EE Optimization for Downlink NOMA-Based Multi-Tier CRANs

Abstract

Non-orthogonal multiple access (NOMA) is increasingly becoming very attractive in cloud radio access networks (CRANs) to further boost the overall spectral efficiency, connectivity and, capacity of such networks. This paper addresses optimizing the energy efficiency (EE) for the downlink of a NOMAbased two tiers CRAN. The stochastic geometry represented by Poisson Point Process (PPP) distribution is used to decide the number and locations of the base stations (BSs) in each tier within the coverage area. A numerical optimal solution is obtained and compared against a proposed subgradient solution, as well as another proposed unoptimized solution based on the false positioning method. For comparison purposes, two other power allocation techniques are presented to allocate different powers to various BS categories; one allocates the power to each BS based on their relative distances to the cloud-based central station and the other is the bisection based scheme. Two simulation scenarios are presented to examine the performance of the two-tier NOMA-CRANs with NOMA is adopted as the multiple access of each tier in both cases. The first scenario considers heterogeneous CRAN (NOMA-HCRAN) case by using two different BS categories in each tier, namely, the macro-BSs and the RRHs. The second scenario considers a homogeneous CRAN (NOMA-CRAN) case by using the RRHs in both tiers but each tier has different frequency layer to prevent cross tier interference. Simulation results show the promising performance gain can be achieved with the proposed techniques relative to the existing approaches. More specifically, it was illustrated that the proposed subgradient based NOMA CRAN offers better performance than the proposed false positioning based NOMA CRAN, which is in turn better than the existing techniques, in particular, the bisection and the distance based NOMA-CRAN.Index Terms-Non-orthogonal multiple access (NOMA), cloud radio access network (CRAN), false positioning method, resource allocation, energy efficiency.

An efficient hybrid energy harvesting protocol for cooperative NOMA systems: Error and outage performance

“…At S, the messages of users are combined in an SC information signal with different power levels according to the users' channel gain 2 and the R receives this information signal in the first phase. Thus, the received information signal by the R node is given as…”

“…Non-orthogonal multiple access (NOMA) is widely renowned for increasing the number of users and improving spectral efficiency in next-generation wireless networks [1][2][3]. Besides, NOMA can be easily integrated with other physical layer schemes.…”

Multiple-Intelligent Reflective Surfaces (Multi-IRSs)-Based NOMA System

“…Several existing literature works, i.e., refs. [1,2,[4][5][6][7][8][9][10][11][12] have explored different aspects of NOMA potential and their outcomes have approved its effectiveness, especially against its orthogonal predecessors. NOMA has proven its vitality to be adapted as a future air interface as a stand-alone, or even in combination with existing techniques such as multi-input multi-output (MIMO) [6,13,14] and device-to-device (D2D) communications [4,15,16].…”

The Impact of User-Pairing on the Performance of Non-Orthogonal Multiple Access (NOMA) System

“…NOMA was also presented as a delivery approach for multicast systems [6], NOMAbased cloud-radio access networks (CRAN) [7], etc., most of those works have showed that expressing a multiuser NOMA system is not simple and requires a complex approach specially to design the SIC decoding process. Therefore, some researchers investigated user pairing and user clustering as a mean to handle this problem.…”

“…Based on which, the cellular spectrum is shared by choosing the D2D source that offers the highest achievable SINR. In addition, the optimization NOMA based CRAN is investigated by [7] in terms of the achievable energy efficiency. The authors proposed a number of power allocation assignments and addressed the effectiveness of NOMA-CRAN combination in a multi-tier network.…”