Mikael Coldrey

Self-interference suppression in full-duplex MIMO relays

Full-duplex relays can provide cost-effective cover-age extension and throughput enhancement. However, the main limiting factor is the resulting self-interference signal which deteriorates the relay performance. In this paper, we propose a novel technique for self-interference suppression in full-duplex Multiple-Input Multiple-Output (MIMO) relays. The relay employs transmit and receive weight filters for suppressing the self-interference signal. Unlike existing techniques that are based on zero forcing of self-interference, we aim at maximizing the ratio between the power of the useful signal to the self-interference power at the relay reception and transmission. Our simulation results show that the proposed algorithm outperforms the existing schemes since it can suppress interference substantially with less impact on the useful signal.

Modeling and Capacity of Polarized MIMO Channels

In this work the modeling and capacity of a dual polarized (DP) MIMO channel is addressed. The modeling includes channel parameters such as receive and transmit correlation, channel cross-polarization discrimination (XPD), and antenna parameters such as polarization state, polarization parallelity and coupling. The capacity of the DP MIMO channel is evaluated and compared to the capacity of a single polarized (SP) MIMO system. The SP MIMO system with spatially separated antenna sensors has the advantage that it also offers array gain and will therefore during idealized conditions outperform the DP MIMO system. However, in this work it is found that this advantage often is reduced and sometimes even lost when channel and antenna imperfections such as, e.g., correlation, channel XPD, and polarization mismatch are introduced. The main conclusion is that DP antennas might not always yield the best MIMO performance, but instead offer compact antenna solutions for mobile devices and robust performance that is more insensitive to the aforementioned imperfections.

Training-Based MIMO Systems—Part I: Performance Comparison

In this paper, we make a performance comparison between two different training-based schemes for multiple-input multiple-output (MIMO) channel estimation. The two schemes are the conventional time-multiplexed pilot (CP) scheme and the more recently suggested superimposed pilot (SIP) scheme. Unlike previous comparisons found in the literature, which are mostly based on estimation error performances, the performance comparison in this paper is made by deriving and comparing the maximum data rate (or rather a tight lower bound on the maximum mutual information) achieved by each scheme. By using the maximum mutual information criterion, for each training scheme, we can optimally allocate the time and power spent on transmission of training and data sequences. Once the system parameters (time and power) are tuned to give optimal performance, we can compare their respective maximum data rate. The theory is applied to a blockwise flat-fading MIMO channel, and it is found that in certain scenarios (such as many receive antennas and/or short channel coherence times), it is beneficial to use the SIP. In other scenarios, the SIP scheme suffers from a higher estimation error, and its gain over the CP scheme is often lost.

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 non-linearity introduced by the one-bit ADCs.

Non-line-of-sight small cell backhauling using microwave technology

In this article we discuss different technology alternatives for small cell backhaul, and we present high-frequency microwave technology as a very interesting alternative for wireless backhauling of small cells. In fact, we demonstrate that high-frequency microwave technology can be used for NLOS wireless backhauling of small cells, which opens up new applications for microwave technology. We discuss urban NLOS channel propagation at high frequencies, and we show both measurement and simulation results to validate the use of high-frequency microwave technology for NLOS small cell backhaul.

Throughput Analysis of Massive MIMO Uplink With Low-Resolution ADCs

We investigate the uplink throughput achievable by a multiple-user (MU) massive multiple-input multiple-output (MIMO) system, in which the base station is equipped with a large number of low-resolution analog-to-digital converters (ADCs). Our focus is on the case where neither the transmitter nor the receiver have any a priori channel state information. This implies that the fading realizations have to be learned through pilot transmission followed by channel estimation at the receiver, based on coarsely quantized observations. We propose a novel channel estimator, based on Bussgang’s decomposition, and a novel approximation to the rate achievable with finite-resolution ADCs, both for the case of finite-cardinality constellations and of Gaussian inputs, that is accurate for a broad range of system parameters. Through numerical results, we illustrate that, for the 1-bit quantized case, pilot-based channel estimation together with maximal-ratio combing, or zero-forcing detection enables reliable multi-user communication with high-order constellations, in spite of the severe nonlinearity introduced by the ADCs. Furthermore, we show that the rate achievable in the infinite-resolution (no quantization) case can be approached using ADCs with only a few bits of resolution. We finally investigate the robustness of low-ADC-resolution MU-MIMO uplink against receive power imbalances between the different users, caused for example by imperfect power control.

On the MIMO capacity with residual transceiver hardware impairments

Radio-frequency (RF) impairments in the transceiver hardware of communication systems (e.g., phase noise (PN), high power amplifier (HPA) nonlinearities, or in-phase/quadrature-phase (I/Q) imbalance) can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although calibration algorithms can partially compensate these impairments, the remaining distortion still has substantial impact. Despite this, most prior works have not analyzed this type of distortion. In this paper, we investigate the impact of residual transceiver hardware impairments on the MIMO system performance. In particular, we consider a transceiver impairment model, which has been experimentally validated, and derive analytical ergodic capacity expressions for both exact and high signal-to-noise ratios (SNRs). We demonstrate that the capacity saturates in the high-SNR regime, thereby creating a finite capacity ceiling. We also present a linear approximation for the ergodic capacity in the low-SNR regime, and show that impairments have only a second-order impact on the capacity. Furthermore, we analyze the effect of transceiver impairments on large-scale MIMO systems; interestingly, we prove that if one increases the number of antennas at one side only, the capacity behaves similar to the finite-dimensional case. On the contrary, if the number of antennas on both sides increases with a fixed ratio, the capacity ceiling vanishes; thus, impairments cause only a bounded offset in the capacity compared to the ideal transceiver hardware case.

Efficient Channel Estimation Techniques for Amplify and Forward Relaying Systems

In this paper, we present a channel estimation scheme for Amplify-and-Forward (AF) relaying systems, using measurements at the destination only. A Least-Squares (LS) based channel estimation algorithm is developed, that provides the destination with full knowledge of all channel responses involved in the transmission. To investigate the algorithm performance, the Cramer-Rao lower bound (CRB) is analytically computed and compared with the asymptotic covariance of the proposed estimator. Since the existing estimator does not reach the CRB, we also propose and analyze an improved algorithm by taking into account the noise characteristics via weighted LS (WLS). The improved algorithm is asymptotically efficient, since it attains the CRB as the SNR tends to infinity.

Quantized Precoding for Massive MU-MIMO

Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang’s theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3–4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared with the infinite-resolution case for an uncoded bit-error rate of 10−3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB.

Coordinated 3D Beamforming for Interference Management in Cellular Networks

We consider downlink transmission in a cellular network consisting of multi-antenna base stations (BSs), single-antenna mobile users, directional antennas each with a vertically adjustable beam, and control signaling delays in feedback and backhaul links. We propose a novel transmission technique in which intercell interference management is performed via coordinating the beamforming jointly in the horizontal and vertical planes of the wireless channel, denoted as coordinated 3D beamforming. In the horizontal plane, we focus on intercell interference cancelation (ICIC) and investigate its performance when the provided channel state information (CSI) is impaired due to delay/mobility. It is demonstrated that the superiority of ICIC over conventional intracell maximum ratio transmission is highly dependent on the CSI accuracy. In the vertical plane, we consider intercell interference control via coordinatively adapting the elevation angle of the BS antenna pattern, denoted as tilt, to the locations of the scheduled users. It is shown that with perfect CSI interference management should be performed in the horizontal plane using ICIC, while at high delay/mobility it should be done in the vertical plane via coordinated tilt adaptation. For intermediate values of delay/mobility, joint interference management in both planes is required.