Successive Interference Cancellation Research Articles

Optimization of resource allocation in 5G networks: A network slicing approach with hybrid NOMA for enhanced uRLLC and eMBB coexistence

SummaryTraditional Orthogonal Multiple Access (OMA) and spectrum sharing methods struggle to provide the diverse quality of service (QoS) demands for enhanced mobile broadband (eMBB), ultra‐reliable low latency communications (uRLLC), and massive machine type communications (mMTC) leading to suboptimal performance and service quality degradation. Single‐carrier‐non‐orthogonal multiple access (SC‐NOMA) appears to be a more optimized solution. It can serve multiple users simultaneously on the same time‐frequency resources. This approach offers both enhanced spectrum efficiency and meets the QoS requirements for the coexistence of eMBB, uRLLC, and mMTC. However, SC‐NOMA has some drawbacks. Decoding a user's signal involves a complex successive interference cancellation (SIC) process that gets harder with more users causing delays and errors. Additionally, strong user signals can interfere with weaker ones, limiting the number of users per channel. In order to overcome the drawbacks associated with OMA and SC‐NOMA, this paper introduces a new method called user‐paired NOMA (hybrid NOMA). Hybrid NOMA adopts a strategic approach, employing two user pairing techniques: near‐far/far‐near (NF‐FN) and near‐near/far‐far (NN‐FF). NF‐FN pairing prioritizes users with similar signal strengths but different distances from the base station. This minimizes interference for the weaker user during SIC. NN‐FF pairing, on the other hand, groups users with similar signal strengths and proximity. This approach further simplifies SIC and minimizes potential interference altogether. The simulation results demonstrate trade‐offs between eMBB and uRLLC performance. OMA suffers with dedicated resource allocation, while SC‐NOMA balances performance but experiences interference. NN‐FF prioritizes eMBB and offers best latency, while NF‐FN prioritizes uRLLC with high spectral efficiency but suffers from higher latency. Finally, by providing a thorough grasp of how hybrid NOMA resource allocation works to improve the performance of various use cases, this research makes a significant contribution to the field of 5G spectrum optimization.

A framework for co-existence of radar and communication with joint design

The integration of both sensing and communication functions is a crucial feature for future communication systems. This paper considers a novel scenario where a radar covers multiple small-cell base stations which operate in different spectra. Due to the limited spectra resource, the radar needs to reuse the spectra of one BS for tracking. To suppress interference and improve performance, we propose a framework including two stages and the corresponding communication and sensing algorithms. Specifically, at the detection stage, we aim to minimize the system transmit power while maintaining the performance of both radar and communication. At the tracking stage, our goal is to maximize the radar sensing performance under a given power budget, while ensuring communication quality. Due to the complexity of the original problem, we address it by introducing auxiliary variables and proposing a penalty dual decomposition-based algorithm, enabling us to solve a more tractable form of the problem. In the inner loop, we propose a concave–convex procedure-based algorithm to handle the optimization problem, while adopting the block coordinate descent algorithm to iteratively update the variables. In the outer loop, we update the penalty term or Lagrange multipliers. Furthermore, we propose a radar target parameter estimation algorithm based on successive interference cancellation, which aims to mitigate communication interference. Finally, numerical simulations demonstrate the effectiveness of the proposed system, and the superior performance of our proposed algorithms over benchmark algorithms.

Effective capacity of STAR-RIS assisted RSMA network with imperfect SIC

The proliferation of various Internet of Everything applications places urgent demand for high energy efficiency, massive connection and wide coverage for the future communication era. Motivated by this, rate-splitting multiple access (RSMA) and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has attracted wide publicity from industry and academia. In this paper, we consider a STAR-RIS assisted two-user RSMA network with imperfect successive interference cancellation, and all channels are modeled as Nakagami-m distribution. By adopting effective capacity (EC) as the metric, we analyze the system performance under certain quality-of-service constraint. Specifically, analytical expressions of EC for a pair of RSMA users are provided. To explore further insights, high signal-to-noise ratio (SNR) conditions are also considered. Furthermore, the effect of some specific elements on system EC performance are analyzed, and some significant conclusions are obtained as follows: (1) As SNR grows, the effective capacities of two users improve, but finally converge to constant at high SNR. (2) The increase in the amount of the STAR-RIS elements can obviously increase the effective capacities. (3) Compared to traditional STAR-RIS assisted non-orthogonal multiple access networks, STAR-RIS assisted RSMA network has distinct advantages to improve system EC performance.

Outage and throughput performance analysis of incremental relaying‐based underlay cognitive nonorthogonal multiple access networks with maximal ratio combining

SummaryIn this paper, we investigate the effectiveness of incremental relaying (IR)‐based underlay cognitive nonorthogonal multiple access (CNOMA) system with maximal ratio combining (MRC). Considering imperfect successive interference cancelation (i‐SIC), we derive analytical expressions for the outage probabilities experienced by the secondary users (SUs) and the system outage probability of the IR‐CNOMA system. We also derive the analytical expression for the outage probability of far SUs by considering IR‐CNOMA system with MRC. The maximum transmit power constraint of the secondary nodes and the interference threshold constraint of the primary receiver are considered in the analysis. We also evaluate the system throughput of IR‐CNOMA network. We also derive outage and throughput expression for the traditional cooperative relaying‐based CNOMA system (CR‐CNOMA) for the purpose of comparison. We derive analytical expression for the asymptotic outage probability and the asymptotic system outage probabilities of the SUs of IR‐CNOMA system. Further, we derive expressions for the optimal power allocation (OPA) factor at the secondary source that minimizes the asymptotic system outage probability of the IR‐CNOMA system. Through numerical and simulation investigations, we demonstrate that the system outage probability significantly lowers when the OPA factor is selected based on the criteria outlined in this work. It can be observed from the results that the IR‐CNOMA system outperforms the conventional CR‐CNOMA system in terms of outage probabilities and throughput. The outage probability is further reduced when IR‐CNOMA system with MRC is considered for the far SUs.

Ergodic analysis of IRS-NOMA with inter-cell interference and Imperfect-CSI and SIC over Nakagami-m faded channel

Future wireless technology requires higher data rates, low latency, and flexibility to provide services to users. To fulfil these demands, various multiple access techniques are proposed. Among these techniques, the non-orthogonal multiple access technique (NOMA) is providing better features compared to orthogonal multiple access (OMA) techniques, such as more number of radio resources with low latency. In NOMA based communication system, if a user is lying on the cell's edge, their performance is poor. Recently, intelligent reflecting surfaces (IRS)-NOMA system is introduced to enhance its performance. To implement IRS-NOMA in a real-time scenario, the impact of inter-cell interference and imperfect-channel state information (CSI) and successive interference cancellation (SIC) is very much required. In this work, we derived analytical expressions to evaluate the Ergodic capacity of the IRS-NOMA over the Nakagami-m faded channel by considering inter-cell interference, imperfect-CSI, and SIC. By considering these factors, this work offers a comprehensive understanding of the system's capabilities and limitations. Here, two user IRS-NOMA is considered and also evaluated the analytical results by varying fading parameter (m), number of interferers (K), error in CSI and SIC, and IRS elements. These results are also supported by simulated results.

Error Mitigation in Noma for Underlay CR Networks with Imperfect Successive Interference Cancellation

Error Mitigation in Noma for Underlay CR Networks with Imperfect Successive Interference Cancellation

Decorrelative successive interference cancellation for cyclic interleaved frequency division multiplexing

Decorrelative successive interference cancellation for cyclic interleaved frequency division multiplexing

Outage and average sum‐rate analysis of intelligent reflecting surface assisted nonorthogonal multiple access system over η−μ fading channel

SummaryIntelligent reflecting surface (IRS) is evolved as a one of key technology by enabling a reconfigurable, intelligent, and low power for the sixth‐generation (6G) wireless communication. In this research, an IRS‐assisted NOMA network is explored over fading channel, where IRS is placed on top of the base station (BS). IRS aids in fine‐tuning the phase of the incoming signal from BS in a meticulous way, which improves the performance of the system. The statistical channel modeling of downlink IRS‐NOMA system is proposed and validated with Monte Carlo (MC) simulation. Also, analytical expressions of OP and average sum‐rate are derived for user in IRS‐NOMA system over fading channel. Furthermore, the influence of performance factors such as number of reflecting elements (M), power allocation factor, and imperfect successive interference cancelation (I‐SIC) on OP are examined. Simulation results reveal that the IRS‐NOMA system experiences less outage compared to IRS‐OMA and conventional relaying techniques.

User Clustering with Spatial Concept using Supervised Learning for NOMA Downlink

This research aims to optimize the performance of Successive Interference Cancellation (SIC) in Power Domain Non-Orthogonal Multiple Access (PD-NOMA) technology by applying spatial concepts through the use of beamforming techniques. User clustering is a key element in achieving this goal, and this research applies various supervised machine learning classification algorithms including Decision Tree, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest, Logistic Regression, and Naive Bayes. The experimental results show that Random Forest achieves the highest accuracy in classifying users, followed by Decision Tree. In addition, in measuring performance using ROC (Receiver Operating Characteristic) and AUC (Area Under the Curve) curves, Decision Tree and Random Forest achieved the best results as well. While in terms of experimentation process time, decision tree has a faster time than random forest. Overall, Random Forest and Decision Tree algorithms are suitable for the task of user clustering in the context of PD-NOMA which utilizes the spatial concept of user to Base Station (BS).

Optimization of handoff for joint uplink base station association and power control with max‐min fairness in NOMA small‐cell networks

SummaryThe handoff rate and load balancing are two important issues that have a great impact on the spectrum and energy efficiency in the small‐cell networks (SCN). This paper investigates the handoff optimization in SCN with power‐domain non‐orthogonal multiple access (NOMA) that uses successive interference cancelation (SIC), considering the fairness among base stations (BSs). We study the joint base station association and power control problem by considering the motion of mobile users (MUs) and load balancing in the SCNs. Under the maximum allowable transmit power and minimum average‐rate constraints, two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs. The total power consumption minimization and the system‐wide and handoff utility maximization problems are combined into a single‐stage optimization problem through the weighted‐sum method. We solve the formulated problem using a game theory‐based algorithm and primal decomposition theory. The simulation results show that our proposed algorithm can significantly reduce the frequent handoffs and bring a fair power‐controlled BS association in SCN.

Outage Performance of Underlay CR-NOMA-based D2D Communications under Imperfect CSI and SIC

Background: Non-orthogonal multiple access (NOMA) is a promising technique for improving wireless communication performance in the future. In addition to NOMA, cognitive radio (CR) is another technology that can address the issue of limited spectrum availability and meet the increasing demands for wireless connectivity. Methods: This paper focuses on investigating underlay CR-NOMA-based D2D communications. The study assumes a decode-and-forward (DF) mode used in the system, where nearby users (D1, D2) act as helper users to assist distant users (D3, D4). The paper derives the closed-form expressions for outage probability (OP) and throughput at the far users in three scenarios: (1) Perfect successive interference cancellation (SIC) and perfect channel state information (CSI), (2) Imperfect CSI, and (3) Imperfect SIC. Results: In CR-NOMA mode, the results indicate that the performance of user D4 was better than user D3. Additionally, the OP performance of distant users employing CR-NOMA mode surpasses that of users using CR-OMA mode. The optimal power allocation (PA) values are investigated. Conclusion: The presence of imperfect CSI and SIC has an unfavorable influence on the outage performance. Monte Carlo simulations are used to validate the derived analytical expressions.

NOMA for Integrating Sensing and Communications Toward 6G: A Multiple Access Perspective

This article focuses on the development of integrated sensing and communications (ISAC) from a multiple access (MA) perspective, where the idea of non-orthogonal multiple access (NOMA) is exploited for harmoniously accommodating the sensing and communication functionalities. We first reveal that the developing trend of ISAC is from orthogonality to non-orthogonality, and introduce the fundamental models of the downlink and uplink ISAC while identifying the design challenges from the MA perspective. (1) For the downlink ISAC, we propose two novel designs, namely NOMA-empowered downlink ISAC and NOMA-inspired downlink ISAC to effectively coordinate the inter-user interference and the sensingto- communication interference, respectively. (2) For the uplink ISAC, we first propose a pure-NOMA-based uplink ISAC design, where a fixed communication-to-sensing successive interference cancellation order is employed for distinguishing the mixed sensing-communication signal received over the fully shared radio resources. Then, we propose a general semi-NOMA-based uplink ISAC design, which includes the conventional orthogonal multiple access-based and pure-NOMA-based uplink ISAC as special cases, thus being capable of providing flexible resource allocation strategies between sensing and communication. Along each proposed NOMA-ISAC design, numerical results are provided for showing the superiority over conventional ISAC designs.

DNN-based algorithm for joint SIC ordering and power allocation in downlink NOMA-enabled heterogeneous networks

In the heterogeneous network (HetNet) employing downlink non-orthogonal multiple access (NOMA), we focus on the non-convex optimization problem to optimize the spectral efficiency (SE) while the users satisfy the quality-of-service (QoS) requirement. In the previous work, the optimal joint successive interference cancellation and power allocation (JSPA) algorithm for maximizing SE is proposed to solve the mixed-integer non-linear programming (MINLP) problem in NOMA-enabled HetNet. However, the optimal solution requires exponential complexity by the number of base stations (BSs). Therefore, we present a deep neural network (DNN)-based algorithm for JSPA to reduce the complexity. In particular, to deal with the MINLP-based JSPA problem, we reformulate it into an equivalently simple problem that optimizes only the power consumption of BSs. Then, we introduce the unsupervised DNN-based method for JSPA to handle the simplified problem. The presented scheme yields improved SE and outage performance compared with traditional DNN-based methods. Additionally, we propose a user selection scheme with low complexity to enhance the SE of the proposed DNN-based power allocation. Through simulations, we illustrate that the suggested DNN-based scheme can attain SE performance similar to that of the optimal scheme.

Joint altitude and beamwidth optimization for LEO satellite‐based IoT constellation

SummaryLow Earth Orbit (LEO) satellite‐based Internet of Things (IoT) has become a hot topic in IoT networks due to the ability of global coverage, especially in remote areas. How to design a commercial LEO satellite‐based constellation to meet the IoT traffic requirement remains an open problem. In this paper, we propose a throughput optimization algorithm for LEO satellite‐based IoT networks meanwhile reducing the number of LEO satellite. Based on stochastic geometry theory, a closed‐form expression is derived for the throughput of a dynamic LEO satellite‐based IoT networks when LEO satellite equips with capture effect (CE) receiver and successive interference cancelation (SIC) receiver, respectively. Furthermore, a joint altitude and beamwidth optimization problem is formulated under the constraint of Walker constellation to optimize the throughput and the number of LEO satellites. To solve this multi‐objective optimization problem, we design an iterative non‐dominated sorting genetic algorithm II (NSGA‐II) for the rapid development of IoT traffic. Simulation results show that our proposed algorithm can effectively improve the throughput performance of random access (RA) protocol in LEO satellite‐based IoT networks compared to benchmark problems.

Joint Phase Shift Design and Resource Management for a Non-Orthogonal Multiple Access-Enhanced Internet of Vehicle Assisted by an Intelligent Reflecting Surface-Equipped Unmanned Aerial Vehicle

This paper integrates intelligent reflecting surfaces (IRS) with unmanned aerial vehicles (UAV) to enhance the transmission performance of the Internet of Vehicles (IoV) through non-orthogonal multiple access (NOMA). It focuses on strengthening the signals from cell edge vehicles (CEVs) to the base station by optimizing the wireless propagation environment via an IRS-equipped UAV. The primary goal is to maximize the sum data rate of CEVs while satisfying the constraint of the successive interference cancellation (SIC) decoding threshold. The challenge lies in the non-convex nature of jointly considering the power control, subcarrier allocation, and phase shift design, making the problem difficult to optimally solve. To address this, the problem is decomposed into two independent subproblems, which are then solved iteratively. Specifically, the optimal phase shift design is achieved using the deep deterministic policy gradient (DDPG) algorithm. Furthermore, the graph theory is applied to determine the subcarrier allocation policy and derive a closed-form solution for optimal power control. Finally, the simulation results show that the proposed joint phase shift and resource management scheme significantly enhances the sum data rate compared to the state-of-the-art schemes, thereby demonstrating the benefits of integrating the IRS-equipped UAV into NOMA-enhanced IoV.

Performance evaluation of Non‐Orthogonal multiple access system based on outage probability and power consumption

SummaryIn this growing world, the field of communication is developing quickly. The research community's attention is shifting to the design of networks beyond fifth generation (5G) and the sixth generation (6G) due to the rapid spread of the 5G mobile networks. Due to that, there will be a lot of traffic in the area, which will interfere with the channels and maybe produce noise. Nonorthogonal multiple access (NOMA) contributes to streamlined communication and a decrease in the possibility of interference. The communication will be encoded and decoded from transmitter to receiver utilizing the superposition coding (SC) and successive interference cancelation (SIC) approaches, ensuring the message's secrecy. This paper considers a simultaneous wireless information and power transfer (SWIPT)‐based cooperative NOMA system, where the nearby user to the source node acts as a relay to assist the far user. To further enhance the system performance, an improved golden search optimization (IGSO) is used to determine the best power allocation and power splitting coefficients by decreasing the outage probability. The existing models are compared with the proposed model in the results section regarding outage probability and throughput, where the proposed model outperformed all other existing models.

Deep learning based detection of signal of interest of uplink NOMA multi-users in NOMA In-band Full-duplex Radio communication

The research focuses on investigating the symbol error rate (SER) performance of the Non Orthogonal Multiple Access (NOMA) In-band Full-duplex Radio communication system, which is considered a promising technology for 5G/6G. This system facilitates simultaneous transmission and reception of data over the same resource block for multiple users via power domain multiplexing. However, the system faces a significant challenge in the form of self-interference signal (SI). The SI signal transmitted from the NOMA In-band full-duplex radio transmitting antenna is also received by its own receiving antenna. It limits perfect successive interference cancellation (SIC) for channel estimation and signal detection of the signal of interest (SoI) from uplink NOMA multi-users at the receiver of NOMA In-band Full-duplex radio. Furthermore the SER performance is significantly degraded due to various SI and SoI channel imperfections. To address this, a three-phase-based efficient approach has been proposed for simultaneous non-linear SI cancellation and detection of the SoI from uplink NOMA two users under aforementioned SI and SoI channel imperfections. The approach uses the Least Square-SIC Estimator, Minimum Mean Square Error-SIC Estimator, and deep learning (DL) methods. The reported 4 dB SNR gain compared to least square-SIC/minimum mean square error SIC and DNN-based methods demonstrate the robustness of the proposed DL-aided approach against various SI and SoI channel imperfections for NOMA In-band Full-duplex Radio communication.

Uplink-downlink resource optimization for provisioning 5G application considering SUI fading channel models

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PD-NOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model.

Investigating power scaling factor for pattern division multiple access

Pattern division multiple access (PDMA) is a one type of multi-domain non-orthogonal multiple access (NOMA) that support massive connectivity and can improve spectral efficiency. The unique pattern is used by each user to map its transmitting data into a group of resource, which consist of frequency, code and spatial domain or combination of these resources. Power scaling and phase shifting are used to resolve ambiguity as consequence non uniform distribution of the received combined constellation. In this paper, we propose investigation on power scaling factor for each user in PDMA matrix to increase sum rate transmission and propose combine successive interference cancellation (SIC) based on diversity order and power scaling factor for each user. The simulation results confirm that the proper implement power scaling factor in pattern type 2 show best performance in Rician fading channels.

Downlink Learning-aided Precoding for Cell-Free networks Specially D esigned for beyond 5G Communication System

Objectives: With increase in number of access points in Cell-Free Massive Multiple Input Multiple Output (CFMM) system, spatial complexity of calculating precoding vector increases with traditional precoding schemes. So, to reduce computational complexity, network cost, and run time, a new deep learning -aided precoder is specially designed for CFMM system. The performance of downlink (DL) Cell-Free Massive Multiple Input Multiple Output (CFMM) system operating under Rayleigh fading channel model is analyze using new deep learning-based precoding scheme. Methods: We introduce new deep learning-aided precoder and an improved version of basic scalable pilot assignment algorithm which enhances system performance. We derive closed- form expression for average DL spectral efficiency (SE) for the proposed scheme, which is then compared with Minimum Mean Square Error Successive Interference Cancellation (MMSESIC), Regularized Zero Forcing (RZF), Least Square (LS) and Maximum Ratio (MR) combining techniques. We analyze the proposed scheme with perfect channel state information (CSI), instantaneous CSI, coherent transmission, non-coherent transmission, different pilot configuration. Findings: The spectral efficiency obtained with CFMM-MMSESIC and the proposed scheme is 3 bits/s/Hz, and 2.5bits/s/Hz respectively, which clearly indicates the difference of 20 % only. So, the proposed scheme gives near optimal results, and we can use simple linear combining techniques instead of complex non-linear combining techniques. Also, the proposed scheme with coherent data transmission gives performance curve, which is very close to MMSESIC scheme as desired. The performance of the proposed system is improved by reducing run time and computational complexity as compared to conventional linear precoding schemes. Novelty: The proposed precoder improves performance by reducing run time and computational complexity. Advanced pilot assignment algorithm enhances performance by reducing pilot contamination. Keywords: Cell-Free Massive Multiple Input Multiple Output, Pilot Contamination, Precoding, Minimum Mean Square Error Successive Interference Cancellation, Maximum Ratio, Regularized Zero Forcing (RZF), Least Square (LS)