Performance of multiple-input multiple-output wireless communications systems using distributed antennas

In this contribution we propose and investigate a multiple-input multiple-output (MIMO) wireless communications system, where multiple receive antennas are distributed in the area covered by a cellular cell and connected with the base-station (BS). We first analyze the total received power by the BS through the distributed antennas, when assuming that the mobile's signal is transmitted over lognormal shadowed Rayleigh fading channels. Then, the outage probability of the distributed antenna MIMO systems is investigated, when considering various antenna distribution patterns. Furthermore, space-time coding at the mobile transmitter is considered for enhancing the outage performance of the distributed antenna MIMO system. Our study and simulation results show that the outage performance of a distributed antenna MIMO system can be significantly improved, when either increasing the number of distributed receive antennas or increasing the number of mobile transmit antennas

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Uplink capacity of a variable density cellular system with multicell processing

In this work we investigate the information theoretic capacity of the uplink of a cellular system. Assuming centralised processing for all base stations, we consider a power-law path loss model along with variable cell size (variable density of Base Stations) and we formulate an average path-loss approximation. Considering a realistic Rician flat fading environment, the analytical result for the per-cell capacity is derived for a large number of users distributed over each cell. We extend this general approach to model the uplink of sectorized cellular system. To this end, we assume that the user terminals are served by perfectly directional receiver antennas, dividing the cell coverage area into perfectly non-interfering sectors. We show how the capacity is increased (due to degrees of freedom gain) in comparison to the single receiving antenna system and we investigate the asymptotic behaviour when the number of sectors grows large. We further extend the analysis to find the capacity when the multiple antennas used for each Base Station are omnidirectional and uncorrelated (power gain on top of degrees of freedom gain). We validate the numerical solutions with Monte Carlo simulations for random fading realizations and we interpret the results for the real-world systems

Fundamental Limits in MIMO Broadcast Channels

This paper studies the fundamental limits of MIMO broadcast channels from a high level, determining the sum-rate capacity of the system as a function of system paramaters, such as the number of transmit antennas, the number of users, the number of receive antennas, and the total transmit power. The crucial role of channel state information at the transmitter is emphasized, as well as the emergence of opportunistic transmission schemes. The effects of channel estimation errors, training, and spatial correlation are studied, as well as issues related to fairness, delay and differentiated rate scheduling

Capacity bounds and estimates for the finite scatterers MIMO wireless channel

We consider the limits to the capacity of the multiple-input–multiple-output wireless channel as modeled by the finite scatterers channel model, a generic model of the multipath channel which accounts for each individual multipath component. We assume a normalization that allows for the array gain due to multiple receive antenna elements and, hence, can obtain meaningful limits as the number of elements tends to infinity. We show that the capacity is upper bounded by the capacity of an identity channel of dimension equal to the number of scatterers. Because this bound is not very tight, we also determine an estimate of the capacity as the number of transmit/receive elements tends to infinity which is asymptotically accurate

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

Design considerations of MIMO antennas for mobile phones

YesThe paper presents a new modeling and design concept of antennas using polar- ization diversity of 2 £ 2 and 3 £ 3 Multiple Input Multiple Outputs (MIMO) system that is proposed for future mobile handsets. The channel capacity is investigated and discussed over Raleigh fading channel and compared to a linear/planner antenna array MIMO channel. The capacity is also discussed over three types of power azimuth spectrums. The results are compared to the constraints capacity limits in which the maximum capacity observed

Performance of Optimum Combining in a Poisson Field of Interferers and Rayleigh Fading Channels

This paper studies the performance of antenna array processing in distributed multiple access networks without power control. The interference is represented as a Poisson point process. Desired and interfering signals are subject to both path-loss fading (with an exponent greater than 2) and to independent Rayleigh fading. Using these assumptions, we derive the exact closed form expression for the cumulative distribution function of the output signal-to-interference-plus-noise ratio when optimum combining is applied. This results in a pertinent measure of the network performance in terms of the outage probability, which in turn provides insights into the network capacity gain that could be achieved with antenna array processing. We present and discuss examples of applications, as well as some numerical results.Comment: Submitted to IEEE Trans. on Wireless Communication (Jan. 2009