Energy Efficient Multi-User MISO Communication using Low Resolution Large Intelligent Surfaces (1809.05397v1)

Abstract: We consider a multi-user Multiple-Input Single-Output (MISO) communication system comprising of a multi-antenna base station communicating in the downlink simultaneously with multiple single-antenna mobile users. This communication is assumed to be assisted by a Large Intelligent Surface (LIS) that consists of many nearly passive antenna elements, whose parameters can be tuned according to desired objectives. The latest design advances on these surfaces suggest cheap elements effectively acting as low resolution (even $1$-bit resolution) phase shifters, whose joint configuration affects the electromagnetic behavior of the wireless propagation channel. In this paper, we investigate the suitability of LIS for green communications in terms of Energy Efficiency (EE), which is expressed as the number of bits per Joule. In particular, for the considered multi-user MISO system, we design the transmit powers per user and the values for the surface elements that jointly maximize the system's EE performance. Our representative simulation results show that LIS-assisted communication, even with nearly passive $1$-bit resolution antenna elements, provides significant EE gains compared to conventional relay-assisted communication.

• The paper demonstrates that low-resolution intelligent surfaces significantly enhance energy efficiency in multi-user MISO communications through optimized transmit power and phase shifts.
• It introduces an alternating optimization algorithm that jointly adjusts transmit power and low-resolution phase configurations to maximize bits per Joule.
• Numerical results reveal over 40% energy efficiency improvement compared to conventional relay models, supporting the viability of low-resolution LIS in future networks.

Energy Efficient Multi-User MISO Communication Using Low Resolution Large Intelligent Surfaces

The paper "Energy Efficient Multi-User MISO Communication using Low Resolution Large Intelligent Surfaces" investigates the deployment of Large Intelligent Surfaces (LIS) in multi-user Multiple-Input Single-Output (MISO) communication systems, with an emphasis on energy efficiency (EE). The system under consideration comprises a multi-antenna base station (BS) communicating with multiple single-antenna mobile users, augmented by a LIS featuring numerous nearly passive antenna elements with low-resolution phase shifters. The core objective is to evaluate the potential of the LIS technology in enhancing EE, particularly when these elements demonstrate low phase resolution capabilities.

Summary of Findings

1. System Model and Challenges: The paper develops a mathematical framework to model a multi-user MISO system supported by LIS. This system involves complex interplay between the direct and reflected signals, managed through adjustable low-resolution phase shifters. The LIS technology proposes an alternative to conventional relay-assisted communication, aiming for improved EE in dense next-generation networks.
2. Design and Optimization: The design task involves customizing the transmit powers at the BS and configuring the LIS elements to optimize EE, defined as bits per Joule. The paper proposes a system model alongside a power consumption framework accounting for various factors, including hardware power and phase shifter functionality. Recognizing the challenge posed by the nonlinear and non-convex nature of the problem, the authors deploy an alternating optimization approach to iteratively solve for optimal power allocation and LIS configuration.
3. Algorithmic Approach: An innovative algorithm is devised to tackle the transmit power and phase value optimization. For 1-bit phase resolution LIS cases, an exhaustive search comparison is conducted, affirming the algorithm's efficacy. The overall complexity is reduced to be more feasible for implementation in large-scale deployments.
4. Numerical Results: Simulation results demonstrate significant EE gains achievable by integrating LIS with low phase resolutions, especially when considering 1-bit and 2-bit elements. Interestingly, even with low resolution, the LIS-based approach is shown to surpass traditional relay communication models in terms of EE, suggesting a credible alternative for EE enhancement in future networks. The optimal number of LIS elements is also identified as a key parameter for maximizing EE, highlighting the balance between surface complexity and performance benefit.
5. Comparative Analysis: The paper provides a comparative analysis with conventional relay-based communication systems, showcasing more than a 40% increase in EE with the proposed LIS model under certain conditions. This suggests that LIS technology could offer a more sustainable solution as the demand for efficient communication systems continues to rise.

Implications and Future Directions

The insights offered by this paper suggest that utilizing LIS technology in MISO systems with low-resolution elements can be a viable and effective approach to enhance EE within future communication networks. Theoretically, LIS could represent a transformative step toward sustainable mobile communications by drastically reducing energy utilization while maintaining high data rates.

For future work, more extensive experimentation with varying phase resolutions and surface sizes will be necessary to refine the LIS configuration for different deployment scenarios. Additionally, further exploration into the real-world feasibility concerning the practical constraints of implementing large intelligent surfaces, such as electromagnetic wave behavior and system integration, could provide a fuller picture of its potential impact on EE advancements in wireless communications.