Ove Edfors

Massive MIMO for next generation wireless systems

Multi-user 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, and 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 extensive use of inexpensive low-power components, reduced latency, simplification of the MAC layer, and robustness against intentional jamming. The anticipated throughput depends 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 article presents an overview of the massive MIMO concept and contemporary research on the topic.

On channel estimation in OFDM systems

The use of multi-amplitude signaling schemes in wireless OFDM systems requires the tracking of the fading radio channel. The paper addresses channel estimation based on time-domain channel statistics. Using a general model for a slowly fading channel, the authors present the MMSE and LS estimators and a method for modifications compromising between complexity and performance. The symbol error rate for a 18-QAM system is presented by means of simulation results. Depending upon estimator complexity, up to 4 dB in SNR can be gained over the LS estimator.

OFDM channel estimation by singular value decomposition

We present and analyze low-rank channel estimators for orthogonal frequency-division multiplexing (OFDM) systems using the frequency correlation of the channel. Low-rank approximations based on the discrete Fourier transform (DFT) have been proposed, but these suffer from poor performance when the channel is not sample spaced. We apply the theory of optimal rank-reduction to linear minimum mean-squared error (LMMSE) estimators and show that these estimators, when using a fixed design, are robust to changes in channel correlation and signal-to-noise ratio (SNR). The performance is presented in terms of uncoded symbol-error rate (SER) for a system using 16-quadrature amplitude modulation (QAM).

Time and frequency synchronization for OFDM using PN-sequence preambles

Fast and reliable time and frequency synchronization is crucial for packet-based orthogonal frequency division multiplex (OFDM) systems. In this paper we compare and analyze preambles for OFDM systems based on repeated OFDM data symbols or repeated short pseudonoise sequences (PN-sequences). We make an analytical evaluation for AWGN channels and simulate the performance in oneand two-tap Rayleigh fading channels. The PN-based preamble gives better detection properties in terms of lower false detection probability and lower probability of missing the synchronization signal. The PN-based preamble has low peak-to-average power ratio and it makes it possible to use an ADC with one-bit quantization in stand-by mode. For frequency offset estimation both preambles give similar performance, but the PN-based preamble allows for a greater reduction in stand-by mode power consumption.

Analysis of DFT-Based Channel Estimators for OFDM

In this paper we analyze the performance of three low-complexity channel estimators, based on the discrete Fourier transform (DFT), for orthogonal frequency-division multiplexing (OFDM) systems. Estimators of this type have been analyzed for discrete-time channels, and we extend this analysis to continuous-time channels. We present analytical expressions for their mean-squared error (MSE) and evaluate their complexity vs. symbol-error rate (SER) for 16-QAM. The analysis shows that this type of estimators may experience an irreducible error floor at high SNRs. However, in one of the three estimators the error floor can be eliminated while the complexity stays low and the performance is maximized.

Is Orbital Angular Momentum (OAM) Based Radio Communication an Unexploited Area

We compare the technique of using the orbital angular momentum (OAM) of radio waves for generating multiple channels in a radio communication scenario with traditional multiple-in-multiple-out (MIMO) communication methods. We demonstrate that, for certain array configurations in free space, traditional MIMO theory leads to eigen-modes identical to the OAM states. From this we conclude that communicating over the sub-channels given by OAM states is a subset of the solutions offered by MIMO, and therefore does not offer any additional gains in capacity.

Massive MIMO Performance Evaluation Based on Measured Propagation Data

Massive MIMO, also known as very-large MIMO or large-scale antenna systems, is a new technique that potentially can offer large network capacities in multi-user scenarios. With a massive MIMO system, we consider the case where a base station equipped with a large number of antenna elements simultaneously serves multiple single-antenna users in the same time-frequency resource. So far, investigations are mostly based on theoretical channels with independent and identically distributed (i.i.d.) complex Gaussian coefficients, i.e., i.i.d. Rayleigh channels. Here, we investigate how massive MIMO performs in channels measured in real propagation environments. Channel measurements were performed at 2.6 GHz using a virtual uniform linear array (ULA), which has a physically large aperture, and a practical uniform cylindrical array (UCA), which is more compact in size, both having 128 antenna ports. Based on measurement data, we illustrate channel behavior of massive MIMO in three representative propagation conditions, and evaluate the corresponding performance. The investigation shows that the measured channels, for both array types, allow us to achieve performance close to that in i.i.d. Rayleigh channels. It is concluded that in real propagation environments we have characteristics that can allow for efficient use of massive MIMO, i.e., the theoretical advantages of this new technology can also be harvested in real channels.

Linear Pre-Coding Performance in Measured Very-Large MIMO Channels

Wireless communication using very-large multiple-input multiple-output (MIMO) antennas is a new research field, where base stations are equipped with a very large number of antennas as compared to previously considered systems. In theory, as the number of antennas increases, propagation properties that were random before start to become deterministic. Theoretical investigations with independent identically distributed (i.i.d.) complex Gaussian (Rayleigh fading) channels and unlimited number of antennas have been done, but in practice we need to know what benefits we can get from very large, but limited, number of antenna elements in realistic propagation environments. In this study we evaluate properties of measured residential-area channels, where the base station is equipped with 128 antenna ports. An important property to consider is the orthogonality between channels to different users, since this property tells us how advanced multi-user MIMO (MU-MIMO) pre-coding schemes we need in the downlink. We show that orthogonality improves with increasing number of antennas, but for two single-antenna users there is very little improvement beyond 20 antennas. We also evaluate sum-rate performance for two linear pre-coding schemes, zero-forcing (ZF) and minimum mean squared error (MMSE), as a function of the number of base station antennas. Already at 20 base station antennas these linear pre-coding schemes reach 98% of the optimal dirty-paper coding (DPC) capacity for the measured channels.

A flexible 100-antenna testbed for Massive MIMO

Massive multiple-input multiple-output (MIMO) is one of the main candidates to be included in the fifth generation (5G) cellular systems. For further system development it is desirable to have real-time testbeds showing possibilities and limitations of the technology. In this paper we describe the Lund University Massive MIMO testbed - LuMaMi. It is a flexible testbed where the base station operates with up to 100 coherent radio-frequency transceiver chains based on software radio technology. Orthogonal Frequency Division Multiplex (OFDM) based signaling is used for each of the 10 simultaneous users served in the 20 MHz bandwidth. Real time MIMO precoding and decoding is distributed across 50 Xilinx Kintex-7 FPGAs with PCI-Express interconnects. The unique features of this system are: (i) high throughput processing of 384 Gbps of real time baseband data in both the transmit and receive directions, (ii) low-latency architecture with channel estimate to precoder turnaround of less than 500 micro seconds, and (iii) a flexible extension up to 128 antennas. We detail the design goals of the testbed, discuss the signaling and system architecture, and show initial measured results for a uplink Massive MIMO over-the-air transmission from four single-antenna UEs to 100 BS antennas.

The effect of feedback quantization on the throughput of a multiuser diversity scheme

The impact of the quantization of SNR measurements on the throughput of a multiuser diversity scheme for constant-rate transmission is investigated under a block-Rayleigh fading assumption. In the downlink, each user measures its SNR, quantizes it, and feeds it back to the transmitter, which transmits a packet to the user with the highest quantized SNR. In the case of several users having the same quantized SNR, one of them is selected at random. It is concluded that using only a few quantization levels can yield a throughput that is only slightly less than the throughput obtained by using unquantized feedback.