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

With the rapid development in wireless communication technologies, interference has become a main impediment to network performance, making interference management (IM) a critical issue. Interference steering (IS) is emerging as a novel way of IM, which can steer the spatial feature of interference to a target subspace by exploiting the interactions of multiple signals over the air to avoid the disturbance to the interfered receiver. In reality, there always exists multiple interferences from single or multiple sources. We propose three ways to realize IS. The first two of them are categorized as individual interference steering (IIS), in which multiple interfering signals are separately adjusted to either an identical direction ( a single-target IS , STIS) or different directions ( multi-target IS , MTIS), incurring single or multiple degrees of freedom (DoFs) overheads, respectively. Furthermore, by recognizing that the goal of IM is to limit the effect of interference—i.e., the effective portion of interference imposed on the intended transmission— we propose aggregated interference steering (AIS) that exploits the constructive or destructive effects of multiple interfering signals. By considering the overall effect of multiple interferences, the DoF cost of AIS is reduced to one regardless of the number of interference to be managed. Finally, the proposed three IS realizations are adapted to minimize the power cost of steering interference. Our theoretical analysis and in-depth simulation results have shown that the proposed IS schemes can effectively manage multiple interference via better utilizing the DoF and transmit power. The AIS is shown to be advantageous in both power cost and DoF consumption.

Design and Adaptation of Multi-Interference Steering

With the development of diverse wireless communication technologies, interference has become a key impediment in network performance, thus making effective interference management (IM) essential to accommodate a rapidly increasing number of subscribers with diverse services. Although there have been numerous IM schemes proposed thus far, none of them are free of some form of cost. It is, therefore, important to balance the benefit brought by and cost of each adopted IM scheme by adapting its operating parameters to various network deployments and dynamic channel conditions. We propose a novel IM scheme, called dynamic interference steering (DIS), by recognizing the fact that interference can be not only suppressed or mitigated but also steered in a particular direction. Specifically, DIS exploits both channel state information and the data contained in the interfering signal to generate a signal that modifies the spatial feature of the original interference to partially or fully cancel the interference appearing at the victim receiver. By intelligently determining the strength of the steering signal, DIS can steer the interference in an optimal direction to balance the transmitter’s power used for interference steering and the desired signal’s transmission. DIS is shown via simulation to be able to make better use of the transmit power, hence enhancing users’ spectral efficiency effectively.

pdf/dynamic-interference-steering-in-heterogeneous-cellular-43cvu0jv9a.pdf

Dynamic Interference Steering in Heterogeneous Cellular Networks

Interference management (IM) is essential to wireless communication networks, but interference suppression, a key component of IM, is known to degrade users' achievable spectral efficiency (SE). It is thus important to select an appropriate IM method with optimal operating parameters according to diverse network deployments, transmit power differences of various communication equipments, and dynamically changing channel conditions so as to balance the benefits brought by and the cost of IM. Interference neutralization (IN) has recently been receiving considerable attention, with which a duplicate of interference of the same strength and opposite phase w.r.t. the original interfering signal is generated to neutralize the disturbance at the intended receiver. However, to the best of our knowledge, all existing IN schemes assume that interference is completely neutralized without accounting for their power consumption. To remedy this deficiency, we propose a novel scheme, called dynamic interference neutralization (DIN). By intelligently determining the appropriate portion of interference to be neutralized, we balance the transmitter's power used for IN and the desired signal's transmission. We then present a new way to adaptively select one of DIN and other IM methods by taking into account the cost of multiple IM methods and their benefits. Our analysis has shown that DIN can include complete IN and non-interference management (non-IM) as special cases. The proposed strategy is shown via simulation to be able to make better use of the transmit power than existing IM methods, hence enhancing users' SE.

When and how much to neutralize interference

With the rapid development of wireless technologies, interference has become a main impediment to network performance, making interference management (IM) a critical issue that warrants a thorough investigation. In this paper, we propose a novel IM technique, called signal dodging and interference guiding (SDIG). With this method, we first intellectually move the data transmission away from the interference, hence can partially avoid the influence of disturbance to the desired signal. Then, we employ existing IM method, including zero-forcing (ZF) reception, interference alignment (IA), interference steering (IS), and etc., to further eliminate the interference. The SDIG consists of two phases, the first one is modifying the desired signal while the second is mitigating the interference. This is similar to the idea of Taichi in that both involve the actions of passive defense and active attack. Therefore, we also use the term Taichi as an equivalent for SDIG. Our in-depth simulation has shown that with the proposed scheme, both the interfered user's and the system's spectral efficiency can be significantly improved.

Taichi: Signal Dodging and Interference Guiding

An Adaptive tranSmission mechanism exploiting both interference loCality and the relationship between dEsired sigNal and inTerference (ASCENT) is proposed for uplink transmission in heterogeneous networks. The authors adopt both X channel and Z channel models according to which spatial signal processing is designed. In the X channel, the picocell base station (PBS) exploits information the macrocell base station (MBS) shares to cancel local interference, and cooperatively decodes the data carried by strong interference from a macro-user (MU), which is then fed to the MBS. As a result, a pico-user (PU) can transmit simultaneously with an MU on the same channel. In addition, adaptive reception is employed to achieve good tradeoff between interference suppression and the desired level of signal distortion. For the Z channel, the PU and the PBS adopt signal processing suitable for their own channel state. At a PBS, interference cancellation is adopted to eliminate disturbance from an MU via inter-base station collaboration. ASCENT is also extended to the case of multiple picocells. The authors’ simulation results show that in X channel mode, the achievable uplink rate of an MU can be significantly enhanced. In the case of Z channel, the PU's rate is improved while guaranteeing the MU's data rate.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-com.2016.0847

Adaptive transmission in heterogeneous networks

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Coordinated Multi-Point Transmissions Based on Interference Alignment and Neutralization

When and how much to neutralize interference

Taichi: Signal Dodging and Interference Guiding

Adaptive transmission in heterogeneous networks