[Paper Review] Transceiver Design for Cooperative Non-Orthogonal Multiple Access Systems with Wireless Energy Transfer

Ruijin Sun, Ying Wang+2 more|arXiv (Cornell University)|Aug 27, 2016

Energy Harvesting in Wireless Networks2 references3 citations

TL;DR

This paper proposes a transceiver design for a cooperative non-orthogonal multiple access (NOMA) system with wireless energy harvesting, where a strong user (R) acts as an energy-harvesting decode-and-forward relay to improve the quality of service (QoS) of a weak user (D). By jointly optimizing beamforming, power splitting ratio, and receiver filtering under QoS and power constraints, the scheme maximizes R's data rate while ensuring D's rate requirement is met, achieving significant outage performance gains over direct transmission, especially with increased relay antennas.

ABSTRACT

In this paper, an energy harvesting (EH) based cooperative non-orthogonal multiple access (NOMA) system is considered, where node S simultaneously sends independent signals to a stronger node R and a weaker node D. We focus on the scenario that the direct link between S and D is too weak to meet the quality of service (QoS) of D. Based on the NOMA principle, node R, the stronger user, has prior knowledge about the information of the weaker user, node D. To satisfy the targeted rate of D, R also serves as an EH decode-and-forward (DF) relay to forward the traffic from S to D. In the sense of equivalent cognitive radio concept, node R viewed as a secondary user assists to boost the performance of D, in exchange for receiving its own information from S. Specifically, transmitter beamforming design, power splitting ratio optimization and receiver filter design to maximize node R rate are studied with the predefined QoS constraint of D and the power constraint of S. Since the problem is non-convex, we propose an iterative approach to solve it. Moreover, to reduce the computational complexity, a zero- forcing (ZF) based solution is also presented. Simulation results demonstrate that, both two proposed schemes have better performance than the direction transmission.

Motivation & Objective

• To address the energy shortage in cooperative NOMA systems where strong users relay signals for weak users, degrading their own performance due to high transmission power.
• To enhance spectral efficiency and user fairness in NOMA by enabling simultaneous information and energy transfer via RF energy harvesting at the relay node R.
• To maximize the data rate of the strong user R while guaranteeing the minimum rate requirement of the weak user D under total power and QoS constraints.
• To develop low-complexity solutions, including a zero-forcing (ZF)-based beamforming scheme, for practical deployment.
• To evaluate system performance through extensive simulations under realistic channel conditions and power constraints.

Proposed method

• Formulates a non-convex optimization problem to jointly design transmitter beamforming vectors, power splitting ratios, and receiver filters to maximize R’s rate under D’s QoS and S’s total power constraints.
• Employs an iterative algorithm to solve the non-convex problem by alternately optimizing beamforming, power splitting, and receiver filter under fixed-point iterations.
• Proposes a zero-forcing (ZF)-based beamforming scheme to reduce computational complexity by forcing interference cancellation between intended signals.
• Uses the equivalent cognitive radio model where R, as a secondary user, relays D’s signal in exchange for receiving its own data from S.
• Applies power domain multiplexing in NOMA with successive interference cancellation (SIC) at R to decode D’s signal before forwarding.
• Models the energy harvesting process with a fixed efficiency (η = 0.8), where R splits the received signal into information decoding and energy harvesting streams.

Experimental results

Research questions

• RQ1 How can beamforming and power splitting be jointly optimized to maximize the relay user’s rate in a cooperative NOMA system with energy harvesting?
• RQ2 What is the performance gain of the proposed scheme over direct transmission in terms of outage probability for the weak user D?
• RQ3 How does increasing the number of antennas at the relay R affect the system performance in terms of D’s outage probability and R’s data rate?
• RQ4 To what extent does the ZF-based beamforming scheme approximate the performance of the optimal iterative solution?
• RQ5 Under what conditions does the ZF scheme achieve near-optimal performance, especially when D’s rate requirement is high?

Key findings

• The proposed optimal iterative scheme achieves significantly lower outage probability for node D compared to direct transmission, especially at higher transmission powers.
• The ZF-based beamforming scheme achieves nearly identical outage performance to the optimal scheme when D’s rate requirement is high, due to near-total power allocation to D’s beamforming vector.
• As the number of antennas at R increases, the outage probability of D decreases significantly, demonstrating the benefit of spatial diversity.
• The rate region of node R expands substantially with increasing transmit power from S, and the performance gap between optimal and ZF schemes diminishes as D’s rate requirement increases.
• The optimal scheme outperforms the ZF scheme in rate region coverage, but the ZF scheme offers a strong trade-off between performance and complexity.
• Simulation results confirm that both proposed schemes (optimal and ZF) significantly outperform direct transmission in terms of reliability and spectral efficiency under the same power and QoS constraints.