Fast and efficient user pairing and power allocation algorithm for non-orthogonal multiple access in cellular networks

Non-orthogonal multiple access (NOMA) is emerging as a promising multiple access technology for the fifth generation cellular networks to address the fast growing mobile data traffic. It applies superposition coding in transmitters, allowing simultaneous allocation of the same frequency resource to multiple intra-cell users. Successive interference cancellation is used at the receivers to cancel intra-cell interference. User pairing and power allocation (UPPA) is a key design aspect of NOMA. Existing UPPA algorithms are mainly based on exhaustive search method with extensive computation complexity, which can severely affect the NOMA performance. A fast proportional fairness (PF) scheduling based UPPA algorithm is proposed to address the problem. The novel idea is to form user pairs around the users with the highest PF metrics with pre-configured fixed power allocation. Systemlevel simulation results show that the proposed algorithm is significantly faster (seven times faster for the scenario with 20 users) with a negligible throughput loss than the existing exhaustive search algorithm

Detection for 5G-NOMA: An Online Adaptive Machine Learning Approach

Non-orthogonal multiple access (NOMA) has emerged as a promising radio access technique for enabling the performance enhancements promised by the fifth-generation (5G) networks in terms of connectivity, low latency, and high spectrum efficiency. In the NOMA uplink, successive interference cancellation (SIC) based detection with device clustering has been suggested. In the case of multiple receive antennas, SIC can be combined with the minimum mean-squared error (MMSE) beamforming. However, there exists a tradeoff between the NOMA cluster size and the incurred SIC error. Larger clusters lead to larger errors but they are desirable from the spectrum efficiency and connectivity point of view. We propose a novel online learning based detection for the NOMA uplink. In particular, we design an online adaptive filter in the sum space of linear and Gaussian reproducing kernel Hilbert spaces (RKHSs). Such a sum space design is robust against variations of a dynamic wireless network that can deteriorate the performance of a purely nonlinear adaptive filter. We demonstrate by simulations that the proposed method outperforms the MMSE-SIC based detection for large cluster sizes.Comment: Accepted at ICC 201

Low-Complexity Reliability-Based Equalization and Detection for OTFS-NOMA

Orthogonal time frequency space (OTFS) modulation has recently emerged as a potential 6G candidate waveform which provides improved performance in high-mobility scenarios. In this paper we investigate the combination of OTFS with non-orthogonal multiple access (NOMA). Existing equalization and detection methods for OTFS-NOMA, such as minimum-mean-squared error with successive interference cancellation (MMSE-SIC), suffer from poor performance. Additionally, existing iterative methods for single-user OTFS based on low-complexity iterative least-squares solvers are not directly applicable to the NOMA scenario due to the presence of multi-user interference (MUI). Motivated by this, in this paper we propose a low-complexity method for equalization and detection for OTFS-NOMA. The proposed method uses a novel reliability zone (RZ) detection scheme which estimates the reliable symbols of the users and then uses interference cancellation to remove MUI. The thresholds for the RZ detector are optimized in a greedy manner to further improve detection performance. In order to optimize these thresholds, we modify the least squares with QR-factorization (LSQR) algorithm used for channel equalization to compute the the post-equalization mean-squared error (MSE), and track the evolution of this MSE throughout the iterative detection process. Numerical results demonstrate the superiority of the proposed equalization and detection technique to the existing MMSE-SIC benchmark in terms of symbol error rate (SER).Comment: 13 pages, 8 figures. arXiv admin note: substantial text overlap with arXiv:2211.0738

Transmission Scheme, Detection and Power Allocation for Uplink User Cooperation with NOMA and RSMA

In this paper, we propose two novel cooperative-non-orthogonal-multiple-access (C-NOMA) and cooperative-rate-splitting-multiple-access (C-RSMA) schemes for uplink user cooperation. At the first mini-slot of these schemes, each user transmits its signal and receives the transmitted signal of the other user in full-duplex mode, and at the second mini-slot, each user relays the other user's message with amplify-and-forward (AF) protocol. At both schemes, to achieve better spectral efficiency, users transmit signals in the non-orthogonal mode in both mini-slots. In C-RSMA, we also apply the rate-splitting method in which the message of each user is divided into two streams. In the proposed detection schemes for C-NOMA and C-RSMA, we apply a combination of maximum-ratio-combining (MRC) and successive-interference-cancellation (SIC). Then, we derive the achievable rates for C-NOMA and C-RSMA, and formulate two optimization problems to maximize the minimum rate of two users by considering the proportional fairness coefficient. We propose two power allocation algorithms based on successive-convex-approximation (SCA) and geometric-programming (GP) to solve these non-convex problems. Next, we derive the asymptotic outage probability of the proposed C-NOMA and C-RSMA schemes, and prove that they achieve diversity order of two. Finally, the above-mentioned performance is confirmed by simulations.Comment: 32 pages, 13 figure

Non-orthogonal Multiple Access (NOMA) with Asynchronous Interference Cancellation

Non-orthogonal multiple access (NOMA) allows allocating one carrier to more than one user at the same time in one cell. It is a promising technology to provide high throughput due to carrier reuse within a cell. In this thesis, a novel interference cancellation (IC) technique is proposed for asynchronous NOMA systems, which uses multiple symbols from each interfering user to carry out IC. With the multiple symbol information from each interfering user the IC performance can be improved substantially. The proposed technique creates and processes so called "IC Triangles". That is, the order of symbol detection is based on detecting all the overlapping symbols of a stonger user before detecting a symbol of a weak user. Also, successive IC (SIC) is employed in the proposed technique. Employing IC Triangles together with the SIC suppresses co-channel interference from strong (earlier detected) signals for relatively weak (yet to be detected) signals and make it possible to achieve low bit error rate (BER) for all users. Further, iterative signal processing is used to improve the system performance. Employing multiple iterations of symbol detection which is based on exploiting a priori estimate obtained from the previous iteration can improve the detection and IC performances. The BER and capacity performance analyses of an uplink NOMA system with the proposed IC technique are presented, along with the comparison to orthogonal frequency division multiple access (OFDMA) systems. Performance analyses validate the requirement for a novel IC technique that addresses asynchronism at NOMA uplink transmissions. Also, numerical and simulation results show that NOMA with the proposed IC technique outperforms OFDMA for uplink transmissions. It is also concluded from the research that, in the NOMA system, users are required to have large received power ratio to satisfy BER requirements and the required received power ratio increases with increasing the modulation level. Also, employing iterative IC provides significant performance gain in NOMA and the number of required iterations depend on the modulation level and detection method. Further, at uplink transmissions, users' BER and capacity performances strongly depend on the relative time offset between interfering users, besides the received power ratio