Abstract
Cloud-radio access networks (C-RANs) are regarded as a promising solution to provide low cost services among users through the centralized coordination of baseband units for 5G wireless networks. The coordinated multi-point access, visualization and cloud computing technologies enable C-RANs to provide higher capacity and wider coverage, as well as manage the interference and mobility in a centralized coordinated way. However, C-RANs face many challenges due to massive connectivity and spectrum scarcity. If not properly handled, these challenges may degrade the overall performance. Recently, the non-orthogonal multiple access (NOMA) scheme has been suggested as an attractive solution to support multi-user resource sharing in order to improve the spectrum and energy efficiency in 5G wireless networks. In this paper, among various NOMA schemes, we consider and implement the sparse code multiple access (SCMA) scheme to jointly optimize the codebook (CB) and power allocation in the downlink of C-RANs, where the utilization of SCMA in C-RANs to improve the energy efficiency has not been investigated in detail in the literature. To solve this NP-hard joint optimization problem, we decompose the original problem into two sub-problems: codebook allocation and power allocation. Using the conflict graph, we propose the throughput aware SCMA CB selection (TASCBS) method, which generates a stable codebook allocation solution within a finite number of steps. For the power allocation solution, we propose the iterative level-based power allocation (ILPA) method, which incorporates different power allocation approaches (e.g., weighted and NOMA successive interference cancellation (SIC)) into different levels to satisfy the maximum power requirement. Simulation results show that the sum data rate and energy efficiency performances of SCMA supported C-RANs depend on the selected power allocation approach. In terms of energy efficiency, the performance significantly improves with the number of users when the NOMA-SIC aware geometric water-filling based power allocation method is used.
Highlights
The ever increasing number of mobile users, smart devices and applications increases the device density and mobile traffic loads, and eventually makes the traditional cellular networks incapable of handling such high demand
In PD-non-orthogonal multiple access (NOMA), the users are grouped according to their locations and at most two users are share the same SC, which is helpful to reduce the error propagation of successive interference cancelation (SIC) [31], [20]
To solve the optimization problem, we proposed the throughput aware sparse code multiple access (SCMA) codebook selection and iterative level-based power allocation methods
Summary
The ever increasing number of mobile users, smart devices and applications increases the device density and mobile traffic loads, and eventually makes the traditional cellular networks incapable of handling such high demand. Two-tier heterogeneous network (HetNet) with downlink power allocation is studied in [20], where the users receive the data from multiple access points using the CoMP NOMA method. Different from the above works, in this paper, we investigate the energy efficiency aspects of the SCMA method in C-RANs in terms of codebook and power allocation. In the resource allocation problem, the C-RAN small cell base station power budget, the fronthaul capacity constraint and the quality of service (QoS) requirement of each user, are considered. B. CONTRIBUTIONS In this work, we apply the conflict graph theory and geometric water filling approach to solve the codebook and power allocation in SCMA supported C-RANs with the objective to maximize the energy efficiency.
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