Sub-channel Assignment, Power Allocation and User Scheduling for Non-Orthogonal Multiple Access Networks (1608.08313v1)

Abstract: In this paper, we study the resource allocation and user scheduling problem for a downlink nonorthogonal multiple access network where the base station allocates spectrum and power resources to a set of users. We aim to jointly optimize the sub-channel assignment and power allocation to maximize the weighted total sum-rate while taking into account user fairness. We formulate the sub-channel allocation problem as equivalent to a many-to-many two-sided user-subchannel matching game in which the set of users and sub-channels are considered as two sets of players pursuing their own interests. We then propose a matching algorithm which converges to a two-side exchange stable matching after a limited number of iterations. A joint solution is thus provided to solve the sub-channel assignment and power allocation problems iteratively. Simulation results show that the proposed algorithm greatly outperforms the orthogonal multiple access scheme and a previous non-orthogonal multiple access scheme.

• The paper introduces iterative, game-theoretic and optimization-based algorithms to jointly address sub-channel assignment and power allocation in NOMA networks.
• Simulation results reveal that the proposed USMA-1 and USMA-2 algorithms significantly outperform traditional OFDMA and previous NOMA approaches in spectral efficiency and user fairness.
• The methodologies utilize geometric programming and simulated annealing to effectively solve the NP-hard resource allocation problem in downlink wireless communications.

Resource Allocation and User Scheduling for Non-Orthogonal Multiple Access Networks

This paper centers on the challenges and methodologies related to resource allocation and user scheduling within downlink Non-Orthogonal Multiple Access (NOMA) networks. These networks present a significant departure from traditional Orthogonal Multiple Access (OMA) systems by allowing multiple users to share the same sub-channel, thereby enhancing spectral efficiency and connectivity.

The authors tackle the primary issue of optimizing resource allocation, specifically sub-channel assignment and power distribution, to maximize the weighted total sum-rate while maintaining user fairness. The problem is formulated as a combinatorial optimization problem, known to be NP-hard due to its non-convex nature and the involved co-channel interference, arising from the unique sub-channel sharing properties of NOMA.

Methodology

To address this problem, the paper introduces a joint sub-channel and power allocation solution through a decoupled iterative approach:

1. Sub-channel Allocation: This is formulated as a many-to-many two-sided matching game with externalities. The authors propose two novel algorithms: USMA-1 and USMA-2. USMA-1 is designed to achieve a two-sided exchange stable matching through iterative user-subchannel swap operations. USMA-2 aims for global optimality using a simulated annealing method, albeit with a higher complexity due to a larger number of iterations.
2. Power Allocation: Treated as a geometric programming problem, it allows for an optimal solution using interior point methods, given a specific sub-channel allocation setup.

Key Findings

Simulation results demonstrate that the proposed algorithms significantly outperform both the OFDMA scheme and some previously proposed NOMA schemes. Specifically, these methods yield superior spectral efficiency and user fairness, underscoring the potential of NOMA as a robust technique for future wireless communications. The authors note that despite increased complexity, NOMA provides a more favorable balance between spectrum efficiency and user connectivity compared to traditional schemes.

Implications and Future Directions

By addressing the intricate balance between maximizing spectral efficiency and maintaining fairness, this research offers substantial advancements in the deployment of NOMA networks. The proposed methodologies highlight the potential of game-theoretic and optimization-based approaches in solving complex resource allocation problems. Future work may delve into further reducing algorithmic complexity or enhancing robustness in high-mobility scenarios where channel conditions fluctuate more rapidly. Additionally, exploring the integration of NOMA with emerging technologies such as massive MIMO may offer further opportunities for innovation.

In sum, this paper provides a comprehensive assessment of resource allocation strategies in NOMA networks, laying a significant foundation for ongoing and future research in efficient and fair multi-user communication systems.