Serving 22 Users in Real-Time with a 128-Antenna Massive MIMO Testbed

Abstract

This paper presents preliminary results for a novel 128-antenna massive Multiple-Input, Multiple-Output (MIMO) testbed developed through Bristol Is Open in collaboration with National Instruments and Lund University. We believe that the results presented here validate the adoption of massive MIMO as a key enabling technology for 5G and pave the way for further pragmatic research by the massive MIMO community. The testbed operates in real-time with a Long-Term Evolution (LTE)-like PHY in Time Division Duplex (TDD) mode and supports up to 24 spatial streams, providing an excellent basis for comparison with existing standards and complimentary testbeds. Through line-of-sight (LOS) measurements at 3.51 GHz in an indoor atrium environment with 12 user clients, an uncoded system sum-rate of 1.59 Gbps was achieved in real-time using a single 20 MHz LTE band, equating to 79.4 bits/s/Hz. In a subsequent indoor trial, 22 user clients were successfully served, which would equate to 145.6 bits/s/Hz using the same frame schedule. To the best of the author's knowledge, these are the highest spectral efficiencies achieved for any wireless system to date.

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

“…For Massive MIMO it is especially crucial, since performance is dependent on propagation characteristics, and measurement-based channel models themselves are still under development. Thanks to recent advances in Software-Defined Radio (SDR) technology, several Massive MIMO prototype systems have been built by both industry and academia, including the Argos testbed with 96 antennas [10], Eurecom's 64-antenna testbed [64], Facebook's ARIES project [65], the 100-antenna LuMaMi testbed from Lund University (Figure 20a) [63], SEU's 128-antenna testbed [5], and testbeds exploring distributed arrays from the KU Leuven (Figure 20b) [66] and University of Bristol [67].…”

“…Diverse field trials, both indoors and outdoors with static and mobile users, have been conducted using the Massive MIMO testbeds. In a 2016 experiment, a 128-antenna Massive MIMO base station served 22 users, each transmitting with 256-QAM modulation, on the same time-frequency resource [67]. The spectral efficiency benefits from the spatial multiplexing as well as from the high constellation order, enabled by the array gain.…”

Massive MIMO Optimization With Compatible Sets

“…This allows us to exploit favorable propagation, that is, that the channel responses from each antenna at the base station to the different user terminals are sufficiently different to allow separation of the users' data streams by digital pre-and post-processing. In the presence of favorable propagation and a large number of antennas, an effect known as channel hardening [9] arises, and a radical increase in spectral efficiency is possible [10]. Channel hardening means that each channel will be close to its expected value and channel variation is negligible in both the time and frequency domains.…”

EVM Prediction for Massive MIMO

“…Massive multiple-input, multiple-output (Ma-MIMO) is a multi-user (MU) multiple-input, multiple-output (MIMO) architecture with a large number of antennas at the base station (BS) serving several users within the same time and frequency resource [1]. The significant capacity enhancements observations and reporting from various field trials have encouraged the industry to consider Ma-MIMO as key 5G technology for sub-6 GHz wireless access [2] [3]. Theory indicates that the user channel vectors become pairwise orthogonal as the number of BS antennas is increased, facilitating the effective use of matched filtering (MF) [1].…”

“…The level of spatial orthogonality achieved when using a practical number of antennas in real channels may not be ideal. When the individual user channels become correlated, zero-forcing (ZF) or Minimum Mean Square Error (MMSE) become necessary for reliable data transmission [3] [5]. These linear techniques can suppress the interference between users, but this requires perfect channel state information (CSI).…”