[Paper Review] Rate-Splitting Multiple Access for Multi-antenna Downlink Communication Systems: Spectral and Energy Efficiency Tradeoff

Gui Zhou, Yijie Mao+1 more|arXiv (Cornell University)|Jan 9, 2020

Advanced Wireless Communication Technologies4 citations

TL;DR

This paper proposes a joint spectral efficiency (SE) and energy efficiency (EE) optimization framework for rate-splitting multiple access (RSMA) in multi-antenna downlink systems with rate-dependent circuit power. By transforming the multi-objective problem into single-objective subproblems via weighted-sum and weighted-power methods, and employing a low-complexity algorithm for two-user systems and a successive convex approximation (SCA)-based method for K-user systems, the approach achieves faster convergence and superior SE-EE tradeoff performance compared to SDMA and NOMA.

ABSTRACT

Rate-splitting (RS) has recently been recognized as a promising physical-layer technique for multi-antenna broadcast channels (BC). Due to its ability to partially decode the interference and partially treat the remaining interference as noise, RS is an enabler for a powerful multiple access, namely rate-splitting multiple access (RSMA), that has been shown to achieve higher spectral efficiency (SE) and energy efficiency (EE) than both space division multiple access (SDMA) and non-orthogonal multiple access (NOMA) in a wide range of user deployments and network loads. As SE maximization and EE maximization are two conflicting objectives, the study of the tradeoff between the two criteria is of particular interest. In this work, we address the SE-EE tradeoff by studying the joint SE and EE maximization problem of RSMA in multiple input single output (MISO) BC with rate-dependent circuit power consumption at the transmitter. To tackle the challenges coming from multiple objective functions and rate-dependent circuit power consumption, we first propose two methods to transform the original problem into a single-objective problem, namely, weighted-sum method and weighted-power method. A successive convex approximation (SCA)-based algorithm is then proposed to jointly optimize the precoders and RS message split of the transformed problem. Numerical results show that our algorithm converges much faster than existing algorithms. In addition, the performance of RS is superior to or equal to non-RS strategy in terms of both SE and EE and their tradeoff.

Motivation & Objective

• Address the fundamental tradeoff between spectral efficiency (SE) and energy efficiency (EE) in multi-antenna downlink systems under practical rate-dependent circuit power constraints.
• Overcome the challenges of multi-objective optimization and non-convexity arising from rate-dependent circuit power in RSMA precoder design.
• Develop efficient algorithms that jointly maximize SE and EE without requiring feasibility checks for predefined SE constraints.
• Demonstrate the superiority of RSMA over conventional SDMA and NOMA in both SE and EE performance and their tradeoff.

Proposed method

• Transform the multi-objective SE-EE optimization problem into two single-objective subproblems using the weighted-sum method and the weighted-power method.
• Propose a low-complexity closed-form algorithm for the two-user MISO BC case by solving the transformed single-objective problems.
• Extend the solution to K-user systems using a successive convex approximation (SCA)-based algorithm to handle non-convex precoder optimization.
• Model the transmitter's circuit power as a rate-dependent function to reflect real-world hardware constraints.
• Utilize the Karush-Kuhn-Tucker (KKT) conditions and partial first-order approximations to derive optimality conditions for the SCA framework.
• Apply inner approximation techniques to iteratively refine the solution, ensuring convergence to a stationary point of the original problem.

Experimental results

Research questions

• RQ1 How can the conflicting objectives of SE and EE be jointly optimized in a multi-antenna downlink system with rate-dependent circuit power?
• RQ2 What is the performance gain of RSMA over SDMA and NOMA in terms of SE and EE tradeoff under practical hardware constraints?
• RQ3 Can a low-complexity algorithm with closed-form solution be derived for the two-user RSMA system with joint SE-EE optimization?
• RQ4 How does the SCA-based algorithm for K-user systems compare in convergence speed and performance to existing methods?
• RQ5 What is the impact of rate-dependent circuit power on the SE-EE tradeoff and the resulting precoder design?

Key findings

• The proposed SCA-based algorithm converges significantly faster than existing algorithms, demonstrating improved computational efficiency.
• RSMA achieves higher spectral and energy efficiency than both SDMA and NOMA across a wide range of user deployments and network loads.
• The joint SE-EE optimization via the weighted-sum and weighted-power methods successfully avoids feasibility issues associated with fixed SE constraints.
• For the two-user case, the proposed low-complexity algorithm achieves a closed-form solution, enabling real-time implementation.
• The K-user SCA-based algorithm converges to a stationary point of the original non-convex problem, ensuring reliable performance.
• Numerical results confirm that RSMA provides a superior SE-EE tradeoff, with performance consistently outperforming or matching SDMA and NOMA across all SNR regimes.