Interference Cancellation Decoding Research Articles

Deep-Reinforcement-Learning-Based NOMA-Aided Slotted ALOHA for LEO Satellite IoT Networks

The low earth orbit (LEO) satellites have received extensive attention as an essential supplement to the terrestrial network for supporting global Internet of Things (IoT) services. Considering the rapid growth of IoT devices and the significant satellite-to-ground latency, proposing low-latency, low-overhead access protocols for LEO satellite IoT systems is challenging. In this paper, we propose a multi-beam random access (RA) framework and deploy the deep reinforcement learning (DRL) algorithm to control the non-orthogonal multiple access (NOMA) aided random access strategy. First, we divide the satellite coverage region into multiple beams and assume that the adjacent beams share parts of regions. Hence, the devices in the sharing region are allowed to transmit packets in two periods allocated for the two beams. Then, packets in multiple beams can be decoded jointly by an inter-slot successive interference cancellation (SIC) decoder. In addition, we consider the heterogeneity among devices and assign different power levels for heterogeneous types of devices, which enables power-domain NOMA and the intra-slot SIC decoder in this system to mitigate the collision resolution. To maximize the average throughput, the deep deterministic policy gradient (DDPG) algorithm is adopted to achieve an online decision to optimize the random access protocol where the packet repetition strategies of devices are adjusted dynamically. The simulation results show that the proposed scheme outperforms the traditional benchmark schemes with significant throughput gain.

Secure beamforming designs for maximizing secrecy sum rate in MISO-NOMA networks

In this paper, the application of Non-Orthogonal Multiple Access (NOMA) is investigated in a multiple-input single-output network consisting of multiple legitimate users and a potential eavesdropper. To support secure transmissions from legitimate users, two NOMA Secrecy Sum Rate Transmit BeamForming (NOMA-SSR-TBF) schemes are proposed to maximise the SSR of a Base Station (BS) with sufficient and insufficient transmit power. For BS with sufficient transmit power, an artificial jamming beamforming design scheme is proposed to disrupt the potential eavesdropping without impacting the legitimate transmissions. In addition, for BS with insufficient transmit power, a modified successive interference cancellation decoding sequence is used to reduce the impact of artificial jamming on legitimate transmissions. More specifically, iterative algorithm for the successive convex approximation are provided to jointly optimise the vectors of transmit beamforming and artificial jamming. Experimental results demonstrate that the proposed NOMA-SSR-TBF schemes outperforms the existing works, such as the maximized artificial jamming power scheme, the maximized artificial jamming power scheme with artificial jamming beamforming design and maximized secrecy sum rate scheme without artificial jamming beamforming design.

Secure wireless communications for STAR‐RIS‐assisted millimetre‐wave NOMA uplink networks

AbstractThis paper explores the potential application of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR‐RIS) in improving the physical layer security (PLS) of millimetre wave (mmWave) non‐orthogonal multiple access (NOMA) uplink communications. In particular, the legitimate users on both sides of STAR‐RIS send confidential information simultaneously to the base station (BS) while keeping it secret from the eavesdroppers near the BS by exploiting the STAR‐RIS to proactively regulate the electromagnetic propagation environment. By jointly designing the transmit power, the active beamforming at the BS, and the reflecting/transmitting coefficients at the STAR‐RIS, the authors' goal is to maximize the minimum secrecy capacity subject to the successive interference cancellation decoding order constraints. Due to the non‐convexity of the formulated problem, an efficient algorithm is proposed by capitalizing on alternating optimization, a penalty‐based approach, successive convex approximation, and semi‐definite relaxation. Firstly, a two‐layer iterative algorithm based on the penalty for the joint beamforming optimization sub‐problem is proposed. Then, the non‐convex problem is transformed into a convex positive semi‐definite programming problem for the transmit power sub‐problem. Numerical simulation results reveal that the STAR‐RIS‐aided system has more tremendous advantages and effectiveness in improving the PLS of mmWave NOMA uplink communication compared with the benchmark schemes.

Energy-Efficient Backscatter-Assisted Coded Cooperative NOMA for B5G Wireless Communications

In this manuscript, we propose an alternating optimization framework to maximize the energy efficiency of a backscatter-enabled cooperative Non-orthogonal multiple access (NOMA) system by optimizing the transmit power of the source, power allocation coefficients (PAC), and power of the relay node under imperfect successive interference cancellation (SIC) decoding. A three-stage low-complexity energy-efficient alternating optimization algorithm is introduced which optimizes the transmit power, PAC, and relay power by considering the quality of service (QoS), power budget, and cooperation constraints. Subsequently, a joint channel coding framework is introduced to enhance the performance of far user which has no direct communication link with the base station (BS) and has bad channel conditions. In the destination node, the far user data is jointly decoded using a Sum-product algorithm (SPA) based joint iterative decoder realized by jointly-designed Quasi-cyclic Low-density parity-check (QC-LDPC) codes. Simulation results evince that the proposed backscatter-enabled cooperative NOMA system outperforms its counterpart by providing an efficient performance in terms of energy efficiency. Also, proposed jointly-designed QC-LDPC codes provide an excellent bit-error-rate (BER) performance by jointly decoding the far user data for considered BSC cooperative NOMA system with only a few decoding iterations.

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

Device-to-device(D2D) communication combined with non-orthogonal multiple access(NOMA) can further improve the quality of service for future communications systems and increase spectrum utilization and connection density in cellular networks. In this paper, an effective power allocation scheme is designed to optimize the performance of a D2D communication system based on NOMA for imperfect Successive Interference Cancellation(SIC) decoding. To solve the non-convexity of the problem due to integer constraints and coupling variables, an alternate optimization algorithm was designed to obtain the optimal solution of each subproblem by Lagrange duality analysis and the sub-gradient descent method. Finally, the numerical simulation results demonstrate the performance advantages of the proposed joint optimization algorithm for channel resource allocation and power control in energy efficiency.

Outage Performance Analysis of RSMA-Aided Semi-Grant-Free Transmission Systems

In this paper, we analyze the outage performance of a rate-splitting multiple access (RSMA)-aided semi-grant-free (SGF) transmission system, in which a grant-based user (GBU) and multiple grant-free users (GFUs) access the base station by sharing the same resource blocks. In the RSMA-aided SGF (RSMA-SGF) transmission system, the GBU and admitted GFU are respectively treated as the primary and secondary users by using the cognitive radio principle. With the aid of RSMA, the admitted GFU’s transmit power allocation, target rate allocation, and successive interference cancellation decoding order are jointly optimized to attain the maximum achievable rate for the admitted GFU, without deteriorating the GBU’s outage performance compared to orthogonal multiple access. Taking into account the extended non-outage zone achieved by rate-splitting, a closed-form expression is derived for the outage probability of the admitted GFU in the considered RSMA-SGF system. Asymptotic analysis for the admitted GFU’s outage probability is also provided. The superior outage performance and full multiuser diversity gain achieved by the RSMA-SGF transmission system are verified by the analytical and simulation results.

Performance comparison of successive interference cancellation decoding order for base station association and power control in small cell networks incorporating handoff optimization

The co-channel interference and frequent handoff are two important issues that have a great impact on the spectrum and energy efficiency in the non-orthogonal multiple access (NOMA) with successive interference cancellation (SIC) in the small cell networks (SCN). This paper investigates the performance of SIC decoding order based on the users’ channel state information (CSI) and random SIC decoding order under the perfect and imperfect conditions for the handoff optimization in SCNs with NOMA. The effect of SIC decoding order in the joint base station association and power control problem is studied by considering the motion of mobile users (MUs). Two optimization problems are formulated using the number of associated MUs, the number of handoffs, and the transmit power of all MUs, under the maximum allowable transmit power and minimum average-rate constraints. Two objectives are combined into a single-stage optimization problem through the weighted sum method. The formulated problem is solved using a game theory-based algorithm and primal decomposition theory. The simulation results show that changing the SIC decoding order can lead to performance improvement in the uplink NOMA- based SCNs. Also, it is shown that the proposed algorithm can significantly reduce the frequent handoffs in small cell networks.

Backscatter Sensors Communication for 6G Low-Powered NOMA-Enabled IoT Networks Under Imperfect SIC

The combination of nonorthogonal multiple access (NOMA) using power-domain with backscatter communication (BC) is expected to connect large-scale Internet of things (IoT) devices in the future sixth-generation era. This article introduces a BC in a multicell IoT network, where a source in each cell transmits a superimposed signal to its associated IoT devices using NOMA. The backscatter sensor tag (BST) also transmits data to IoT devices by reflecting and modulating the superimposed signal of the source. A new optimization framework is provided that simultaneously optimizes the total power of each source, power allocation coefficient of IoT devices, and RC of BST under imperfect successive interference cancellation decoding. This work aims to maximize the total energy efficiency (EE) of the IoT network subject to the quality of services of each IoT device. The problem is first transformed using the Dinkelbach method and then decoupled into two subproblems. The Karush–Kuhn–Tucker conditions and dual Lagrangian method are employed to obtain efficient solutions. In addition, we also calculate the EE of the conventional NOMA network without BC as a benchmark framework. Simulation results unveil the advantage of our considered NOMA BC network over the conventional NOMA network in terms of system total EE.

On the Secrecy Design of STAR-RIS Assisted Uplink NOMA Networks

This paper investigates the secure transmission in a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted uplink non-orthogonal multiple access system, where the legitimate users send confidential signals to the base station by exploiting STAR-RIS to reconfigure the electromagnetic propagation environment proactively. Depending on the availability of the eavesdropping channel state information (CSI), both the full CSI and statistical CSI of the eavesdropper are considered. For the full eavesdropping CSI scenario, we adopt the adaptive-rate wiretap code scheme with the aim of maximizing minimum secrecy capacity subject to the successive interference cancellation decoding order constraints. To proceed, we propose an alternating hybrid beamforming (AHB) algorithm to jointly optimize the receive beamforming, transmit power, and reflection/transmission coefficients. While for the statistical eavesdropping CSI scenario, the constant-rate wiretap code scheme is employed to minimize the maximum secrecy outage probability (SOP) subject to the quality-of-service requirements of legitimate users. Then, we derive the exact SOP expression under the constant-rate coding strategy and develop an extended AHB algorithm for the joint secrecy beamforming design. Simulation results demonstrate the effectiveness of the proposed scheme. Moreover, some useful guidance about the quantification of phase shift/amplitude and the deployment of STAR-RIS is provided.

Intelligent reflecting surface-assisted cognitive radio-inspired rate-splitting multiple access systems

Intelligent reflecting surface (IRS) has been widely regarded as a promising technology for configuring wireless propagation environments. In this paper, we utilize IRS to assist transmission of a secondary user (SU) in a cognitive radio-inspired rate-splitting multiple access (CR-RSMA) system in which a primary user's (PU's) quality of service (QoS) requirements must be guaranteed. Without introducing intolerable interference to deteriorate the PU's outage performance, the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels. For the IRS-assisted CR-RSMA (IRS-CR-RSMA) scheme, we derive the optimal transmit power allocation, target rate allocation, and successive interference cancellation decoding order to enhance the outage performance of the SU. The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived. Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.

Achieving Near Ideal Covertness in NOMA Systems With Channel Inversion Power Control

In this letter, we propose two resource allocation schemes for covert communication in a downlink NOMA system, where the transmitter can send information simultaneously both to the public and the covert receiver, while maintaining ideal (or near-ideal) covertness with respect to the warden. The covert transmission is concealed by combining NOMA and channel inversion power control, acting as a random source of uncertainty at the warden. The transmission scheme supports zero outage transmission to the public user and non-zero outage transmission to the covert user, while guaranteeing an ideal or near-ideal covertness at the warden, depending on whether the covert user employs single-user decoding or successive interference cancellation (SIC) decoding. In the latter case, we determine the optimal power sharing factor between the public and covert signals that maximizes the average covert throughput, given a predefined fixed transmission rate to the public user. If the channel between the transmitter and the covert receiver is moderate or strong, the SIC decoding, compared to the single-user decoding, leads to much higher covert throughput at the cost of minor degradation of covertness.

A new approach of successive interference cancellation decoder in power domain non-orthogonal multiple access transmission

A new approach of successive interference cancellation decoder in power domain non-orthogonal multiple access transmission

Low-complexity hybrid interference cancellation for sparse code multiple access

Sparse Code Multiple Access (SCMA) is one of Non Orthogonal Multiple Access (NOMA) candidates for 5G, the fifth generation mobile network. Multiple overlapped blocks of SCMA code are transmitted per frequency layer which compels the receiver to cancel unwanted SCMA code blocks. Thanks to the sparsity of SCMA, Message Passing Algorithm (MPA) achieves near-optimal performance. Nevertheless, this process is time-consuming and has a high degree of complexity even if Max-Log Algorithm is used. The major contribution of this paper is to propose a new decoding scheme called Hybrid Interference Cancellation (HIC) to reduce time processing without degrading a target Bit Error Rate (BER). The HIC decodes and removes the strongest user, reducing the complexity of Log Domain MPA decoding of remaining users, followed by a Low Density Parity Code (LDPC) decoder. The interference cancellation decoder is either a hard interference cancellation or a soft interference cancellation. The originality of the paper is to calculate a threshold value based on power measurements to decide whether hard decoder or soft decoder should be used to reach the BER target with a lower complexity. Results show a significant reduction in terms of complexity as compared to the traditional MPA process for the same values of BER.

Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks

The integration of Ambient Backscatter Communication (AmBC) with Non-Orthogonal Multiple Access (NOMA) is expected to support connectivity of low-powered Internet-of-Vehicles (IoVs) in the upcoming Sixth-Generation (6G) transportation systems. This paper proposes an energy-efficient resource allocation framework for the AmBC-enabled NOMA IoV network under imperfect Successive Interference Cancellation (SIC) decoding. In particular, multiple Road-Side Units (RSUs) transmit superimposed signals to their associated IoVs utilizing downlink NOMA transmission. Meanwhile, the Backscatter Tags (BackTags) also transmit data symbols towards nearby IoVs by reflecting the superimposed signals of RSUs. Thus, the objective is to maximize the total energy efficiency of the NOMA IoV network subject to the minimum data rate of all IoVs. A joint problem that simultaneously optimizes the total power budget of each RSU, power allocation coefficient of IoVs and reflection power of BackTags under imperfect SIC decoding is formulated. A Dinkelbach approach is first adopted to transform the optimization problem and then the transformed problem is decoupled into two subproblems for optimal transmit power at RSUs and efficient reflection power at BackTags, respectively. To solve the problems efficiently, dual theory and Karush-Kuhn-Tucker conditions are exploited, where the Lagrangian dual variables are iteratively calculated using the subgradient method. To check the performance of the proposed framework, a benchmark optimization without AmBC is also provided. Numerical results demonstrate the superiority of the proposed AmBC-enabled NOMA IoV framework over the benchmark conventional IoV framework.

Successive Interference Cancellation Decoding With Adaptable Decision Regions for NOMA Schemes

In this work, we propose adaptable decision regions in the successive interference cancellation (SIC) decoder for the three-user uplink/downlink non-orthogonal multiple access (NOMA) scheme by exploiting the knowledge of the channel gains. We present scenarios in which the modified SIC decoder outperforms the traditional one and is able to replicate the performance achieved by a deep learning-based decoder. We present analytical symbol error rate (SER) expressions for the three users, compare them to simulation results, and discuss possible consequences of our analysis, such as the optimal power allocation. We also employ heatmaps to analyze the joint influence on the SER of some system parameters, such as signal-to-noise ratio and channel gains.

Performance Analysis of MIMO-NOMA Iterative Receivers for Massive Connectivity

The Fifth Generation (5G) of wireless networks introduced support to Machine-Type Communications (MTC), which is the wireless connectivity solution for Internet of Things (IoT) applications. MTC is split into two different categories: massive MTC (mMTC) and critical MTC (cMTC). Current 5G standards and technologies are not capable of fully satisfying the requirements of both mMTC and cMTC use cases, thus industry and academia have already started developing solutions for MTC in beyond-5G and 6G networks. In some mMTC use cases, receivers might not be equipped with a large number of antennas owing to cost, size or power limitations, thus the number of active devices in a time slot may surpass the number of antennas. Due to the limited spatial multiplexing capabilities, only multi-antenna techniques are not enough to provide connectivity to a massive number of devices in such scenarios. In this paper, we propose and evaluate the performance of iterative linear receivers that can address this issue. By combining Multiple-Input Multiple-Output (MIMO) techniques with Non-Orthogonal Multiple Access (NOMA) exploiting Successive Interference Cancellation (SIC) or Parallel Interference Cancellation (PIC) decoding, the proposed novel receivers are capable of performing dynamic ordering SIC/PIC decoding of multiple overlapping signals even when the number of active devices surpasses that of receive antennas. The performance of the receivers is studied in terms of outage probability and computational complexity. Simulation results show that, among all the receivers studied in this paper, the PIC-based Minimum Mean Square Error (MMSE) receiver presents the best performance while at the same time reducing the number of complex signal operations such as matrix inversions.

Efficient Resource Allocation for Wireless-Powered MIMO-NOMA Communications

Wireless-powered communication (WPC) is a promising technology for varied smart network applications in the industrial, commercial, and security sectors. It employs a large number of connected low-powered user equipments (UEs) in which the harvested energy from electromagnetic radiations is used for signal transmission. However, efficient resource allocation schemes are still required to optimize the performance of WPC networks over limited power and spectrum environments. In this paper, a new approach of wireless-powered multiple-input multiple-output non-orthogonal multiple access (WP-MIMO-NOMA) is designed by employing harvest-then-transmit protocol with joint time-split and power control (TS-PC) techniques to optimize the network performance and lifetime with affordable complexity. We derive the sum rate, UEs’ rates, and rate region expressions based on power-domain NOMA and successive interference cancellation (SIC) decoding. An optimal joint TS-PC (OJTS-PC) scheme is proposed to maximize the network sum rate with enhanced user-fairness under constrained harvested energy level, uplink transmit power, and minimum UE’s rate. Besides, a near-optimal greedy TS-PC (GTS-PC) algorithm is designed to reduce computational efforts significantly. For comparison, we derive the rate expressions for the reference WP-MIMO-OMA system based on orthogonal frequency-division multiple access (OFDMA) and time-division multiple access (TDMA). Numerical results validate the effectiveness of proposed resource allocation schemes in terms of realized sum rate, UE’s rate, and user-fairness without scarifying the limited power of far UEs. This will prolong the lifetime of WPC networks operating over constrained power and bandwidth resources.

Backscatter-Enabled NOMA for Future 6G Systems: A New Optimization Framework Under Imperfect SIC

This letter proposes a new optimization framework for power-domain non-orthogonal multiple access (PD-NOMA) ambient backscatter communication (AmBC) system with imperfect successive interference cancellation (SIC) decoding. In particular, we jointly optimize the transmit power of the source and the reflection coefficient of the backscatter tag to enhance the sum-rate of the system. Closed-form solutions are derived for the considered joint optimization problem via iteratively computing the Lagrange multipliers by the sub-gradient method. Simulation results validate the superiority of the proposed joint optimization framework over other benchmark frameworks, namely suboptimal PD-NOMA AmBC, optimal pure PD-NOMA, and orthogonal multiple access.

Proactive Eavesdropping of Suspicious Non-Orthogonal Multiple Access Networks

In this correspondence, legitimate surveillance of a downlink suspicious non-orthogonal multiple access (NOMA) network with multiple groups of suspicious users (SUs), in the presence of a full-duplex monitor equipped with a successive interference cancellation (SIC) decoder, is investigated. Proactive eavesdropping is adopted, i.e., the monitor simultaneously eavesdrops the suspicious communications, and sends jamming signals. The problem of maximizing the number of successfully eavesdropped SUs by jointly optimizing the jamming power allocation and the decoding order at the monitor is investigated considering both imperfect full-duplex self-interference cancellation, and imperfect SIC. By exploring the particular problem structure, a heuristic iterative algorithm is proposed, where the optimal decoding at the monitor is proved to be equal to that at the SUs. Extensive simulations confirm that the proposed algorithm achieves performance very close to the optimal one but with significantly lower complexity, and outperforms various benchmark algorithms.

Partial Non-Orthogonal Multiple Access (NOMA) in Downlink Poisson Networks

Non-orthogonal multiple access (NOMA) allows users sharing a resource-block to efficiently reuse spectrum and improve cell sum rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {R}_{\mathrm{ tot}}$ </tex-math></inline-formula> at the expense of increased interference. Orthogonal multiple access (OMA), on the other hand, guarantees higher coverage. We introduce partial-NOMA in a large two-user downlink network to provide both throughput and reliability. The associated partial overlap controls interference while still offering spectrum reuse. The nature of the partial overlap also allows us to employ receive-filtering to further suppress interference. For signal decoding in our partial-NOMA setup, we propose a new technique called flexible successive interference cancellation (FSIC) decoding. We plot the rate region abstraction and compare with OMA and NOMA. We formulate a problem to maximize <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {R}_{\mathrm{ tot}}$ </tex-math></inline-formula> constrained to a minimum throughput requirement for each user and propose an algorithm to find a feasible resource allocation efficiently. Our results show that partial-NOMA allows greater flexibility in terms of performance. Partial-NOMA can also serve users that NOMA cannot. We also show that with appropriate parameter selection and resource allocation, partial-NOMA can outperform NOMA.