Non-Orthogonal Multiple Access (NOMA) has recently been considered as a key enabling technique for 5G cellular systems. In NOMA, by exploiting the channel gain differences multiple users are multiplexed into transmission power domain and then non-orthogonally scheduled on the same spectrum resources. Successive interference cancellation (SIC) is then applied at the receiver(s) to decode the message signals. In this paper, first we briefly describe the differences in the working principles of uplink and downlink NOMA transmissions. Then, for both uplink and downlink NOMA, we formulate a sum-throughput maximization problem in a cell such that the user clustering (i.e., grouping users into a single cluster or multiple clusters) and power allocations in NOMA cluster(s) can be optimized under transmission power constraints, minimum rate requirements of the users, and SIC constraints. Due to the combinatorial nature of the formulated mixed integer non-linear programming (MINLP) problem, we solve the problem in two steps, i.e., by first grouping users into clusters and then optimizing their respective power allocations. In particular, we propose a low-complexity suboptimal user grouping scheme. The proposed scheme exploits the channel gain differences among users in a NOMA cluster and group them into a single cluster or multiple clusters in order to enhance the sum-throughput of the system. For a given set of NOMA clusters, we then derive the optimal power allocation policy that maximizes the sum throughput per NOMA cluster and in turn maximizes the overall system throughput. Using KKT optimality conditions, closed-form solutions for optimal power allocations are derived for any cluster size, considering both uplink and downlink NOMA systems. Numerical results compare the performance of NOMA over orthogonal multiple access (OMA) and illustrate the significance of NOMA in various network scenarios.

Abstract-The evolving fifth generation (5G) cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, e.g., higher data rates, excellent endto-end performance and user-coverage in hot-spots and crowded areas with lower latency, energy consumption and cost per information transfer. To address these challenges, 5G systems will adopt a multi-tier architecture consisting of macrocells, different types of licensed small cells, relays, and device-to-device (D2D) networks to serve users with different quality-of-service (QoS) requirements in a spectrum and energy-efficient manner. Starting with the visions and requirements of 5G multi-tier networks, this article outlines the challenges of interference management (e.g., power control, cell association) in these networks with shared spectrum access (i.e., when the different network tiers share the same licensed spectrum). It is argued that the existing interference management schemes will not be able to address the interference management problem in prioritized 5G multitier networks where users in different tiers have different priorities for channel access. In this context, a survey and qualitative comparison of the existing cell association and power control schemes is provided to demonstrate their limitations for interference management in 5G networks. Open challenges are highlighted and guidelines are provided to modify the existing schemes in order to overcome these limitations and make them suitable for the emerging 5G systems.

Drones (or unmanned aerial vehicles [UAVs]) are expected to be an important component of fifth generation (5G)/beyond 5G (B5G) cellular architectures that can potentially facilitate wireless broadcast or point-to-multipoint transmissions. The distinct features of various drones such as the maximum operational altitude, communication, coverage, computation, and endurance impel the use of a multi-tier architecture for future drone-cell networks. In this context, this article focuses on investigating the feasibility of multi-tier drone network architecture over traditional single-tier drone networks and identifying the scenarios in which drone networks can potentially complement the traditional RF-based terrestrial networks. We first identify the challenges associated with multi-tier drone networks as well as drone-assisted cellular networks. We then review the existing state-of-the-art innovations in drone networks and drone-assisted cellular networks. We then investigate the performance of a multitier drone network in terms of spectral efficiency of downlink transmission while illustrating the optimal intensity and altitude of drones in different tiers numerically. Our results demonstrate the specific network load conditions (i.e., ratio of user intensity and base station intensity) where deployment of drones can be beneficial (in terms of spectral efficiency of downlink transmission) for conventional terrestrial cellular networks.Index Terms-5G and beyond 5G (B5G) cellular, point-tomultipoint/broadcast communication, drone-aided wireless communications, multi-tier drones, spectral efficiency

Non-orthogonal multiple access (NOMA) serves multiple users by superposing their distinct message signals.The desired message signal is decoded at the receiver by applying successive interference cancellation (SIC). Using the theory of Poisson cluster process (PCP), this paper provides a framework to analyze multi-cell uplink NOMA systems. Specifically, we characterize the rate coverage probability of a NOMA user who is at rank m (in terms of the distance from its serving BS) among all users in a cell and the mean rate coverage probability of all users in a cell. Since the signal-to-interference-plus-noise ratio (SINR) of m-th user relies on efficient SIC, we consider three scenarios, i.e., perfect SIC (in which the signals of m − 1 interferers who are stronger than m-th user are decoded successfully), imperfect SIC (in which the signals of of m − 1 interferers who are stronger than m-th user may or may not be decoded successfully), and imperfect worst case SIC (in which the decoding of the signal of m-th user is always unsuccessful whenever the decoding of its relative m − 1 stronger users is unsuccessful). The worst case SIC assumption provides remarkable simplifications in the mathematical analysis and is found to be highly accurate for scenarios of practical interest. To analyze the rate coverage expressions, we first characterize the Laplace transforms of the intra-cluster interferences in closed-form considering both perfect and imperfect SIC scenarios. In the sequel, we characterize the distribution of the distance of a user at rank m which is shown to be the generalized Beta distribution of first kind and the conditional distribution of the distance of the intracluster interferers which is different for both perfect and imperfect SIC scenarios. The Laplace transform of the inter-cluster interference is then characterized by exploiting distance distributions from geometric probability. The derived expressions are customized to capture the performance of a user at rank m in an equivalent orthogonal multiple access (OMA) system. Finally, numerical results are presented to validate the derived expressions. It is shown that the average rate coverage of a NOMA cluster outperforms its counterpart OMA cluster with higher number of users per cell and higher target rate requirements. A comparison of Poisson Point Process (PPP)-based and PCP-based modeling is conducted which shows that the PPP-based modeling provides optimistic results for the NOMA systems.

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