Energy Efficient Delay Sensitive Optimization in SWIPT-MIMO

Abstract

In this paper, we consider joint antenna selection and optimal beamforming for energy efficient delay minimization. We assume multiple-input multi-output (MIMO) system with full duplex simultaneous wireless information and power transfer (FD-SWIPT) where each sensor is equipped with a power splitting (PS) system and can simultaneously receive both energy and information from the aggregator (AGG). We show that the antenna selection and beamforming power control policies are adaptive to the energy state information (ESI), the queue state information (QSI) and the channel state information (CSI). We develop an analytical framework for energy efficient delayoptimal control problem based on the theory of infinite horizon partially observable Markov decision process (POMDP). The infinite-horizon POMDP problem is transformed into an equivalent value Bellman program and solved by near-optimal pointbased Heuristic Search Value Iteration (PB-HSVI) method under specific standard conditions. The proposed solution outcome is a set of sub-optimal antenna selection and beamforming control policies. Simulation results reveal an effective trade-off between the contradictory objectives (i.e. delay and power consumption) and show the enhancement in delay by using FD-SWIPT systems in comparison to Half Duplex (HD)-SWIPT systems.

Challenges and Perspectives in Neuromorphic-based Visual IoT Systems and Networks

“…In these solutions the learning-based antenna assignment and beamforming power control policy can be adaptive to the users' energy state information (ESI), the users' queue state information (QSI) and/or the uplink/downlink channel state information (CSI). The work in [17] developed an analytical framework for the latency-optimal control problem based on the theory of infinite horizon partially observable Markov decision process (POMDP). In this POMDP method, the proposed optimal protocols optimize the transposition delay of the user while limiting the energy consumption by users and the aggregator.…”