Beamforming for MISO Interference Channels with QoS and RF Energy Transfer (1311.7237v1)

Abstract: We consider a multiuser multiple-input single-output interference channel where the receivers are characterized by both quality-of-service (QoS) and radio-frequency (RF) energy harvesting (EH) constraints. We consider the power splitting RF-EH technique where each receiver divides the received signal into two parts a) for information decoding and b) for battery charging. The minimum required power that supports both the QoS and the RF-EH constraints is formulated as an optimization problem that incorporates the transmitted power and the beamforming design at each transmitter as well as the power splitting ratio at each receiver. We consider both the cases of fixed beamforming and when the beamforming design is incorporated into the optimization problem. For fixed beamforming we study three standard beamforming schemes, the zero-forcing (ZF), the regularized zero-forcing (RZF) and the maximum ratio transmission (MRT); a hybrid scheme, MRT-ZF, comprised of a linear combination of MRT and ZF beamforming is also examined. The optimal solution for ZF beamforming is derived in closed-form, while optimization algorithms based on second-order cone programming are developed for MRT, RZF and MRT-ZF beamforming to solve the problem. In addition, the joint-optimization of beamforming and power allocation is studied using semidefinite programming (SDP) with the aid of rank relaxation.

• The paper optimizes beamforming to minimize transmission power in MISO interference channels with simultaneous QoS and RF energy harvesting constraints.
• Fixed beamforming schemes and an adaptive SDP approach are proposed, comparing efficiency, feasibility, and optimal performance.
• The findings illuminate interference handling trade-offs and motivate adaptive energy-efficient strategies for wireless networks with RF energy harvesting.

Beamforming for MISO Interference Channels with QoS and RF Energy Transfer

This paper addresses an optimization problem within a Multiple-Input Single-Output (MISO) interference channel framework, where the receivers must simultaneously meet Quality of Service (QoS) and Radio-Frequency Energy Harvesting (RF-EH) constraints. The innovative aspect of this paper lies in its approach to minimizing the transmission power while considering these dual constraints using a power-splitting technique. Receivers divide the received energy for information decoding and battery charging, demanding sophisticated optimization of power resources and beamforming strategies.

The authors propose both fixed and adaptive beamforming strategies. For scenarios employing fixed beamforming, they evaluate traditional schemes: Zero-Forcing (ZF), Regularized Zero-Forcing (RZF), and Maximum Ratio Transmission (MRT). They introduce a hybrid MRT-ZF approach to leverage the strengths of both MRT and ZF. Their findings stress that ZF beamforming requires more power to meet constraints compared to MRT, but guarantees feasible solutions when the number of antennas per transmitter meets or exceeds the number of receivers.

The theoretical analysis reveals a closed-form solution for ZF beamforming, while for MRT, RZF, and MRT-ZF, second-order cone programming (SOCP) based algorithms offer optimal solutions. In the context of systems with heavy interference, the MRT-ZF beamforming stands out for providing feasible and quality solutions over standard methods at reasonable computational complexity.

The paper ventures into optimal adaptive solutions via a semidefinite programming (SDP) approach, employing rank relaxation. The SDP solution notably yields rank-1 solutions for the two and three-user scenarios, suggesting exact optimal beamforming solutions. The SDP delivers superior quality solutions and sets a benchmark, though at the cost of increased computational overhead.

Numerical evaluations demonstrate significant variations in required transmission power against alterations in system parameters like SINR thresholds and RF-EH constraints. Notably, the MRT-ZF scheme ensures feasible power-efficient solutions, dominating in instances where the optimal benchmark approach is computationally prohibitive.

The implications of this research are multi-fold. Practically, it motivates adaptive energy-efficient transmission strategies pivotal for modern wireless communication systems integrating EH capabilities. Theoretically, the results highlight the nuanced trade-offs in handling interference— critically setting a stepping stone for future research in optimizing RF-EH based systems. The paper also hints at future explorations into distributed algorithmic solutions and practical implementations in systems with limited channel state information.

This paper positions itself as an important reference for advancing simultaneous wireless information and power transfer technologies, facilitating sustainable operations in next-generation wireless networks. Researchers and practitioners can employ the proposed schemes to optimize transmit power more finitely, catering to an evolving landscape where energy constraints are increasingly prioritized.