[Paper Review] Optimizing Non-Orthogonal Multiple Access in Random Access Networks

Ziru Chen, Yong Liu+4 more|arXiv (Cornell University)|Feb 14, 2020

Advanced Wireless Communication Technologies13 references4 citations

TL;DR

This paper proposes an optimized p-persistent slotted ALOHA protocol with non-orthogonal multiple access (NOMA) to maximize network throughput in random access networks. By modeling transmission probabilities for high- and low-power users and applying successive interference cancellation (SIC), the authors derive analytical conditions for successful NOMA decoding and propose an iterative algorithm to jointly optimize high/low power transmission probabilities, achieving significant throughput gains over conventional ALOHA.

ABSTRACT

Non-orthogonal multiple access (NOMA) has been considered as a promising solution for improving the spectrum efficiency of next-generation wireless networks. In this paper, the performance of a p-persistent slotted ALOHA system in support of NOMA transmissions is investigated. Specifically, wireless users can choose to use high or low power for data transmissions with certain probabilities. To achieve the maximum network throughput, an analytical framework is developed to analyze the successful transmission probability of NOMA and long term average throughput of users involved in the non-orthogonal transmissions. The feasible region of the maximum number of concurrent users using high and low power to ensure successful NOMA transmissions are quantified. Based on the analysis, an algorithm is proposed to find the optimal transmission probabilities for users to choose high and low power to achieve the maximum system throughput. In addition, the impact of power settings on the network performance is further investigated. Simulations are conducted to validate the analysis.

Motivation & Objective

• To address the challenge of maximizing spectral efficiency in machine-type communications (MTC) with random access and limited channel state information.
• To analyze the feasibility of NOMA in p-persistent slotted ALOHA systems where users randomly access the channel with variable power levels.
• To derive the feasible region for concurrent high- and low-power users to ensure successful NOMA decoding via SIC.
• To develop an optimization algorithm that jointly determines the optimal transmission probabilities for high- and low-power modes to maximize long-term average system throughput.

Proposed method

• Develops a mathematical model to compute the successful transmission probability of NOMA users based on user distribution, path loss, fading, and power allocation.
• Derives analytical expressions for the long-term average throughput, incorporating user-specific data rates determined by SINR and SIC performance.
• Identifies sufficient and necessary conditions for successful NOMA transmission by quantifying the feasible region of high- and low-power user counts.
• Proposes an iterative algorithm that alternately optimizes the transmission probabilities for high- and low-power users to maximize system throughput.
• Uses a power control strategy where users select high power (v₁) or low power (v₂) with probabilities τ₁ and τ₂, respectively, to balance interference and reliability.
• Validates the analytical model through Monte Carlo simulations using MATLAB, comparing NOMA-enabled ALOHA with conventional ALOHA.

Experimental results

Research questions

• RQ1 What is the feasible region of high- and low-power users that ensures successful NOMA decoding under SIC in a p-persistent slotted ALOHA system?
• RQ2 How do transmission probabilities τ₁ and τ₂ for high- and low-power modes affect the long-term average system throughput?
• RQ3 What is the optimal joint configuration of τ₁ and τ₂ that maximizes system throughput under varying user counts and power levels?
• RQ4 How does the choice of power levels (v₁, v₂) and SINR threshold impact the performance of NOMA in random access networks?
• RQ5 To what extent does NOMA improve throughput compared to conventional p-persistent ALOHA without NOMA?

Key findings

• The optimal transmission probabilities τ₁ and τ₂ for high- and low-power users are not equal; τ₁ > τ₂ is required to maximize throughput, as higher power improves decoding reliability and multiplexing gain.
• The maximum network throughput is achieved at a specific user count m, with throughput peaking and then decreasing due to increased contention, and the peak shifts right for lower transmission probabilities.
• The proposed algorithm converges to the optimal solution in approximately 10 iterations, with negligible throughput improvement beyond that point.
• Simulations confirm that NOMA-enabled ALOHA achieves significantly higher throughput than conventional ALOHA, especially at moderate user densities.
• The feasible region for successful NOMA transmission is bounded: for n₁=2 high-power users and n₂=5 low-power users, both can be decoded; increasing n₂ beyond 10 causes low-power users to fail due to excessive interference.
• Throughput gains from NOMA are most pronounced when users are distributed across a range of distances and power levels are carefully controlled to balance interference and rate.