AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Ubiquitous Cell-Free Massive MIMO Communications

Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users, and hence, increases the spectral and energy efficiency. It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and Networking on August 5, 201

Reciprocity Calibration for Massive MIMO: Proposal, Modeling and Validation

This paper presents a mutual coupling based calibration method for time-division-duplex massive MIMO systems, which enables downlink precoding based on uplink channel estimates. The entire calibration procedure is carried out solely at the base station (BS) side by sounding all BS antenna pairs. An Expectation-Maximization (EM) algorithm is derived, which processes the measured channels in order to estimate calibration coefficients. The EM algorithm outperforms current state-of-the-art narrow-band calibration schemes in a mean squared error (MSE) and sum-rate capacity sense. Like its predecessors, the EM algorithm is general in the sense that it is not only suitable to calibrate a co-located massive MIMO BS, but also very suitable for calibrating multiple BSs in distributed MIMO systems. The proposed method is validated with experimental evidence obtained from a massive MIMO testbed. In addition, we address the estimated narrow-band calibration coefficients as a stochastic process across frequency, and study the subspace of this process based on measurement data. With the insights of this study, we propose an estimator which exploits the structure of the process in order to reduce the calibration error across frequency. A model for the calibration error is also proposed based on the asymptotic properties of the estimator, and is validated with measurement results.Comment: Submitted to IEEE Transactions on Wireless Communications, 21/Feb/201

System capacity enhancement for 5G network and beyond

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of people’s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairments’ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the user’s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmitters’ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receivers’ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the users’ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system

Massive MIMO for Next Generation Wireless Systems

Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over conventional point-to-point MIMO: it works with cheap single-antenna terminals, a rich scattering environment is not required, and resource allocation is simplified because every active terminal utilizes all of the time-frequency bins. However, multi-user MIMO, as originally envisioned with roughly equal numbers of service-antennas and terminals and frequency division duplex operation, is not a scalable technology. Massive MIMO (also known as "Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension MIMO" & "ARGOS") makes a clean break with current practice through the use of a large excess of service-antennas over active terminals and time division duplex operation. Extra antennas help by focusing energy into ever-smaller regions of space to bring huge improvements in throughput and radiated energy efficiency. Other benefits of massive MIMO include the extensive use of inexpensive low-power components, reduced latency, simplification of the media access control (MAC) layer, and robustness to intentional jamming. The anticipated throughput depend on the propagation environment providing asymptotically orthogonal channels to the terminals, but so far experiments have not disclosed any limitations in this regard. While massive MIMO renders many traditional research problems irrelevant, it uncovers entirely new problems that urgently need attention: the challenge of making many low-cost low-precision components that work effectively together, acquisition and synchronization for newly-joined terminals, the exploitation of extra degrees of freedom provided by the excess of service-antennas, reducing internal power consumption to achieve total energy efficiency reductions, and finding new deployment scenarios. This paper presents an overview of the massive MIMO concept and contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin

A Concise Review of 5G New Radio Capabilities for Directional Access at mmWave Frequencies

In this work, we briefly outline the core 5G air interface improvements introduced by the latest New Radio (NR) specifications, as well as elaborate on the unique features of initial access in 5G NR with a particular emphasis on millimeter-wave (mmWave) frequency range. The highly directional nature of 5G mmWave cellular systems poses a variety of fundamental differences and research problem formulations, and a holistic understanding of the key system design principles behind the 5G NR is essential. Here, we condense the relevant information collected from a wide diversity of 5G NR standardization documents (based on 3GPP Release 15) to distill the essentials of directional access in 5G mmWave cellular, which becomes the foundation for any corresponding system-level analysis.Comment: 14 pages, 6 figures, 4 tables, published in proceedings of International Conference on Next Generation Wired/Wireless Networking, NEW2AN 2018, St. Petersburg, Russi