Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges

Abstract

Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same time and frequency, NOMA can scale up the number of served users, increase the spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. While single-cell NOMA has drawn significant attention recently, much less attention has been given to multi-cell NOMA. This article discusses the opportunities and challenges of NOMA in a multi-cell environment. As the density of base stations and devices increases, inter-cell interference becomes a major obstacle in multi-cell networks. As such, identifying techniques that combine interference management approaches with NOMA is of great significance. After discussing the theory behind NOMA, this paper provides an overview of the current literature and discusses key implementation and research challenges, with an emphasis on multi-cell NOMA. I. WHAT DRIVES NOMA?The next generation of wireless networks will require a paradigm shift in order to support massive numbers of devices with diverse data rate and latency requirements. Particularly, the increasing demand for Internet of Things (IoT) devices poses challenging requirements on 5G wireless systems. Two key features of 5G are expected to be a latency of 1ms, compared to 10 ms in the 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE), and support for 10 Gbps throughput.To fulfill these requirements, numerous potential technologies have been introduced over the last few years.

A Survey of Non-Orthogonal Multiple Access for 5G

“…Furthermore, in order to increase the attainable performance of the SIC receiver, cooperative NOMA transmission has been proposed in [29] [30]. A range of investigations related to multi-cell NOMA schemes were carried out in [31]- [33]. Moreover, since having an increased number of cell-edge users typically degrades the efficiency of coordinated multi-point (CoMP) transmissions, this limitation was circumvented by a promising NOMA solution proposed for a CoMP system in [34].…”

“…It has been shown that the average rate coverage of a NOMA cluster is better than that of its counterpart OMA cluster for higher number of users per cell and for higher target rate requirements. Furthermore, an up-todate literature review of interference management techniques that apply NOMA in multi-cell networks has been provided in [33], including both NOMA using joint processing and NOMA relying on coordinated scheduling/beamforming. The major practical issues and challenges that arise in the implementation of multi-cell NOMA have also been highlighted in [33], such as the SIC implementation issues, imperfect CSI, as well as multi-user power allocation and clustering.…”

Uplink Nonorthogonal Multiple Access Technologies Toward 5G: A Survey

“…The major design target of NOMA is to introduce controllable mutual interference among users to achieve a fine tradeoff between multiplexing gain and detection reliability. According to both theoretical and numerical analysis, NOMA outperforms OMA with respect to SE, EE, and connectivity [8][9][10][11]. To grasp the development of NOMA technologies, some published review papers have presented different aspects of NOMA.…”

“…Furthermore, NOMA can be jointly designed with cooperative multiple point (CoMP) [9,109,110] or multipleantenna technology [41,[111][112][113]. Also, there have been some initial studies about employing NOMA in wireless power transfer network to increase the access opportunities [114][115][116].…”

Effective Design of Multi-User Reception and Fronthaul Rate Allocation in 5G Cloud RAN

“…NOMA is also helpful in a multi-cell environment to manage inter-cell interference [6]. To deal with practical constraints such as receiver complexity, it has been proposed in [7] to perform the uplink multi-user detection needed in NOMA over several smaller subsets of users, while each subset transmits on a different channel.…”