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IRS-Aided Multi-Antenna Wireless Powered Communications in Interference Channels

Ying Gao, Qingqing Wu, Wen Chen

TL;DR

This work addresses maximizing the system sum throughput in an IRS-aided multi-antenna wireless powered IFC with multiple HAP-WD pairs and IRSs. It introduces three transmission schemes—IRS-aided asynchronous (Asy), TDMA, and synchronous (Syn)—and develops a general alternating-optimization framework to solve the non-convex resource allocation problems by efficiently updating DL beamforming $oldsymbol{w}_{i,j}$, UL resources $oldsymbol{ au},oldsymbol{S}_{i,j},p_{k,j}$, and IRS phase shifts $oldsymbol{v}_j$ using SCA, SDP, and QCP techniques. The framework guarantees convergence to a stationary point while offering detailed complexity characterizations, and numerical results show that IRSs improve both sum throughput and energy efficiency, with Asy providing the highest throughput and Syn/TDMA favored under specific interference and resource conditions. The findings offer practical guidance on scheme selection in IRS-aided WPCNs and suggest future work on imperfect CSI, multi-antenna WDs, and NOMA comparisons.

Abstract

This paper investigates intelligent reflecting surface (IRS)-aided multi-antenna wireless powered communications in a multi-link interference channel, where multiple IRSs are deployed to enhance the downlink/uplink communications between each pair of hybrid access point (HAP) and wireless device. Our objective is to maximize the system sum throughput by optimizing the allocation of communication resources. To attain this objective and meanwhile balance the performance-cost tradeoff, we propose three transmission schemes: the IRS-aided asynchronous (Asy) scheme, the IRS-aided time-division multiple access (TDMA) scheme, and the IRS-aided synchronous (Syn) scheme. For the resulting three non-convex design problems, we propose a general algorithmic framework capable of suboptimally addressing all of them. Numerical results show that our proposed IRS-aided schemes noticeably surpass their counterparts without IRSs in both system sum throughput and total transmission energy consumption at the HAPs. Moreover, although the IRS-aided Asy scheme consistently achieves the highest sum throughput, the IRS-aided TDMA scheme is more appealing in scenarios with substantial cross-link interference and limited IRS elements, while the IRS-aided Syn scheme is preferable in low cross-link interference scenarios.

IRS-Aided Multi-Antenna Wireless Powered Communications in Interference Channels

TL;DR

This work addresses maximizing the system sum throughput in an IRS-aided multi-antenna wireless powered IFC with multiple HAP-WD pairs and IRSs. It introduces three transmission schemes—IRS-aided asynchronous (Asy), TDMA, and synchronous (Syn)—and develops a general alternating-optimization framework to solve the non-convex resource allocation problems by efficiently updating DL beamforming , UL resources , and IRS phase shifts using SCA, SDP, and QCP techniques. The framework guarantees convergence to a stationary point while offering detailed complexity characterizations, and numerical results show that IRSs improve both sum throughput and energy efficiency, with Asy providing the highest throughput and Syn/TDMA favored under specific interference and resource conditions. The findings offer practical guidance on scheme selection in IRS-aided WPCNs and suggest future work on imperfect CSI, multi-antenna WDs, and NOMA comparisons.

Abstract

This paper investigates intelligent reflecting surface (IRS)-aided multi-antenna wireless powered communications in a multi-link interference channel, where multiple IRSs are deployed to enhance the downlink/uplink communications between each pair of hybrid access point (HAP) and wireless device. Our objective is to maximize the system sum throughput by optimizing the allocation of communication resources. To attain this objective and meanwhile balance the performance-cost tradeoff, we propose three transmission schemes: the IRS-aided asynchronous (Asy) scheme, the IRS-aided time-division multiple access (TDMA) scheme, and the IRS-aided synchronous (Syn) scheme. For the resulting three non-convex design problems, we propose a general algorithmic framework capable of suboptimally addressing all of them. Numerical results show that our proposed IRS-aided schemes noticeably surpass their counterparts without IRSs in both system sum throughput and total transmission energy consumption at the HAPs. Moreover, although the IRS-aided Asy scheme consistently achieves the highest sum throughput, the IRS-aided TDMA scheme is more appealing in scenarios with substantial cross-link interference and limited IRS elements, while the IRS-aided Syn scheme is preferable in low cross-link interference scenarios.
Paper Structure (18 sections, 9 equations, 4 figures, 1 table)

This paper contains 18 sections, 9 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. IRS-Aided Asy Scheme
  5. IRS-Aided TDMA Scheme
  6. IRS-Aided Syn Scheme
  7. Problem Formulation
  8. Proposed General Algorithmic Framework for (P1)-(P3)
  9. How To Solve (P1)?
  10. Optimizing $\{\mathbf w_{i,j}\}$
  11. Optimizing $\left\lbrace \{\delta_j\}, \{\mathbf S_{i,j}\}, \{p_{k,j}\}\right\rbrace$
  12. Optimizing $\{\mathbf v_j\}$
  13. Optimizing $\mathbf v_1$
  14. Optimizing $\hat{\mathbf v}$
  15. Convergence and Complexity Analysis
  16. ...and 3 more sections

Figures (4)

  • Figure 1: Illustration of three different transmission schemes: (a) IRS-aided Asy scheme; (b) IRS-aided TDMA scheme; (c) IRS-aided Syn scheme.
  • Figure 2: Simulation setup. HAP $k$ and WD $k$ are positioned in polar coordinates $\left(d_{\rm HAP},\frac{2\pi(k-1)}{K}, \frac{\pi}{2}\right)$ and $\left(d_{\rm WD},\frac{2\pi(k-1)}{K}, \frac{\pi}{2}\right)$ in meters (m), respectively. Each IRS is positioned $d_{\rm h}$ m directly above the y-axis (x-axis), with a vertical distance of $d_{\rm I}$ m from the z-axis.
  • Figure 3: (a) Average sum throughput versus $d_{\rm HAP}$; (b) Average total energy consumption at the HAPs versus $d_{\rm }$; (c) Average sum throughput versus $N$.
  • Figure 4: Average sum throughput versus $d_{\rm I}$.