Analysis of Massive MIMO With Hardware Impairments and Different Channel Models

Massive Multiple-Input Multiple-Output (MIMO) is foreseen to be one of the main technology components in next generation cellular communications (5G). In this paper, fundamental limits on the performance of downlink massive MIMO systems are investigated by means of simulations and analytical analysis. Signal-to-noise-and-interference ratio (SINR) and sum rate for a single-cell scenario multi-user MIMO are analyzed for different array sizes, channel models, and precoding schemes. The impact of hardware impairments on performance is also investigated. Simple approximations are derived that show explicitly how the number of antennas, number of served users, transmit power, and magnitude of hardware impairments affect performance.Comment: 5 pages, 5 figure

Impact of Spatial Filtering on Distortion from Low-Noise Amplifiers in Massive MIMO Base Stations

In massive MIMO base stations, power consumption and cost of the low-noise amplifiers (LNAs) can be substantial because of the many antennas. We investigate the feasibility of inexpensive, power efficient LNAs, which inherently are less linear. A polynomial model is used to characterize the nonlinear LNAs and to derive the second-order statistics and spatial correlation of the distortion. We show that, with spatial matched filtering (maximum-ratio combining) at the receiver, some distortion terms combine coherently, and that the SINR of the symbol estimates therefore is limited by the linearity of the LNAs. Furthermore, it is studied how the power from a blocker in the adjacent frequency band leaks into the main band and creates distortion. The distortion term that scales cubically with the power received from the blocker has a spatial correlation that can be filtered out by spatial processing and only the coherent term that scales quadratically with the power remains. When the blocker is in free-space line-of-sight and the LNAs are identical, this quadratic term has the same spatial direction as the desired signal, and hence cannot be removed by linear receiver processing

Out-of-Band Radiation Measure for MIMO Arrays with Beamformed Transmission

The spatial characteristics of the out-of-band radiation that a multiuser MIMO system emits in the environment, due to its power amplifiers (modeled by a polynomial model) are nonlinear, is studied by deriving an analytical expression for the continuous-time cross-correlation of the transmit signals. At a random spatial point, the same power is received at any frequency on average with a MIMO base station as with a SISO base station when the two radiate the same amount of power. For a specific channel realization however, the received power depends on the channel. We show that the power received out-of-band only deviates little from the average in a MIMO system with multiple users and that the deviation can be significant with only one user. Using an ergodicity argument, we conclude that out-of-band radiation is less of a problem in massive MIMO, where total radiated power is lower compared to SISO systems and that requirements on spectral regrowth can be relaxed in MIMO systems without causing more total out-of-band radiation

Spatial Characteristics of Distortion Radiated from Antenna Arrays with Transceiver Nonlinearities

The distortion from massive MIMO (multiple-input--multiple-output) base stations with nonlinear amplifiers is studied and its radiation pattern is derived. The distortion is analyzed both in-band and out-of-band. By using an orthogonal Hermite representation of the amplified signal, the spatial cross-correlation matrix of the nonlinear distortion is obtained. It shows that, if the input signal to the amplifiers has a dominant beam, the distortion is beamformed in the same way as that beam. When there are multiple beams without any one being dominant, it is shown that the distortion is practically isotropic. The derived theory is useful to predict how the nonlinear distortion will behave, to analyze the out-of-band radiation, to do reciprocity calibration, and to schedule users in the frequency plane to minimize the effect of in-band distortion

IT development in the local setting - an architectural perspective

The objective of this article is to describe some relevant undertakings related to the introduction of local communication networks in residential areas in Sweden and to broaden the discussion on the ongoing IT development and its influence on local settings and living. A further objective is to discuss how current and expected changes might influence research in architecture and its relevance for the architectural profession

One-Bit Massive MIMO: Channel Estimation and High-Order Modulations

We investigate the information-theoretic throughout achievable on a fading communication link when the receiver is equipped with one-bit analog-to-digital converters (ADCs). The analysis is conducted for the setting where neither the transmitter nor the receiver have a priori information on the realization of the fading channels. This means that channel-state information needs to be acquired at the receiver on the basis of the one-bit quantized channel outputs. We show that least-squares (LS) channel estimation combined with joint pilot and data processing is capacity achieving in the single-user, single-receive-antenna case. We also investigate the achievable uplink throughput in a massive multiple-input multiple-output system where each element of the antenna array at the receiver base-station feeds a one-bit ADC. We show that LS channel estimation and maximum-ratio combining are sufficient to support both multiuser operation and the use of high-order constellations. This holds in spite of the severe nonlinearity introduced by the one-bit ADCs

Modelado estadístico de amplificadores no lineales

Complexity relaxations in wireless communication systems operating at the boundaries of components performance are foreseen. Due to this matter, a need to properly characterize hardware impairments degrading the performance of communications links has been recognized in previous studies. Statistical models might be the definitive tool for assessing the impact of these non-idealities. Particularly, the non-linearity of power amplifiers in multi-antenna scenarios was examined in this thesis. To this matter, a full revision of a novel method capable of capturing this limitation for a single-antenna and thus, a single power amplifier, was carried out. Thereafter, the strategy was to commence with the simplest multiantenna case and to increase the number of antennas and users until a general model was achieved. Results of the developed models in the thesis are provided concluding that these kind of approaches are valid to model the non-linear nature of power amplifiers in MIMO systems. Another studies of the evolution of this distortion when varying the number of antennas and users are also presented and analyzed

Massive MU-MIMO-OFDM Uplink with Hardware Impairments: Modeling and Analysis

We study the impact of hardware impairments at the base station (BS) of an orthogonal frequency-division multiplexing (OFDM)-based massive multiuser (MU) multiple-input multiple-output (MIMO) uplink system. We leverage Bussgang's theorem to develop accurate models for the distortions caused by nonlinear low-noise amplifiers, local oscillators with phase noise, and oversampling finite-resolution analog-to-digital converters. By combining the individual effects of these hardware models, we obtain a composite model for the BS-side distortion caused by nonideal hardware that takes into account its inherent correlation in time, frequency, and across antennas. We use this composite model to analyze the impact of BS-side hardware impairments on the performance of realistic massive MU-MIMO-OFDM uplink systems

Low Complexity Joint Impairment Mitigation of I/Q Modulator and PA Using Neural Networks

neural networks (NNs) for multiple hardware impairments mitigation of a realistic direct conversion transmitter are impractical due to high computational complexity. We propose two methods to reduce the complexity without significant performance penalty. First, propose a novel NN with shortcut connections, referred to as shortcut real-valued time-delay neural network (SVDEN), where trainable neuron-wise shortcut connections are added between the input and output layers. Second, we implement a NN pruning algorithm that gradually removes connections corresponding to minimal weight magnitudes in each layer. Simulation and experimental results show that SVDEN with pruning achieves better performance for compensating frequency-dependent quadrature imbalance and power amplifier nonlinearity than other NN-based and Volterra-based models, while requiring less or similar complexity