Millimeter Wave MIMO Channel Tracking Systems

We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multiple-input multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respectively. In the absence of straightforward time-correlated channel model in the millimeter wave MIMO literature, we present a temporal MIMO channel evolution model for NLoS millimeter wave scenarios. Considering that conventional MIMO channel tracking algorithms in microwave bands are not directly applicable, we propose a new channel tracking technique based on sequentially updating the precoder and combiner. Numerical results demonstrate the superior channel tracking ability of the proposed technique over independent sounding approach in the presented channel model and the spatial channel model (SCM) adopted in 3GPP specification.Comment: 6 pages, 3 figures, conferenc

Beam and Channel Tracking for 5G Communication Systems Using Adaptive Filtering Techniques: A Comparison Study

In this paper, we study the problem of beam tracking of a multipath channel in millimeter-wave massive MIMO communication system using adaptive filters. We focus on the performance of least-mean-square filter (LMS) and recursive least-squares filter (RLS) algorithms, compared to a reference extended Kalman filter (EKF), in scenarios where the wireless channel is dominated by a single line of sight (LOS) path or a small number of strong paths. The signal direction and channel coefficients are tracked and updated using these filters. Our results recommend that beamforming systems at millimeter-wave bands should consider variable number of paths rather than a single dominant LOS path. Furthermore, we show that the mean squared-error (MSE) of the innovation process gives a better overall view of the tracking performance than the MSE of the state parameters

mm-Wave channel estimation with accelerated gradient descent algorithms

Abstract The availability of millimeter wave (mm-Wave) band in conjunction with massive multiple-input-multiple-output (MIMO) technology is expected to boost the data rates of the fifth-generation (5G) cellular systems. However, in order to achieve high spectral efficiencies, an accurate channel estimate is required, which is a challenging task in massive MIMO. By exploiting the small number of paths that characterize the mm-Wave channel, the estimation problem can be solved by compressed-sensing (CS) techniques. In this paper, we propose a novel CS channel estimation method based on the accelerated gradient descent with adaptive restart (AGDAR) algorithm exploiting a ℓ 1-norm approximation of the sparsity constraint. Moreover, a modified re-weighted compressed-sensing (RCS) technique is considered that iterates AGDAR using a weighted version of the ℓ 1-norm term, where weights are adapted at each iteration. We also discuss the impact of cell sectorization and tracking on the channel estimation algorithm. We compare the proposed solutions with existing channel estimations with an extensive simulation campaign on downlink third-generation partnership project (3GPP) channel models

Subspace Tracking and Least Squares Approaches to Channel Estimation in Millimeter Wave Multiuser MIMO

The problem of MIMO channel estimation at millimeter wave frequencies, both in a single-user and in a multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp. left) singular vectors at the transmitter (resp. receiver) side; then, we adapt the projection approximation subspace tracking with deflation and the orthogonal Oja algorithms to our framework and obtain two channel estimation algorithms. We also present an alternative algorithm based on the least squares approach. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. In order to limit the system complexity, a fixed analog beamformer is used at both sides of the communication links. The obtained numerical results, showing the accuracy in the estimation of the channel matrix dominant singular vectors, the system achievable spectral efficiency, and the system bit-error-rate, prove that the proposed algorithms are effective, and that they compare favorably, in terms of the performance-complexity trade-off, with respect to several competing alternatives.Comment: To appear on the IEEE Transactions on Communication

Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter

Pilot Beam Sequence Design for Channel Estimation in Millimeter-Wave MIMO Systems: A POMDP Framework

In this paper, adaptive pilot beam sequence design for channel estimation in large millimeter-wave (mmWave) MIMO systems is considered. By exploiting the sparsity of mmWave MIMO channels with the virtual channel representation and imposing a Markovian random walk assumption on the physical movement of the line-of-sight (LOS) and reflection clusters, it is shown that the sparse channel estimation problem in large mmWave MIMO systems reduces to a sequential detection problem that finds the locations and values of the non-zero-valued bins in a two-dimensional rectangular grid, and the optimal adaptive pilot design problem can be cast into the framework of a partially observable Markov decision process (POMDP). Under the POMDP framework, an optimal adaptive pilot beam sequence design method is obtained to maximize the accumulated transmission data rate for a given period of time. Numerical results are provided to validate our pilot signal design method and they show that the proposed method yields good performance.Comment: 6 pages, 6 figures, submitted to IEEE ICC 201