Performance of NOMA-Based mmWave D2D Networks Under Practical System Conditions

Abstract

This work elaborates the analysis on ergodic capacity, coverage probability, and average throughput for multi-user non-orthogonal multiple access (NOMA) based device-to-device communication networks, which operate in the millimeter-wave spectrum range and are constrained by practical system imperfections such as residual transceiver hardware impairments, imperfect channel state information, and non-ideal successive interference cancellation. More importantly, we consider that the proposed network model is limited by independent and non-identically distributed interference noises emerging from neighboring device nodes. Computationally effective and comprehensive closed-form expressions are delivered to evaluate the ergodic capacity with its upper and lower bounds, as well as coverage probability and average throughput expressions. Furthermore, the asymptotic analysis of ergodic capacity and coverage probability at high and low signal-to-noise-ratio regimes are analyzed and the corresponding closed-form expressions are presented. Valuable discussions on the fairness-based power allocation scheme for NOMA users have been provided. Moreover, a thorough Monte Carlo simulation is carried out to validate the corresponding analytical findings. Finally, simulation results have revealed that the system impairments aforementioned herein cause an ergodic capacity saturation phenomenon. Especially, interference plays a significant role as a performance limitation factor for the ergodic capacity and coverage probability.INDEX TERMS Average throughput, coverage probability, device-to-device (D2D) communications, ergodic capacity, imperfect channel state information (CSI), successive interference cancellation (SIC), millimeter-wave (mmWave), non-orthogonal multiple access (NOMA), residual transceiver hardware impairment (RTHI).

Integration of Cognitive Radio Technology in NOMA-Based B5G Networks: State of the Art, Challenges, and Enabling Technologies

“…Furthermore, the combination of device-to-device (D2D) communication, mmWave technology, and NOMA is always been one of the potential methods for supporting up to 50 billion device connections by 2025. Numerous and closely situated devices' signals, which operate in the mmWave spectrum region, are stacked in the power domain in NOMA-based D2D networks to improve overall spectral efficiency (SE) [84].…”

Energy-Efficient Utility Function-Based Channel Resource Allocation and Power Control for D2D Clusters With NOMA Enablement in Cellular Networks

“…There has been some work on the combination of NOMA and D2D communication. The con-cept of D2D clusters transmitted using NOMA technology was first proposed in the literature [19], where the D2D transmitters within each cluster communicate through multiple D2D receivers in the NOMA technology domain.Under real system conditions, NOMA-based expressions for the coverage probability and average throughput of millimeterwave D2D networks are derived in the literature [20]. The asymptotic analysis of the traversal capacity and coverage probability for high and low SNR states is also analyzed and the corresponding closed form expressions are given; In the literature [21], cellular users combining multiple D2D pairs using the NOMA approach to communication are modeled as two subproblems of pow-er control and channel assignment in order to maximize the sum rate of the D2D pairs, which are solved optimally by introducing auxiliary variables and relaxing binary constraints using a pairwise iterative algorithm;…”

Estimation of Interference Correlation in mmWave Cellular Systems

“…T HE evolution of cellular networks is pushing towards non-orthogonal multiple access (NOMA) schemes, wherein the wireless resource is not exclusively assigned to a user (as in orthogonal multiple access) but is shared among several devices that interfere. Such an approach may be applied either within each cell (in what is more specifically NOMA, [1]) or among different cells, e.g., in dynamic time-division duplexing (TDD) networks [2] and is particularly attractive in systems with partial or distributed coordination, such as in device-to-device (D2D) communications [3] or cell-free networks [4]. In all these cases, the interference among devices becomes challenging and is addressed by several techniques that can be classified according to the underlying interference model: when interference is seen as an additional data signal with a suitable structure (e.g., with known modulation and coding parameters) successive interference cancellation (SIC) or multiuser decoding solutions are applied; when interference is seen as additional noise, it is handled by suitable signal processing at the transmitter or the receiver, e.g., by beamforming and combining signals over multiple antennas in multiple-input multiple-output (MIMO) systems.…”