specifically study the phase and amplitude instability due to RF impairments using measurements carried out in the lab and in the field in a commercial LTE network. We investigate the effect of phase and magnitude errors on the performance of FD-MIMO systems. We discuss and characterize various sources creating these errors including time varying phase drift from low cost local oscillator (LO) and internal temperature variations affecting frequency response of RF chains. The minimum requirements and tradeoffs of different LO architectures and calibration mechanisms for practical cellular deployment are discussed. We then provide details of a novel coherent LO distribution mechanism and related novel array calibration mechanism that can be applied to both TDD and FDD systems. Measurement results are provided to validate the performance of these methods used in a 2D full-connected hybrid beamforming array architecture called High Definition Active Antenna System (HDAAS). These results showcase the efficacy of the proposed methods which can easily be extended to other array architectures including sub-array hybrid beamforming and element-level digitization.Comment: This paper was submitted for publication in IEEE Journal on Selected Areas in Communications on August 29, 201

Index Modulation Techniques for Energy-efficient Transmission in Large-scale MIMO Systems

This thesis exploits index modulation techniques to design energy- and spectrum-efficient system models to operate in future wireless networks. In this respect, index modulation techniques are studied considering two different media: mapping the information onto the frequency indices of multicarrier systems, and onto the antenna array indices of a platform that comprises multiple antennas. The index modulation techniques in wideband communication scenarios considering orthogonal and generalized frequency division multiplexing systems are studied first. Single cell multiuser networks are considered while developing the system models that exploit the index modulation on the subcarriers of the multicarrier systems. Instead of actively modulating all the subcarriers, a subset is selected according to the index modulation bits. As a result, there are subcarriers that remain idle during the data transmission phase and the activation pattern of the subcarriers convey additional information. The transceivers for the orthogonal and generalized frequency division multiplexing systems with index modulation are both designed considering the uplink and downlink transmission phases with a linear combiner and precoder in order to reduce the system complexity. In the developed system models, channel state information is required only at the base station. The linear combiner is designed adopting minimum mean square error method to mitigate the inter-user-interference. The proposed system models offer a flexible design as the parameters are independent of each other. The parameters can be adjusted to design the system in favor of the energy efficiency, spectrum efficiency, peak-to-average power ratio, or error performance. Then, the index modulation techniques are studied for large-scale multiple-input multiple-output systems that operate in millimeter wave bands. In order to overcome the drawbacks of transmission in millimeter wave frequencies, channel properties should be taken in to account while envisaging the wireless communication network. The large-scale multiple-input multiple-output systems increase the degrees of freedom in the spatial domain. This feature can be exploited to focus the transmit power directly onto the intended receiver terminal to cope with the severe path-loss. However, scaling up the number of hardware elements results in excessive power consumption. Hybrid architectures provide a remedy by shifting a part of the signal processing to the analog domain. In this way, the number of bulky and high power consuming hardware elements can be reduced. However, there will be a performance degradation as a consequence of renouncing the fully digital signal processing. Index modulation techniques can be combined with the hybrid system architecture to compensate the loss in spectrum efficiency to further increase the data rates. A user terminal architecture is designed that employs analog beamforming together with spatial modulation where a part of the information bits is mapped onto the indices of the antenna arrays. The system is comprised a switching stage that allocates the user terminal antennas on the phase shifter groups to minimize the spatial correlation, and a phase shifting stage that maximizes the beamforming gain to combat the path-loss. A computationally efficient optimization algorithm is developed to configure the system. The flexibility of the architecture enables optimization of the hybrid transceiver at any signal-to-noise ratio values. A base station is designed in which hybrid beamforming together with spatial modulation is employed. The analog beamformer is designed to point the transmit beam only in the direction of the intended user terminal to mitigate leakage of the transmit power to other directions. The analog beamformer to transmit the signal is chosen based on the spatial modulation bits. The digital precoder is designed to eliminate the inter-user-interference by exploiting the zero-forcing method. The base station computes the hybrid beamformers and the digital combiners, and only feeds back the digital combiners of each antenna array-user pair to the related user terminals. Thus, a low complexity user architecture is sufficient to achieve a higher performance. The developed optimization framework for the energy efficiency jointly optimizes the number of served users and the total transmit power by utilizing the derived upper bound of the achievable rate. The proposed transceiver architectures provide a more energy-efficient system model compared to the hybrid systems in which the spatial modulation technique is not exploited. This thesis develops low-complexity system models that operate in narrowband and wideband channel environments to meet the energy and spectrum efficiency demands of future wireless networks. It is corroborated in the thesis that adopting index modulation techniques both in the systems improves the system performance in various aspects.:1 Introduction 1 1.1 Motivation 1 1.2 Overview and Contribution 2 1.3 Outline 9 2 Preliminaries and Fundamentals 13 2.1 Multicarrier Systems 13 2.2 Large-scale Multiple Input Multiple Output Systems 17 2.3 Index Modulation Techniques 19 2.4 Single Cell Multiuser Networks 22 3 Multicarrier Systems with Index Modulation 27 3.1 Orthogonal Frequency Division Multiplexing 28 3.2 Generalized Frequency Division Multiplexing 40 3.3 Summary 52 4 Hybrid Beamforming with Spatial Modulation 55 4.1 Uplink Transmission 56 4.2 Downlink Transmission 74 4.3 Summary 106 5 Conclusion and Outlook 109 5.1 Conclusion 109 5.2 Outlook 111 A Quantization Error Derivations 113 B On the Achievable Rate of Gaussian Mixtures 115 B.1 The Conditional Density Function 115 B.2 Tight Bounds on the Differential Entropy 116 B.3 A Bound on the Achievable Rate 118 C Multiuser MIMO Downlink without Spatial Modulation 121 Bibliograph