Pith. sign in

REVIEW

Cooperative Multi-Beam Routing for Multi-IRS Aided Massive MIMO

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2011.02354 v2 pith:FCWZHXB4 submitted 2020-11-04 cs.IT math.IT

Cooperative Multi-Beam Routing for Multi-IRS Aided Massive MIMO

classification cs.IT math.IT
keywords routingbeamirssproblemactiveaidedalgorithmbeamforming
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
Share X Bluesky LinkedIn Reddit HN
read the original abstract

Intelligent reflecting surface (IRS) is envisioned to play a significant role in future wireless communication systems thanks to its powerful capability of enabling smart and reconfigurable radio environment. In this paper, we study the multi-IRS aided downlink communication in a massive multiple-input multiple-output (MIMO) system, where a multi-antenna BS simultaneously serves multiple remote single-antenna users with orthogonal beams reflected by multiple IRSs. By exploiting the line-of-sight (LoS) link between each pair of selected IRSs, a multi-hop cascaded LoS link can be established between the BS and each user via their cooperative beam routing. Under this setup, we optimize the selected IRSs and their beam routing path for each user, along with the BS/IRS active/passive beamforming such that the minimum received signal power among all users is maximized, subject to a new multi-beam routing path separation constraint for avoiding the inter-user/route interference. To tackle this problem, we first derive the optimal BS/IRS active/passive beamforming in closed-form for any given beam routes and show the beam routing optimization is NP-complete by recasting it as an equivalent graph-optimization problem. To solve this challenging problem, we then propose an efficient recursive algorithm to partially enumerate the feasible solutions, which effectively balances the performance-complexity trade-off by tuning its design parameter. Numerical results demonstrate that the proposed algorithm can achieve near-optimal performance with low enumeration complexity and also outperform other benchmark schemes.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.