Beamforming Optimization for Intelligent Reflecting Surface-Aided SWIPT IoT Networks Relying on Discrete Phase Shifts

Abstract

Intelligent reflecting surface (IRS) is capable of constructing the favorable wireless propagation environment by leveraging massive low-cost reconfigurable reflectarray elements. In this paper, we investigate the IRS-aided MIMO simultaneous wireless information and power transfer (SWIPT) for Internet of Things (IoT) networks, where the active base station (BS) transmit beamforming and the passive IRS reflection coefficients are jointly optimized for maximizing the minimum signal-tointerference-plus-noise ratio (SINR) among all information decoders (IDs), while maintaining the minimum total harvested energy at all energy receivers (ERs). Moreover, the IRS with practical discrete phase shifts is considered, and thereby the max-min SINR problem becomes a NP-hard combinatorial optimization problem with a strong coupling among optimization variables. To explore the insights and generality of this maxmin design, both the Single-ID Single-ER (SISE) scenario and the Multiple-IDs Multiple-ERs (MIME) scenario are studied. In the SISE scenario, the classical combinatorial optimization techniques, namely the special ordered set of type 1 (SOS1) and the reformulation-linearization (RL) technique, are applied to overcome the difficulty of this max-min design imposed by discrete optimization variables. Then the optimal branch-and-bound algorithm and suboptimal alternating optimization algorithm are respectively proposed. We further extend the idea of alternating optimization to the MIME scenario. Moreover, to reduce the iteration complexity, a two-stage scheme is considered aiming to separately optimize the BS transmit beamforming and the IRS reflection coefficients. Finally, numerical simulations demonstrate the superior performance of the proposed algorithms over the benchmarks in both the two scenarios.

Reconfigurable Intelligent Surface Aided Multi-User Communications: State-of-the-Art Techniques and Open Issues

“…Some energy receivers such as humidity sensors require higher operational energy than required by a typical information receiver [119]. To realize SWIPT in practice, there are various utilized receiver protocols, such as Power Splitting (PS), Time Switching (TS), and hybrid versions of the two [147], [156].…”

“…Another recent study in [156] attempted to solve the maxmin fairness of the IRS-assisted MIMO SWIPT IoT networks consisting of a multi-antenna BS, an IRS with discrete phase shifts and two groups of IoT SWIPT devices, i.e, multiple single-antenna information receivers and multiple multi-antenna energy receivers. To simplify the problem, the authors considered the max-min SINR problem of a single information receiver via jointly optimizing the transmit beamforming vector and IRS reflection matrix subject to the EH constraints of the energy receivers.…”

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

“…Based on the BER in (6), it can be numerically demonstrated that P E is not strictly decreasing versus L when the values of κ i are not equal for all values of i. Consequently, only a subset of elements should be selected while all others should be switched off.…”

“…The used sets of κ are, κ 3 with 4 reflectors have κ = 20, while κ for the remaining reflectors is uniformly distributed over [0, 1]. On the other hand, κ 4 = [20,20,20,20,20,9,8,7,6,5,4,3,2,1,0]. Both Fig.…”

Optimum Elements Selection in IRS-Assisted UAV Communications with Phase Errors

“…where φ jk = φ j − φ k . Based on the BER in (6), it can be numerically demonstrated that P E is not strictly decreasing versus L when the values of κ i are not equal for all values of i. Consequently, only a subset of elements should be selected while all others should be switched off.…”