Compressive Channel Estimation and Tracking for Large Arrays in mm-Wave Picocells

Abstract

Abstract-We propose and investigate a compressive architecture for estimation and tracking of sparse spatial channels in millimeter (mm) wave picocellular networks. The base stations are equipped with antenna arrays with a large number of elements (which can fit within compact form factors because of the small carrier wavelength) and employ radio frequency (RF) beamforming, so that standard least squares adaptation techniques (which require access to individual antenna elements) are not applicable. We focus on the downlink, and show that "compressive beacons," transmitted using pseudorandom phase settings at the base station array, and compressively processed using pseudorandom phase settings at the mobile array, provide information sufficient for accurate estimation of the two-dimensional (2D) spatial frequencies associated with the directions of departure of the dominant rays from the base station, and the associated complex gains. This compressive approach is compatible with coarse phase-only control, and is based on a near-optimal sequential algorithm for frequency estimation which can exploit the geometric continuity of the channel across successive beaconing intervals to reduce the overhead to less than 1% even for very large (32 × 32) arrays. Compressive beaconing is essentially omnidirectional, and hence does not enjoy the SNR and spatial reuse benefits of beamforming obtained during data transmission. We therefore discuss system level design considerations for ensuring that the beacon SNR is sufficient for accurate channel estimation, and that inter-cell beacon interference is controlled by an appropriate reuse scheme.

Compressed Sensing Channel Estimation for OFDM With Non-Gaussian Multipath Gains

“…We represented (31) in Fig. 3(a), where we see that it approximates (29) and lower bounds ρ(d). Fig.…”

“…We use the Binary-search Local Maximum Refinement described in Alg. 2, rather than a gradient as [29], to guarantee that OMPBR is robust in the sense that the result is contained in the bin and never worse than the decision that OMP would make. Lemma 1 shows Alg.…”

Channel estimation via gradient pursuit for mmWave massive MIMO systems with one-bit ADCs

“…In practice, the complexity of Algorithms 2 and 3 is demanding because h(x) and ∇h(x) are required at each iteration, which are high-dimensional functions defined on C B where B ≫ M N . In recent works on channel estimation and data detection in the mmWave band [14], [15], [28], the FFT-based implementation is widely used because H can be approximated by (7) using overcomplete DFT matrices. In this paper, an FFT-based fast implementation of h(x) and ∇h(x) is proposed, which is motivated by [14], [15], [28].…”

Channel Fingerprint Based Beam Tracking for Millimeter Wave Communications

“…Many research efforts have been devoted to designing highefficient beam training schemes, such as using configurable beam width for adaptive beam search [2], sending pseudorandom beacons to apply compressive sensing techniques [3], double-link beam tracking to overcome the blockage problem [4], probabilistic beam tracking for hybrid beamforming architectures [5], adaptive beam tracking with the unscented kalman filter [6] and narrowing down the search range with the historical training results [7]. Channel fingerprints can also This act as useful historical information to aid beam tracking.…”