Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization (1505.01354v1)

Abstract: We propose a data-aided transmit beamforming scheme for the multi-user multiple-input-single-output (MISO) downlink channel. While conventional beamforming schemes aim at the minimization of the transmit power subject to suppressing interference to guarantee quality of service (QoS) constraints, here we use the knowledge of both data and channel state information (CSI) at the transmitter to exploit, rather than suppress, constructive interference. More specifically, we design a new precoding scheme for the MISO downlink that minimizes the transmit power for generic phase shift keying (PSK) modulated signals. The proposed precoder reduces the transmit power compared to conventional schemes, by adapting the QoS constraints to accommodate constructive interference as a source of useful signal power. By exploiting the power of constructively interfering symbols, the proposed scheme achieves the required QoS at lower transmit power. We extend this concept to the signal to interference plus noise ratio (SINR) balancing problem, where higher SINR values compared to the conventional SINR balancing optimization are achieved for given transmit power budgets. In addition, we derive equivalent virtual multicast formulations for both optimizations, both of which provide insights of the optimal solution and facilitate the design of a more efficient solver. Finally, we propose a robust beamforming technique to deal with imperfect CSI, that also reduces the transmit power over conventional techniques, while guaranteeing the required QoS. Our simulation and analysis show significant power savings for small scale MISO downlink channels with the proposed data-aided optimization compared to conventional beamforming optimization.

• The paper presents an innovative precoding scheme that uses constructive interference to lower power requirements while meeting QoS in multi-user MISO downlink systems.
• The methodology leverages both transmitted data and channel state information to achieve higher SINR and enhanced energy efficiency compared to traditional beamforming approaches.
• Numerical results confirm robust performance, even under imperfect CSI and in scenarios with fewer transmit antennas than users.

Overview of Downlink Beamforming Optimization via Constructive Interference

The paper introduces an innovative approach to downlink beamforming optimization in multi-user multiple-input-single-output (MISO) systems, utilizing the concept of constructive interference. This paper proposes a data-aided transmit beamforming scheme that deviates from traditional methods which primarily focus on interference suppression to meet quality of service (QoS) constraints. Instead, the researchers leverage the knowledge of both the transmitted data and channel state information (CSI) to exploit interference constructively.

Proposed Methodology

The central contribution of this paper lies in developing a novel precoding scheme for MISO downlink communication systems with phase-shift keying (PSK) modulated signals. This new approach reduces the requisite transmit power compared to conventional beamforming schemes by allowing constructive interference to serve as an additional source of useful signal power. The method adapts QoS constraints accordingly, resulting in lower power requirements to meet the desired QoS.

Further, this concept is extended to the signal-to-interference-plus-noise ratio (SINR) balancing problem. For a given transmit power budget, the proposed optimization achieves higher SINR values compared to traditional SINR balancing techniques. Additionally, the authors provide a robust beamforming methodology that accounts for imperfect CSI, continuing to offer power savings, especially in small-scale MISO downlink channels.

Numerical Results and Implications

The paper presents strong numerical results demonstrating that the proposed optimization solutions significantly reduce the transmit power needed to meet performance criteria in both power minimization and SINR balancing scenarios. Notably, even in scenarios where the system has fewer transmit antennas than users (N < K), the proposed precoding solution remains viable in a significant fraction of situations, highlighting its practical utility and robustness against user scaling.

These results suggest that by incorporating constructive interference into beamforming strategies, current power consumption challenges in wireless communication systems can be mitigated. This is particularly relevant given the current emphasis on green communications and energy-efficient system designs.

Theoretical Contributions and Future Directions

From a theoretical standpoint, this research offers a new perspective on handling interference, revisiting it as a beneficial factor under certain conditions rather than a disruptive one. This requires a paradigm shift in the traditional design of communication systems. The paper also deconstructs the optimization problem into a virtual multicasting formulation, facilitating more efficient gradient projection algorithms to solve the beamforming challenges.

Future developments could involve extending these methodologies to support different modulation formats such as quadrature amplitude modulation (QAM) and adapting the proposed techniques to broader multi-cell and cooperative network scenarios. Moreover, the robust optimization framework promises avenues for further exploration into handling various forms of channel estimation errors, ensuring broader applicability and reliability.

In summary, by exploiting constructive interference, this paper paves the way toward more efficient and power-conscious communication systems. As the field progresses, these techniques could integrate into evolving standards, positioning interference as a viable asset rather than a liability.