Tracking angles of departure and arrival in a mobile millimeter wave channel

Abstract

Abstract-Millimeter wave provides a very promising approach for meeting the ever-growing traffic demand in next generation wireless networks. To utilize this band, it is crucial to obtain the channel state information in order to perform beamforming and combining to compensate for severe path loss. In contrast to lower frequencies, a typical millimeter wave channel consists of a few dominant paths. Thus it is generally sufficient to estimate the path gains, angles of departure (AoDs), and angles of arrival (AoAs) of those paths. Proposed in this paper is a dual timescale model to characterize abrupt channel changes (e.g., blockage) and slow variations of AoDs and AoAs. This work focuses on tracking the slow variations and detecting abrupt changes. A Kalman filter based tracking algorithm and an abrupt change detection method are proposed. The tracking algorithm is compared with the adaptive algorithm due to Alkhateeb, Ayach, Leus and Heath (2014) in the case with single radio frequency chain. Simulation results show that to achieve the same tracking performance, the proposed algorithm requires much lower signal-to-noise-ratio (SNR) and much fewer pilots than the other algorithm. Moreover, the change detection method can always detect abrupt changes with moderate number of pilots and SNR.

Supervised learning and graph signal processing strategies for beam tracking in highly directional mobile communications

“…Both AoD and AoA can be estimated using beam training procedure, and if one identifies the dominant angular bins, one can make channel estimation without incurring in excessive computational complexity. With a time-variant approach, an EKF was used as a tracking filter, which is applied at each step on the elements of the measurement matrix, in contrast with the technique proposed in the work of Zhang et al 3 The main drawback in the beam tracking technique proposed in the work of Va et al 4 is the performance degradation when too narrow beams are assumed, due to beam misalignment during the measurement. This beam tracking technique exploits the continuous nature of time-varying AoD for beam selection.…”

Joint Space-Time Block-Coding and Beamforming for the Multiuser Radio Over Plastic Fiber Downlink

“…The beamforming employed in this paper is analog beamforming, which requires the knowledge of the Angle of Departure (AoD) at the transmitter. The AoD can be estimated using the techniques reported in [14], [15]. On the other hand, STBC requires the knowledge of the channel impulse response at the receivers, which can be estimated as reported in [16].…”

“…Then, in our design, this information is fed back over the fiber to the tunable frequency generator of Figure 2 through the POF, where the corresponding driving frequencies are applied. Explicitly, the AoD can be accurately estimated using classic techniques reported in the literature, such as the direction search for the largest gain used in the IEEE 802.11ad standard [14], the Kalman filter based tracking algorithm presented in [14] and the path search techniques using different beamwidths [15]. Additionally, several channel estimation technniques have been proposed for STBC in the literature, including closed-form blind channel estimation [16].…”

Beam Allocation for Millimeter-Wave MIMO Tracking Systems

“…To date, most existing works that investigate beam tracking techniques for mmWave channels have focused on the assumption that the values of AoA and AoD vary smoothly. In [15]- [19], the temporal variation of AoA/AoD over the considered period of time is assumed to follow a Markov process, and the AoA's and AoD's deviations between two consecutive channel realizations are modeled as small Gaussian random variables, based on which various Kalman filter-based beam tracking algorithms have been developed. It is also worth mentioning that the authors in [20]- [23] have proposed to employ the mobile users' location and trajectory information to reduce the beam training overhead.…”