Thesis title: Code-domain non orthogonal multiple access for 5G networks
While expected to be standardized by the year 2020, the fifth generation (5G) cur- rently receives considerable attention from the wireless community [1]. Among the key features chacracterizing 5G, non-orthogonal multiple access (NOMA) is one of the promising technologies, that are expected to address the targets of 5G wireless communications, including high spectral efficiency, massive connectivity, and low latency [2, 3].
Back to the history of cellular communications from 1G to 4G, the radio multiple access schemes are mostly characterized by orthogonal multiple access (OMA), where different users are assigned to orthogonal resources in either frequency (frequency-division multiple access (FDMA) and orthorgonal FDMA (OFDMA)), time (time-division multiple access (TDMA)) or code (synchronous code-division multiple access (CDMA) in underloaded condition) domains. However, 5G multiple access is required to support a wide range of use cases, providing access to massive numbers of low-power internet-of-thing (IoT), as well as broadband user terminals in the cellular network. Providing high spectral efficiency, while minimizing sig- naling and control overhead to improve efficiency, may not be feasible to achieve by OMA techniques [4]. In fact, the orthogonality condition can be imposed as a requirement only when the system is underloaded, that is, when the number of active users is lower than the number of available resource elements (degrees of freedom or dimensions).
The idea of NOMA is to serve multiple users in the same band and abandon any attempt to provide orthogonal access to different users as in conventional OMA. Orthogonality naturally drops when the number of active users is higher than the number of degrees of freedom, and “collisions” appear. One possible way of controlling collisions in NOMA is to share the same signal dimension among users and exploit power (power-domain NOMA (PDM-NOMA)) vs. code (code-domain NOMA (CDM-NOMA)) domains [2]. However, refer to NOMA, most of intuition gained from the recent literature implies power-domain case [5], which was firstly introduced by Mazzini [6], including integration of NOMA with other technologies such as MIMO-NOMA, Cognitive Radio NOMA (CR-NOMA), mm-Wave NOMA, full-duplex NOMA and so on.
In PDM-NOMA, it uses superposition coding, a well-known non-orthogonal scheme for downlink transmissions [7], and makes superposition decoding possible by allocating different levels of power to different users [8]. The “near” user, with a higher channel gain, is typically assigned with less transmission power, which helps making successive interference cancellation (SIC) affordable at this user [9]. Interested readers are referred to the latest works on PDM-NOMA such as [5, 10].
CDM-NOMA is characterized by sparsity employed in spreading sequences or multi-dimensional codewords. It is worthy noting that CDM-NOMA and conven- tional CDMA share the same working principle in exploiting different spreading codes. As a matter of fact, several characterizing variants of CDM-NOMA, such as low-density spreading CDMA (LDS-CDMA) [11–13], low-density spreading or- thogonal frequency-division multiplexing (LDS-OFDM) [14], sparse code multiple access (SCMA) [15], pattern division multiple access (PDMA) [16], and multi-user shared access (MUSA) [17], may be inferred from the framework of CDMA. By re- laxing orthogonality requirements, CDM-NOMA variants enable flexible resource allocation, and reduce hardware complexity.
This thesis aims to shed some light on understanding CDM-NOMA and its different dialects, particularly the schemes with single-carrier waveforms from an information-theoretic perspective. At the moment, NOMA has been currently proposed for the 3rd generation partnership project long-term evolution advanced (3GPP-LTE-A) standard, the next general digital TV standard (ATSC 3.0), and the 5G New Radio (NR) standard. In fact, CDM-NOMA variants are currently under consideration via Specification TS 38.812 (Study on NOMA for NR) in anticipation to have a “ready” NR system in 2020 [18]. The emergence of a complete theoretical work on CDM-NOMA is, therefore, of essence and of expectation to contribute as a timely reference for future release of 5G standardization.
In order to understand CDM-NOMA1 in terms of fundamental limits, the con- sidered framework focuses on investigating the following issues:
• the impact of system load, which classifies NOMA vs. OMA,
• the impact of sparsity, which classifies NOMA further into low-dense vs. dense,
• the impact of regularity, which characterizes possible spreading mapping constraints,
• theimpactofthechannelfading,especiallyflat-fading,whichisverycommon in practical scenarios,
• the impact of the channel knowledge, known as channel state information (CSI), which is characterized by the rapid change of real-world communication channels.
The first three issues are investigated subject to the ideal assumption of AWGN channel, and the rests are studied subject to the flat-fading channel assumption, respectively.