Non-Orthogonal Multiple Access (NOMA) and Fog Radio Access Networks (FRAN) are promising candidates within the 5G and beyond systems. This work examines the benefit of adopting NOMA in an FRAN architecture with constrained capacity fronthaul. The paper proposes methods for optimizing joint scheduling and power adaptation in the downlink of a NOMA-based FRAN with multiple resource blocks (RB). We consider a mixed-integer optimization problem which maximizes a network-wide rate-based utility function subject to fronthaul-capacity constraints, so as to determine i) the user-to-RB assignment, ii) the allocated power to each RB, and iii) the power split levels of the NOMA users in each RB. The paper proposes a feasible decoupled solution for such non-convex optimization problem using a three-step hybrid centralized distributed approach. The proposed solution complies with FRAN operation that aims to partially shift the network control to the FAPs, so as to overcome delays due to fronthaul rate constraints. The paper proposes and compares two distinct methods for solving the assignment problem, namely the Hungarian method, and the Multiple Choice Knapsack method. The power allocation and the NOMA power split optimization, on the other hand, are solved using the alternating direction method of multipliers (ADMM). Simulations results illustrate the advantages of the proposed methods compared to different baseline schemes including the conventional Orthogonal Multiple Access (OMA), for different utility functions and different network environments.
The integration of NOMA in a CRAN architecture is analyzed in few recent works, e.g., @cite_9 @cite_18 @cite_31 @cite_26 @cite_23 @cite_6 @cite_3 @cite_14 . References @cite_9 and @cite_18 analyze the outage probability in a NOMA-based CRAN network. In particular, reference @cite_18 proposes an architecture, where the cell-center users are served by their nearest RRHs as their strong users, while multiple RRHs collaborate to serve the cell-edge users as their weak users. Using stochastic geometric tools, it is shown in @cite_18 that NOMA enhances the performance of the cell-edge users. References @cite_31 and @cite_26 analyze the energy efficiency of the DL of a CRAN cellular network. In @cite_31 , NOMA is adopted in the wireless backhaul links connecting the BSs to the cloud, while in @cite_26 , it is adopted in the communication between RRHs and users. Both papers show that the NOMA scheme can achieve higher energy efficiency compared to the conventional OMA.
@cite_18 @cite_26 @cite_14 @cite_9 @cite_6 @cite_3 @cite_23 @cite_31
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In this paper, a novel non-orthogonal multiple access (NOMA)-enabled framework for cloud-radio access networks (CRANs) is proposed. In this framework, two users are scheduled in the same resources according to NOMA; however the performance of cell-edge users is enhanced by means of coordinating beamforming. Stochastic geometry is invoked for modeling the proposed framework, where the positions of BSs follow a cluster point process. In an effort to characterize the performance of the proposed framework, simple expressions in terms of outage probability are derived for both nearby users and the cell-edge users. It is analytically demonstrated that the average beamforming gain is a liner function with respect to the number of cooperating base stations. Numerical results verify the accuracy of analysis and reveal that the proposed framework is capable of greatly enhancing the performance of cell-edge users. This paper studies the application of non-orthogonal multiple access (NOMA) to cache-enabled cloud radio access network (CRAN) with mixed multicast and unicast transmission. Users requesting the same content are grouped together and served with a cluster of remote radio heads (RRHs) using distributed beamforming. In addition, the user with better channel condition in each group is allowed to request an extra unicast content via the NOMA protocol. Each RRH has a local cache which enables it to acquire the requested contents either from the local cache or from the central processor via the fronthaul link. Taking the maximum fronthaul capacity into consideration, we investigate the subchannel (SC) allocation problem to both RRHs and multicast groups to improve the weighted network sum rate. The optimal solution requires exhaustive search, which become prohibitively complicated as the number of RRHs and groups increases. To tackle this problem effectively, we formulate this problem as a three-sided matching problem among SCs, RRHs and multicast groups, and propose a novel low-complexity matching algorithm. We prove mathematically that the proposed algorithm converges to a stable matching within limited number of iterations. Numerical results unveil that the proposed algorithm closely approaches the optimal solution and outperforms the conventional orthogonal multiple access (OMA)-based CRAN. This paper investigates multiple access techniques for wireless downlink in cloud radio access networks (CRANs) where all base stations (BSs) are connected via a cloud. We first propose a power allocation scheme that makes use of non-orthogonal multiple access to allocate the power at the BSs based on their relative wireless distances to the cloud. Specifically, a successive interference cancellation mechanism is designed at the cloud to lay multiple BSs over each other in the power domain. We then analyse the achievable throughput of the NOMA in the CRANs. The derived expressions not only show the effectiveness of the proposed NOMA over the conventional orthogonal frequency division multiple access (OFDMA) but also allow us to develop an algorithm to find the optimal number of BSs in the CRANs. Finally, numerical results are provided to show an improvement of up to eight times of the sum data rate and a higher number of BSs that could be maintained with the proposed NOMA over the OFDMA scheme as well as evaluating the impact of the wireless propagation environment and channel quality on the system throughput and cloud-edge throughput performance. A key problem in the design of cloud radio access networks (CRANs) is that of devising effective baseband compression strategies for transmission on the fronthaul links connecting a remote radio head (RRH) to the managing central unit (CU). Most theoretical works on the subject implicitly assume that the RRHs, and hence the CU, are able to perfectly recover time synchronization from the baseband signals received in the uplink, and focus on the compression of the data fields. This paper instead dose not assume a priori synchronization of RRHs and CU, and considers the problem of fronthaul compression design at the RRHs with the aim of enhancing the performance of time and phase synchronization at the CU. The problem is tackled by analyzing the impact of the synchronization error on the performance of the link and by adopting information and estimationtheoretic performance metrics such as the rate-distortion function and the Cramer-Rao bound (CRB). The proposed algorithm is based on the Charnes-Cooper transformation and on the Difference of Convex (DC) approach, and is shown via numerical results to outperform conventional solutions.