The ambitious high data-rate applications in the envisioned future beyond fifth-generation (B5G) wireless networks require new solutions, including the advent of more advanced architectures than the ones already used in 5G networks, and the coalition of different communications schemes and technologies to enable these applications requirements. Among the candidate communications schemes for future wireless networks are non-orthogonal multiple access (NOMA) schemes that allow serving more than one user in the same resource block by multiplexing users in other domains than frequency or time. In this way, NOMA schemes tend to offer several advantages over orthogonal multiple access (OMA) schemes such as improved user fairness and spectral efficiency, higher cell-edge throughput, massive connectivity support, and low transmission latency. With these merits, NOMA-enabled transmission schemes are being increasingly looked at as promising multiple access schemes for future wireless networks. When the power domain is used to multiplex the users, it is referred to as the power domain NOMA (PD-NOMA). In this paper, we survey the integration of PD-NOMA with the enabling communications schemes and technologies that are expected to meet the various requirements of B5G networks. In particular, this paper surveys the different rate optimization scenarios studied in the literature when PD-NOMA is combined with one or more of the candidate schemes and technologies for B5G networks including multiple-input-single-output (MISO), multiple-input-multiple-output (MIMO), massive-MIMO (mMIMO), advanced antenna architectures, higher frequency millimeter-wave (mmWave) and terahertz (THz) communications, advanced coordinated multi-point (CoMP) transmission and reception schemes, cooperative communications, cognitive radio (CR), visible light communications (VLC), unmanned aerial vehicle (UAV) assisted communications and others. The considered system models, the optimization methods utilized to maximize the achievable rates, and the main lessons learnt on the optimization and the performance of these NOMA-enabled schemes and technologies are discussed in detail along with the future research directions for these combined schemes. Moreover, the role of machine learning in optimizing these NOMA-enabled technologies is addressed.

A Survey of Rate-Optimal Power Domain NOMA With Enabling Technologies of Future Wireless Networks

Cell-free massive multiple-input multiple-output (MIMO) employs a large number of distributed access points (APs) to serve a small number of user equipments (UEs) via the same time/frequency resource. Due to the strong macro diversity gain, cell-free massive MIMO can considerably improve the achievable sum-rate compared to conventional cellular massive MIMO. However, the performance of cell-free massive MIMO is upper limited by inter-user interference (IUI) when employing simple maximum ratio combining (MRC) at receivers. To harness IUI, the expanded compute-and-forward (ECF) framework is adopted. In particular, we propose power control algorithms for the parallel computation and successive computation in the ECF framework, respectively, to exploit the performance gain and then improve the system performance. Furthermore, we propose an AP selection scheme and the application of different decoding orders for the successive computation. Finally, numerical results demonstrate that ECF frameworks outperform the conventional CF and MRC frameworks in terms of achievable sum-rate. 

/pdf/improving-sum-rate-of-cell-free-massive-mimo-with-expanded-11te6sug.pdf

Improving Sum-Rate of Cell-Free Massive MIMO With Expanded Compute-and-Forward

Both interference alignment (IA) and interference neutralization (IN) are exploited for coordinated multi-point (CoMP) communications. With the cooperation of the base station (BS), a transmit precoder and a receive filter are jointly designed, and concurrent transmissions of multiple data streams are then enabled. In the design of a precoder, the IN is applied to the interferences carrying the same data so as to align the interfering signals in the opposite direction in a subspace. On the other hand, for interferences carrying different information, IA is employed to align them in the same direction in a subspace, thus reducing the interference signal observed at the receiver side. Based on different precoding schemes at the transmitter’s side, receivers adopt zero forcing (ZF) so as to recover the desired data. The proposed IA- and IN-based CoMP (IAN-CoMP) mechanism can achieve effective interference cancellation and suppression by exploiting limited and flexible collaboration at the BS side. It can also make a flexible tradeoff between the cooperation overhead and the system’s achievable degrees of freedom (DoFs). We extend the mechanism to general cases where the antenna configurations at both the transmitter and receiver sides, the number of transmitters participating in CoMP, and that of simultaneously served users are variable. Moreover, we discuss both single-location and multi-location-based realizations of the IAN-CoMP. Finally, by defining the average transmit and receive cooperation order, we analyze the upper bound for IAN-CoMP. Our in-depth simulation shows that the IAN-CoMP can significantly improve the spectral efficiency (SE) for cell-edge users.

Coordinated Multi-Point Transmissions Based on Interference Alignment and Neutralization

In cloud radio access networks, functional split refers to a division of signal processing functionalities between the baseband unit (BBU) pool and remote radio heads (RRHs). The functionality of baseband signal precoding can either be performed by the BBU pool or RRHs, which corresponds to different functional splits. The compression-after-precoding (CAP) and data-sharing (DS) strategies are the realizations of these two functional splits. In this paper, we propose a flexible functional split design to enable the dynamic functional configuration of each active RRH to use either CAP or DS strategy. Our goal is to minimize the aggregate power consumption, while taking into account limited fronthaul capacity, fronthaul power consumption, and quality-of-service requirement. We formulate a joint RRH mode (i.e., CAP, DS, and sleep) selection, precoding design, and fronthaul compression problem. The formulated problem is a non-convex quadratically constrained combinatorial optimization problem. Through sequential convex programming and $\ell _1$ -norm convex relaxation, the problem is transformed into a sequence of semidefinite programming problems. An efficient algorithm based on the majorization–minimization scheme is developed to solve the problem. Simulations demonstrate the importance of considering the limited fronthaul capacity and the performance improvement of the proposed algorithm compared with the pure CAP and DS strategies.

Flexible Functional Split Design for Downlink C-RAN With Capacity-Constrained Fronthaul

Non-orthogonal multiple access (NOMA) schemes serve more than one user in the same resource block by multiplexing users in other domains than frequency and time. In this way, NOMA schemes offer several advantages over orthogonal multiple access (OMA) schemes such as improved user fairness and spectral efficiency, higher cell-edge throughput, massive connectivity support, and low transmission latency. With these merits, NOMA transmission schemes are being increasingly looked at as a promising multiple access scheme for future wireless networks. When the power domain is used to multiplex users, it is referred to as the power domain NOMA (PDNOMA) scheme. In this paper, we survey the integration of the PD-NOMA scheme with other upcoming communication schemes and technologies that satisfy the requirements of 5G and beyond 5G (B5G) networks. In particular, this paper surveys the rate optimization schemes studied in the literature when the PD-NOMA scheme is combined with MIMO and massive MIMO (mMIMO), millimeter wave (mmWave) communications, coordinated multi-point (CoMP) transmission and reception, cooperative communications, cognitive radio (CR), visible light communications (VLC), and unmanned aerial vehicle (UAV) assisted communications. The considered system models, the optimization methods used to maximize the achievable rates, and the main outcomes on the performance of these NOMA-enabled schemes are discussed along with future research directions for these combined schemes.

A Survey of Rate-optimal Power Domain NOMA Schemes for Enabling Technologies of Future Wireless Networks.

Both interference alignment (IA) and interference neutralization (IN) are exploited for Coordinated Multi-Point (CoMP) transmissions. With the base station's cooperation, transmit precoder and receive filter are designed jointly, and then concurrent transmissions of multiple data streams are achieved. In the design of preprocessing, IN is applied to the interferences carrying same data so as to align the interfering signals with opposite directions in a subspace. On the other hand, for interferences carrying different information, IA is employed to align them with the same direction in a subspace, thus reducing the interference signal dimension observed at the user side. Based on different precoding schemes at the transmitter's side, receivers adopt zero-forcing (ZF) so as to recover the desired data. The proposed interference alignment and neutralization based CoMP (IAN-CoMP) mechanism can achieve effective interference cancellation and suppression by exploiting limited and flexible collaboration only at the base station (BS) side. We also extend the mechanism to general cases where the antenna configurations at both transmitter and receiver side, the number of transmitters participating in CoMP and simultaneously served users are variable. In addition, the proposed scheme can also achieve a flexible tradeoff between cooperation overhead and the system's achievable degrees of freedom (DoFs). Our in-depth simulation results show that IAN-CoMP can significantly improve the spectral efficiency (SE) for cell-edge users.

Coordinated multi-point transmissions based on interference alignment and neutralization

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Coordinated Multi-Point Transmissions Based on Interference Alignment and Neutralization

Coordinated multi-point transmissions based on interference alignment and neutralization