Towards Very Large Aperture Massive MIMO: a measurement based study

Massive MIMO is a new technique for wireless communications that claims to offer very high system throughput and energy efficiency in multi-user scenarios. The cost is to add a very large number of antennas at the base station. Theoretical research has probed these benefits, but very few measurements have showed the potential of Massive MIMO in practice. We investigate the properties of measured Massive MIMO channels in a large indoor venue. We describe a measurement campaign using 3 arrays having different shape and aperture, with 64 antennas and 8 users with 2 antennas each. We focus on the impact of the array aperture which is the main limiting factor in the degrees of freedom available in the multiple antenna channel. We find that performance is improved as the aperture increases, with an impact mostly visible in crowded scenarios where the users are closely spaced. We also test MIMO capability within a same user device with user proximity effect. We see a good channel resolvability with confirmation of the strong effect of the user hand grip. At last, we highlight that propagation conditions where line-of-sight is dominant can be favorable

Hybrid ray-tracing/FDTD method for human exposure evaluation of a massive MIMO technology in an industrial indoor environment

This paper presents a numerical approach for massive multiple-input multiple-output (MIMO) human exposure assessment. It combines ray-tracing for the estimation of the wireless channel and the finite-difference time-domain method to simulate the exposure of a realistic human phantom. We apply it to estimate the exposure in a model of an industrial indoor environment with a single massive MIMO base station (BS). The exposure scenarios include line-of-sight and non-line-of-sight propagation with the BS using equal gain transmission precoding at 3.5 GHz. Calculated channel parameters are discussed in comparison with the data available in the literature. The exposure in the phantom's head is evaluated in terms of the peak-spatial specific absorption rate averaged over a 10-g cube and referenced to the free-space time-averaged Poynting vector magnitude at the same location

Spatial Separation of Closely-Spaced Users in Measured Massive Multi-User MIMO Channels

Fully-synchronous measurements of a massive multi-user multiple-input multiple-output (MU-MIMO) radio propagation channel are presented. We evaluate the ability of a massive MIMO system to spatially separate users located close to each other in line-of-sight (LOS) propagation conditions. The system consists of a base-station (BS) antenna array equipped with 64 dual-polarized antenna elements (128 ports) arranged in a cylindrical configuration, and eight single-antenna users. The users are confined to a five-meter diameter circle and move randomly at pedestrian speeds. The BS antenna array is located on top of a 20 m tall building and has LOS to the users. We examine user separability by studying singular value spread of the MU-MIMO channel matrix for several subsets of BS antenna array ports, along with sum-rate capacity and achievable sum-rates with both zero-forcing and matched-filtering linear precoders. We also analyze the performance of the user with the lowest rate. Finally, a comparison between the performance offered by the massive MIMO system and that of a conventional MU-MIMO system is provided. To the best of our knowledge, this is the first report of fully-synchronous dynamic measurements of a massive MIMO system. Our investigation shows that even users located close to each other in LOS propagation conditions can be spatially separated in a massive MIMO system

Short-Term Power Constrained Cell-Free Massive-MIMO Over Spatially Correlated Ricean Fading

This paper considers short-term power constrained cell-free massive multiple-input multiple-output (MIMO) scenarios where a large set of multi-antenna access points (APs) provide service to a group of single-antenna mobile stations (MSs) on a spatially correlated multipath environment. Based on a probabilistic approach, the spatially correlated propagation links are modeled using either Ricean or Rayleigh fading channel models that combine a deterministic line-of-sight (LOS) propagation path with a small-scale fading caused by non-line-of-sight (NLOS) multipath propagation. Assuming the use of minimum mean square error (MMSE) channel estimates, closed-form expressions for the downlink (DL) achievable spectral efficiency of a cellfree massive MIMO network with short-term power constraints (i.e., a vector normalized conjugate beamformer (NCB)) are derived and benchmarked against that provided by the conventional cell-free massive MIMO network with long-term power constraints (i.e., the conventional conjugate beamforming (CB)). These expressions, encompassing the effects of spatial antenna correlation, Ricean/Rayleigh fading and pilot contamination, are then used to derive both pragmatic and optimal max-min peruser power allocation strategies and to gain theoretical insight on the performance advantage provided by the use of short-term power constraints instead of the conventional long-term power constrained approach.This work was supported in part by the Agencia Estatal de Investigacion (AEI) of Spain under Grants TEC2017-90093-C3-2-R and TEC2017-90093-C3-3-R, and in part by the European Regional Development Fund (ERDF) funds of the European Union (EU) (AEI/FEDER, UE)

Temporal Analysis of Measured LOS Massive MIMO Channels with Mobility

The first measured results for massive multiple-input, multiple-output (MIMO) performance in a line-of-sight (LOS) scenario with moderate mobility are presented, with 8 users served by a 100 antenna base Station (BS) at 3.7 GHz. When such a large number of channels dynamically change, the inherent propagation and processing delay has a critical relationship with the rate of change, as the use of outdated channel information can result in severe detection and precoding inaccuracies. For the downlink (DL) in particular, a time division duplex (TDD) configuration synonymous with massive MIMO deployments could mean only the uplink (UL) is usable in extreme cases. Therefore, it is of great interest to investigate the impact of mobility on massive MIMO performance and consider ways to combat the potential limitations. In a mobile scenario with moving cars and pedestrians, the correlation of the MIMO channel vector over time is inspected for vehicles moving up to 29 km/h. For a 100 antenna system, it is found that the channel state information (CSI) update rate requirement may increase by 7 times when compared to an 8 antenna system, whilst the power control update rate could be decreased by at least 5 times relative to a single antenna system.Comment: Accepted for presentation at the 85th IEEE Vehicular Technology Conference in Sydney. 5 Pages. arXiv admin note: substantial text overlap with arXiv:1701.0881

Multi-Cell Massive MIMO in LoS

We consider a multi-cell Massive MIMO system in a line-of-sight (LoS) propagation environment, for which each user is served by one base station, with no cooperation among the base stations. Each base station knows the channel between its service antennas and its users, and uses these channels for precoding and decoding. Under these assumptions we derive explicit downlink and uplink effective SINR formulas for maximum-ratio (MR) processing and zero-forcing (ZF) processing. We also derive formulas for power control to meet pre-determined SINR targets. A numerical example demonstrating the usage of the derived formulas is provided.Comment: IEEE Global Communications Conference (GLOBECOM) 201

Capacity bounds for dense massive MIMO in a line-of-sight propagation environment

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive multiple-input multiple-output scenario, we derive analytical expressions for the sum-capacity. Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high signal-to-noise ratio regimes. Furthermore, in the case of low and high signal-to-noise ratio regimes, it is demonstrated that the Gamma probability density function can approximate the probability density function of the instantaneous channel sum-capacity as the number of served devices and base station antennas grows, respectively. A second important demonstration presented in this work is that a Gamma probability density function can also be used to approximate the probability density function of the summation of the channel's singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for a massive number of Internet of Things devices as we show that the transmit power of each device can be made inversely proportional to the number of base station antennas.20

Aspects of Favorable Propagation in Massive MIMO

Favorable propagation, defined as mutual orthogonality among the vector-valued channels to the terminals, is one of the key properties of the radio channel that is exploited in Massive MIMO. However, there has been little work that studies this topic in detail. In this paper, we first show that favorable propagation offers the most desirable scenario in terms of maximizing the sum-capacity. One useful proxy for whether propagation is favorable or not is the channel condition number. However, this proxy is not good for the case where the norms of the channel vectors may not be equal. For this case, to evaluate how favorable the propagation offered by the channel is, we propose a ``distance from favorable propagation'' measure, which is the gap between the sum-capacity and the maximum capacity obtained under favorable propagation. Secondly, we examine how favorable the channels can be for two extreme scenarios: i.i.d. Rayleigh fading and uniform random line-of-sight (UR-LoS). Both environments offer (nearly) favorable propagation. Furthermore, to analyze the UR-LoS model, we propose an urns-and-balls model. This model is simple and explains the singular value spread characteristic of the UR-LoS model well