Secure and Green RSMA-Assisted Heterogeneous ISAC

Rate-splitting multiple access (RSMA) is a key technology for next-generation multiple access systems due to its robustness against imperfect channel state information (CSI). This makes RSMA particularly suitable for high-mobility autonomous driving, where ultra-reliable and low-latency communication (URLLC) is essential. To address the stringent requirements, this study enables RSMA finite blocklength (FBL) transmissions and explicitly evaluates the ergodic performance. We derive the closed-form lower bound for the ergodic sum-rate of RSMA, considering vital factors such as the vehicle velocities, vehicle positions, power allocation of each stream, blocklengths, and block error rates (BLERs). To further enhance the ergodic sum-rate while complying with quality of service (QoS) rate constraints, we jointly optimize the global power coefficient, private power distribution, and common rate splitting. Guided by gradient descent, we first adjust the global power coefficient based on its sum-rate solution. This parameter regulates the power state of the common stream, allowing for dynamic activation or deactivation: if active, we optimize the private power distribution and adjust the common rate splitting to meet minimum transmission constraints; if inactive, we use the sequential quadratic programming for private power distribution optimization. Simulation results confirm that our RSMA scheme significantly improves the ergodic performance, reduces blocklength and BLER, surpassing the RSMA counterpart with average private power and space division multiple access (SDMA). Furthermore, our approach is validated to guarantee the rates for users with the poorest channel conditions, thereby enhancing fairness across the network.

Rate-Splitting Multiple Access (RSMA) has recently appeared as a powerful and robust multiple access and interference management strategy for downlink Multi-user (MU) multi-antenna communications. In this work, we study the precoder design problem for RSMA scheme in downlink MU systems with both perfect and imperfect Channel State Information at the Transmitter (CSIT) and assess the role and benefits of transmitting multiple common streams. Unlike existing works which have considered single-antenna receivers (Multiple-Input Single-Output–MISO), we propose and extend the RSMA framework for multi-antenna receivers (Multiple-Input Multiple-Output–MIMO) and formulate the precoder optimization problem with the aim of maximizing the Weighted Ergodic Sum-Rate (WESR). Precoder optimization is solved using Sample Average Approximation (SAA) together with the proposed vectorization and Weighted Minimum Mean Square Error (WMMSE) based approach. Achievable sum-Degree of Freedom (DoF) of RSMA is derived for the proposed framework as an increasing function of the number of transmitted common and private streams, which is further validated by the Ergodic Sum Rate (ESR) performance using Monte Carlo simulations. Conventional MU–MIMO based on linear precoders and Non-Orthogonal Multiple Access (NOMA) schemes are considered as baselines. Numerical results show that with imperfect CSIT, the sum-DoF and ESR performance of RSMA is superior to those of the two baselines, and is increasing with the number of transmitted common streams. Moreover, by better managing the interference, RSMA not only has significant ESR gains over baseline schemes but is more robust to CSIT inaccuracies, network loads and user deployments.

Rate-splitting multiple access (RSMA) and the intelligent reflecting surface (IRS) are novel technologies to improve spectrum and energy efficiencies in multi-antenna networks. In this paper, we investigate a multi-user multiple-input single-output (MISO) simultaneous wireless information and power transfer (SWIPT) system assisted with an IRS and using RSMA. In particular, the IRS assists with data and energy transmission from the base station (BS) to power-splitting (PS) users under a non-linear energy harvesting (EH) model. Our objective is to minimize the transmission power subject to rate and EH requirements at the users. To solve the non-convex problem, we propose a bilevel programming problem in which a genetic algorithm is used to solve the outer optimization problem, and the inner optimization problem is addressed with the semidefinite relaxation (SDR) method. In addition, to study a practical scenario of imperfect channel state information (CSI), we consider a robust beamforming design based on imperfect cascade channels at the BS. Then, we propose a solution based on the S-procedure with the SDR technique. Simulation results show that our proposed RSMA-based scheme provides a significant reduction in transmission power compared to the space-division multiple access (SDMA) and non-orthogonal multiple access (NOMA) methods under perfect and imperfect CSI.

Rate-splitting multiple access (RSMA) is acknowledged as a promising solution for improving the capacity of dense downlink networks designed to meet the severe criteria of networks beyond 5G, in which a large number of users may be simultaneously supplied by a single bandwidth spectrum. Numerous studies have focused on establishing acceptable RSMA solutions for energy optimization measures like energy efficiency (EE) and weighted power consumption of all users under the acceptance of perfect or imperfect channel state information at transmitter (CSIT). This evaluation focuses on the technical features of newly published papers and their relevance in a variety of situations. We also cover the difficulties and unresolved concerns of RSMA applications in future heterogeneous downlink networks.

In this paper, we study the robust and fair transmission design for a rate splitting multiple access (RSMA)-based multi-user multiple-input single-output (MU-MISO) probabilistic secrecy communication system, where the statistic distribution of estimation errors of eavesdropping channels is available at the transmitter. Our robust resource allocation design aims to maximize the minimum achievable outage constrained (OC) secrecy rate among multiple single-antenna legitimated users (LUs) via optimizing the beamforming vectors and the artificial noise (AN) matrix at the transmitter. To this end, the algorithm design is formulated as a non-convex probabilistic optimization problem which takes into account the maximum transmit power budget. To address the intractability of the optimization problem, the successive convex approximation (SCA) technique and the alternating optimization (AO) approach are exploited to design a suboptimal iterative algorithm for obtaining a locally optimal solution of the considered problem. Simulation results demonstrate that the minimum achievable OC secrecy rate performance of our proposed RSMA-based probabilistic secure transmission system outperforms that of several baseline schemes.

Massive connections of diverse mission-critical devices have sparked people’s envisioning for next-generation ultra-reliable and low-latency communications (xURLLC), prompting the design of customized next-generation advanced transceivers (NGAT). Rate-splitting multiple access (RSMA) has emerged as a pivotal technology for NGAT design, given its robustness to imperfect channel state information (CSI) and resilience to quality of service (QoS). Additionally, xURLLC urgently necessitates large-scale access techniques, thus massive multiple-input multiple-output (mMIMO) is anticipated to integrate with RSMA to enhance xURLLC. In this paper, we develop an innovative RSMA-assisted massive-MIMO xURLLC (RSMA-mMIMO-xURLLC) framework tailored to accommodate xURLLC’s critical QoS constraints in finite blocklength (FBL) regimes. Leveraging uplink pilot training under imperfect CSI at the transmitter, we estimate channel gains and customize linear precoders for efficient downlink short-packet data transmission. Subsequently, we formulate a joint rate-splitting, beamforming, and transmit antenna selection optimization problem to maximize the total effective transmission rate (ETR). Addressing this multi-variable coupled non-convex problem, we decompose it into three corresponding subproblems and propose a low-complexity alternating optimization algorithm for efficient optimization. Extensive simulations demonstrate that compared with non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), the developed architecture accommodates larger-scale access and improves total ETR by 15.3% and 41.91%, respectively.

In this paper, we investigate the ergodic performance of rate-splitting multiple access (RSMA) with finite blocklength (FBL) in high mobility communication systems to meet the ultra-reliable and low-latency (URLLC) requirements. Considering the imperfect channel state information at the transmitter (CSIT) originating from the high mobility of vehicles and the time delay of channel feedback, we analyze the statistical properties of signal-to-interference-plus-noise ratios (SINRs) for common and private streams at the desired vehicle. Next, we derive the closed-form expression for the ergodic sum-rate in FBL RSMA systems considering an arbitrary number of transmit antennas, number of vehicles, vehicle speeds, blocklengths, and block error rates (BLERs). Compared to other benchmarks, such as FBL non-orthogonal multiple access (NOMA) and space division multiple access (SDMA), the proposed scheme holds its optimum performance to meet the stringent BLER requirement while maintaining a prominent reduction in blocklength.

Unmanned aerial vehicles (UAVs) have been applied to various tasks in the low-altitude economy (LAE) with the advantages of high mobility, low costs, and flexible deployment. However, due to the broadcast nature of wireless channels and the increasing number of UAVs, the security of UAV control information and the spectrum resource utilization face significant challenges and threats. Therefore, in this paper, we investigate the secrecy performance of UAV short-packet control information transmission networks based on rate-splitting multiple access (RSMA) with the presence of multiple eavesdroppers. Moreover, we consider and analyze the impacts of both imperfect channel state information (CSI) and successive interference cancellation (SIC) in a more realistic scenario. Considering both large-scale fading and Nakagami-<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> small-scale fading, the closed-form expression of the average effective secrecy sum rate is derived utilizing stochastic geometry and the Gauss-Chebyshev quadrature. Considering that the private stream can be concealed within the high-power common stream, an optimization problem is formulated to maximize the common rate by jointly optimizing the blocklength and power allocation coefficients to enhance security. The block coordinate descent (BCD) algorithm is adopted to solve this problem. Finally, simulation results demonstrate the accuracy of the analysis and the effectiveness of the proposed scheme.

Integrating intelligent reflecting surface (IRS) and rate-splitting multiple access (RSMA) are effective technologies to improve the spectral/energy efficiency in next-generation (beyond 5G(B5G) and 6G) wireless networks. In this paper, we investigate a rate-splitting (RS)-based transmission technique for an IRS-aided communication network involving both near and cell-edge users. In particular, we derive a new architecture called IRS-RS that leverages the interplay between RS and IRS, with an aim to maximize the weighted sum-rate (WSR) of users by selecting the reflecting coefficients at the IRS and designing beamformers at the BS under the constraints of power at the base station (BS), quality of service (QoS) at each user and finite resolution at the IRS. To solve the non-convex WSR maximization problem, we propose an alternating algorithm and compare its performance with baseline non-orthogonal multiple access (NOMA) based transmission for an IRS-aided communication network for both perfect and imperfect channel state information (CSI) cases. Through numerical results, it is shown that the proposed IRS-RS architecture yields better QoS with respect to the cell-edge users when compared to an IRS-NOMA transmission scheme.

Efficient resource allocation is essential in visible light communication (VLC) systems. This study explores the use of optical intelligent reflecting surfaces (OIRS) to enhance the data rate and overall power efficiency of VLC systems under imperfect channel state information (IPCSI), leveraging rate-splitting multiple access (RSMA) for efficient interference management. To this end, we introduce a multi-objective optimization framework to explore the fundamental trade-off between maximizing effective rate and minimizing effective power. In contrast to conventional energy efficiency (EE) approaches, the proposed framework offers flexible system design by allowing the relative importance of rate and power objectives to be adjusted through the reward function. Additionally, it encourages fair resource allocation by penalizing imbalanced rate and power distributions among receivers. We propose a robust resource allocation framework based on the critical actor asynchronous meta-advantage (MA3C) reinforcement learning (RL) algorithm. Simulation results demonstrate substantial robustness to IPCSI via MA3C. Additionally, the integration of RSMA significantly boosts the total data rate and reduces total power, outperforming other benchmarks.

The non-terrestrial networks (NTNs) are recognized as a key component to provide cost-effective and high-capacity ubiquitous connectivity in the future wireless communications. To improve the spectral efficiency in NTNs, rate-splitting multiple access (RSMA) has attracted considerable attention. Nevertheless, the major issue of the considered system is to overcome security hurdles. In this paper, a robust secure precoding transmission scheme based on RSMA is proposed, which is the first time being used for high-altitude platform (HAP)- assisted satellite NTNs. The system features a low-earth orbit satellite that serves multiple ground user equipments (GUEs) using a rate-splitting strategy, while a decode-and-forward HAP relay assists the satellite in establishing communication links with the GUEs. Assuming imperfect channel state information, we formulate an optimization problem to maximize the sum secrecy rate (SSR) of GUEs. The problem jointly optimizes the precoding vectors for both the satellite and the HAP relay, subject to constraints on their maximum transmit powers and the achievable secrecy rates for each GUE. Subsequently, leveraging successive convex approximation and semidefinite relaxation, we present an approach to transform the non-convex constraints into convex ones, enabling the precoding vectors to be obtained through an iterative procedure. Simulation results show that the RSMA can achieve SSR of up to 3.25 bps/Hz and 3.75 bps/Hz compared to non-orthogonal multiple access and time division multiple access, respectively

Rate-splitting multiple access (RSMA) has been proposed as a flexible multiple access scheme for improving interference management in sixth-generation (6G) networks. In particular, the low latency facilitated by RSMA and its robustness against user mobility and imperfect channel state information make it an ideal candidate for the ultra-reliable and low-latency (URLLC) use case in 6G networks. However, since the common message in RSMA needs to be decoded by all the users, the achievable rate of the common message is determined by the user with the poorest channel quality. To overcome this bottleneck, an active intelligent reflecting surface (IRS) can be deployed to enhance the achievable rate of the common stream. However, this comes at the expense of additional power consumption due to the active IRS. In this paper, we consider an active IRS-aided RSMA-based downlink URLLC system and study the resource allocation design for minimization of the power consumption of the base station and the active IRS under quality-of-service constraints for the URLLC users. Our simulation results reveal that active IRSs yield a lower overall power consumption and require a smaller surface size compared to passive IRSs in RSMA-based URLLC systems. Moreover, we show that active IRS-aided RSMA systems consume less power than active IRS-aided space division multiple access (SDMA) systems.

The integration of non-orthogonal multiple access (NOMA) in vehicle-to-everything (V2X) communications has recently shown great potential to improve traffic efficiency, control, and reliability of beyond 5G transportation systems. In V2X communications, it is vital to inspect imperfect channel state information (CSI) because the high mobility of vehicles leads to more channel estimation uncertainties. This paper proposes an energy-efficient power allocation scheme for the road-side unit (RSU) assisted NOMA multicasting in beyond 5G cellular V2X networks. In particular, the energy efficiency maximization problem is investigated under the outage probability of vehicles under imperfect CSI, quality of services (QoS), and power limit constraints. Since the problem is non-convex and difficult to solve directly, we first convert outage probability constraint to non-probabilistic constraint through approximation and adopt a low complexity gradient assisted binary search (GABS) method to obtain the efficient power allocation at RSUs. Then, a successive convex approximation (SCA) technique is exploited to transform the power allocation problem of vehicles associated with each RSU into a tractable concave-convex fractional programming (CCFP) problem. The optimal solution to the CCFP problem is achieved through Dinkelbach and the dual decomposition method. The global optimal power allocation through the GABS-Exhaustive scheme act as a benchmark, which has considerable computational complexity. Simulation results unveil that the proposed suboptimal scheme (GABS-Dinkelbach) can achieve near-optimal performance with very low complexity.

This paper investigates rate-splitting multiple access (RSMA) networks assisted by aerial intelligent reflecting surfaces (AIRS) and assuming a downlink multiple-input single-output (MISO) scenario (AIRS-RSMA) with imperfect successive interference cancelation (SIC). An optimization problem is formulated in order to maximize the total achievable rate by optimizing the transmit beamforming and common achievable rate of the users. By using approximation and transformation techniques, we convert the optimization problem into a semi-definite program (SDP) problem. To solve this problem, an algorithm based on alternating optimization (AO) is proposed to iteratively solve the transmit beamforming problem. Simulation results are provided to demonstrate the efficiency of the proposed method, in which it is revealed that the performance gains in terms of sum-rate of AIRS-RSMA networks with robust beamforming are significantly greater than the non-optimized AIRS-RSMA and conventional non-orthogonal multiple access (NOMA) schemes.

In cognitive relay networks, the interferences from secondary users (SUs) and relays to primary users are constrained to be lower than a threshold. The interference constraints are difficult to satisfy when the channel state information (CSI) is imperfect. In this paper, we propose a robust beamforming scheme for the multi-antenna non-regenerative cognitive relay network where the multi-antenna relay with imperfect CSIs helps the communication of single-antenna SU. Our objective is to design a robust beamforming scheme which maximizes the system capacity subject to transmit power constraint and interference constraints. The bounded channel uncertainties are modeled using the worst-case model. The robust beamforming problem, neglecting the correlation of channel uncertainties, is reformulated as a convex semidefinite programming (SDP) by rank-one relaxation. This convex SDP is related with the worst-case relay transmit power minimization problem, which is further reformulated as a convex SDP, whose rank-one solution is proved to exist. Thus, we propose the suboptimal solution to the robust beamforming problem which is found effectively by solving two convex SDPs. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.