Rate and Reliability Trade-Off for mmWave Communication via Multi-Point Connectivity

Abstract

The fundamental challenge of mmWave frequency band is the sensitivity of the radio channel to blockage, which gives rise to unstable connectivity and also impacts the reliability of a system. In this paper, we explore the viability of using Coordinated Multi-point (CoMP) connectivity for robust and resilient downlink communication. We provide a novel iterative algorithm for Weighted Sum-Rate Maximization (WSRM) problem leveraging Successive Convex Approximation (SCA) with low computational complexity, which admits closed-form solution via iterative evaluation of optimal Karush-Kuhn-Tucker (KKT) conditions. Unlike in the conventional CoMP schemes, the propose precoder design has, per-iteration, computational complexity in the order of base-station (BS) antennas instead of system-wide joint transmit antennas. This is achieved by splitting the beamformer design to be parallel across the coordinating BSs. For the downlink precoder design, a conservative estimate of the user specific rate is obtained by considering possible combinations of potentially blocked links. In the presence of random blockages, the effective throughput and outage performance of the proposed method significantly outperform several baseline scenarios, hence providing more reliable connectivity.

Stochastic Learning Robust Beamforming for Millimeter-Wave Systems With Path Blockage

“…It has been shown [11], [15], [18], [19] that unpredictable blockages occur with 20%-60% probability, leading to significant loss in the achievable throughput. In order to abstract such non-ideal effects, we consider a probabilistic model [15], [16], in which each path undergoes random and independent blockage, whose frequency of occurrence can however be obtained as side-information for the system optimization, as shown in [13]. In other words, the blockage probability of each component channel path can be assumed to be known at the BSs and employed in robust beamforming designs.…”

“…B. Problem Formulation Given the system model described above, in this subsection we offer an optimization problem formulation corresponding to the mmWave robust CoMP downlink beamforming design subject to unpredictable path blockage, which does not rely on a standard deterministic robust optimization framework such as the ones considered, e.g., in [15], [16].…”

“…In turn, in [15], [16], a robust coordinated multipoint (CoMP) beamforming design based on the worst case optimization approach has been proposed to ensure a prescribed communication performance under such random blockages.…”

“…In this letter we contribute to this trending topic by proposing a stochastic framework for the design of outage-minimum robust mmWave CoMP systems, which has two main differences over the state-of-the-art proposed in [15], [16]. First, while the algorithm proposed in [15], [16] relies on the wellknown worst-case optimization approach [17], which requires all conceivable quality of service (QoS) constraints to be considered thus leading to high computational complexities and possible instabilities, 1 our proposed method is based on an stochastic optimization framework that enables us to avoid dealing with such combinatorial operations and yields decent solutions even in ill-conditioned scenarios. Secondly, while a maximization problem with a sum-rate objective was considered in [15], [16], the fundamental goal of robust beamforming design for mmWave systems subjected to uncertain blockage is rather to minimize the required QoS violation (i.e., outage probability), indicating that the formulation in the latter is somewhat sub-optimal.…”

Reliable Positioning and mmWave Communication via Multi-Point Connectivity

“…Finally, we present numerical examples to quantify the complexity and the performance advantages of proposed solutions in terms of achievable sum-rate and reliable connectivity. The paper is an extended version of our previously published conference papers [23], [24]. In [23] we investigated WSRM design leveraging the SCA framework.…”