Optimization of UAV-assisted uplink transmission based on RSMA

In this paper, we investigate the problem of heterogeneous service coexistence in the scope of 5G and beyond (B5G) networks, where multiple ultra-reliable low-latency communication (URLLC) and enhanced mobile broadband (eMBB) users are connected to a common base station (BS), sharing physical network resources. In contrast to the orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA) usually adopted in literature, in this work we employ rate splitting multiple access (RSMA) for URLLC transmission, where a URLLC device splits its message into two sub-messages with partial transmission power, which are potentially recovered at the BS by means of successive interference cancellation (SIC). To study the performance of such methods in the presence of eMBB users, we consider both orthogonal and non-orthogonal network slicing approaches to share the network resources between heterogeneous user profiles with diverse requirements. As a result, we show that, in general, RSMA presents an improved performance in terms of sum-rate and reliability, even when transmitting concurrently with eMBB users. Finally, our results also show that the URLLC sum-rate can be increased by properly adjusting the rate splitting factor based on the average signal-to-noise ratio (SNR), not being necessary instantaneous channel state information (CSI).

This paper presents a machine learning-based framework for the predictive deployment of unmanned aerial vehicles (UAVs) as flying base stations (BSs) to offload heavy traffic from ground BSs. To account for time-varying traffic distribution, a long short-term memory (LSTM)-based prediction algorithm is introduced to predict future cellular traffic. A joint K-means and expectation maximization (EM) algorithm based on Gaussian mixture models (GMM) is proposed to determine the service area of each UAV based on the predicted user service distribution. Based on the predicted traffic, the optimal positions of UAVs are derived, and four multiple access techniques, namely, rate splitting multiple access (RSMA), frequency domain multiple access (FDMA), time domain multiple access (TDMA), and non-orthogonal multiple access (NOMA), are compared to minimize the total transmit power. Simulation results show that the proposed method can reduce up to 24% of the total power consumption compared to the conventional method without traffic prediction. Furthermore, RSMA is found to require the lowest transmit power among the four multiple access techniques. Therefore, this paper focuses on the comparison of multiple access techniques for UAV deployment, which is essential for the efficient and effective use of UAVs as flying BSs.

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) 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.

Non-Orthogonal Multiple Access (NOMA) is known as one of the promising techniques in the fifth generation of wireless communication. The classification of users in (NOMA) is based on power, while it is based on time, frequency and code in Orthogonal Multiple Access (OMA). In this study the downlink NOMA includes two users, one strong and one weak. The comparison of NOMA and OMA properties shows a range of Power Allocation Factors (PAF) for the two users within which NOMA properties have proved to be better than OMA. It was also shown that the achieved PAF is a function of channel gains of two users. Then, the coverage region is defined for multiple access channel; and by considering the Base Station (BS) as a fixed one in the center of the cell, the coverage region for both NOMA and OMA is calculated. The theoretical and analytical results show that the achieved coverage region of NOMA for both weak and strong users has been increased compared to OMA.

Rate-splitting multiple access (RSMA) has recently gained attention in low earth orbit (LEO) satellite-terrestrial networks (LSTNs), due to its ability to provide high spectral efficiency in the context of constrained energy resources of LEO satellites. However, the impracticality of acquiring perfect real-time channel state information (CSI), due to high satellite mobility and long link delay, poses significant challenges to effective utilization of RSMA in LSTNs. To tackle this challenge, we propose a location-based robust RSMA scheme for downlink data transmission in LSTNs. First, we establish an optimization problem to minimize the power consumption of LEO satellites, while meeting user requirement on the real-time data rate violation probability. Subsequently, we transfer the probability constraints of rate violation probabilities into closed-form inequalities, by utilizing Markov inequality, Jensen’s inequality, and Cauchy-Schwarz inequality. The original problem is then transformed into a Markov decision process (MDP), and a Transformer encoder-based deep reinforcement learning (TDRL) algorithm is proposed to solve the complex problem based on the real-time locations of users and the LEO satellite. Additionally, a multi time-frame location-based training dataset generation method is proposed for the training of TDRL model, considering the mobility of LEO satellite. Simulation results demonstrate that the proposed scheme is effective in guaranteeing the rate violation probability requirement of each user, and RSMA significantly outperforms space division multiple access (SDMA) and non-orthogonal multiple access (NOMA), with TDRL achieving faster convergence than other baselines.

Integrating visible light communication (VLC) with the reconfigurable intelligent surface (RIS) significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to the communication environment. These capabilities strengthen the confidentiality and security of VLC systems. This paper presents a comprehensive study on the joint optimization of VLC access point (AP) power allocation, RIS association, and RIS elements orientation angles for secure VLC systems, while considering rate-splitting multiple access (RSMA) and power-domain non-orthogonal multiple access (NOMA) schemes. Specifically, two frameworks are proposed to maximize both the minimum secrecy rate (SR) and the minimum secrecy energy efficiency (SEE) by jointly optimizing power allocation, RIS association, and RIS elements orientation angles for both power-domain NOMA and RSMA-based VLC systems. The proposed frameworks consider random device orientation and guarantee the minimum user-rate requirement. The proposed optimization frameworks belong to the class of mixed integer nonlinear programming, which has no known feasible solution methodology to guarantee the optimal solution. Moreover, the increased degree of freedom and flexibility from the joint consideration of power control, RIS association and element orientation results in a large set of decision variables and constraints, which further complicates the optimization problem. To that end, we utilize a genetic algorithm-based solution method, which through its exploration and exploitation capabilities can obtain a good quality solution. Additionally, comprehensive simulations show that the RSMA scheme outperforms the power-domain NOMA scheme across both the SR and SEE metrics over various network parameters. Furthermore, useful insights on the impact of minimum user rate requirement, number of RIS elements, and maximum VLC AP transmit power on the minimum SR and SEE performances are provided.

Rate‐splitting multiple access (RSMA) is a promising enabler for improving spectral efficiency, interference management, and user fairness in satellite downlink systems. Yet, most RSMA studies are either tailored to terrestrial settings or rely primarily on numerical optimization, offering limited analytical insight under satellite‐realistic propagation such as shadowing. Motivated by geostationary Earth orbit (GEO) downlink operation, this paper provides a tractable performance analysis of an RSMA‐enabled single‐beam multiuser downlink over shadowed Rician fading. We consider a ‐antenna GEO satellite serving single‐antenna users with maximum‐ratio transmission (MRT)–based precoding and perfect successive interference cancellation (SIC). Closed‐form expressions are derived for the distribution of the effective channel gain, leading to exact and high‐SNR outage probability characterizations. The resulting formulas explicitly reveal the roles of the antenna count (defined as the number of satellite transmit antennas ), shadowed Rician parameters, and RSMA power allocation. Furthermore, the analysis yields simple feasibility conditions that delineate practical operating regions for common/private power splitting. We obtain user and system throughput expressions and identify that the achieved diversity order equals . Monte Carlo simulations validate the analysis and benchmark RSMA against nonorthogonal multiple access (NOMA) under various shadowing levels and power‐allocation settings, highlighting reliability–rate trade‐offs and providing actionable guidance for GEO satellite downlink design.

Rate splitting multiple access (RSMA) is a promising approach that has gained momentous attention in the field of wireless communications. With the increasing demand for higher data rates and reliable connections, traditional multiple access approaches like SDMA, NOMA have limitations in terms of interference management as well as channel state information uncertainty. The effectiveness of the RSMA has been recognized in addressing these limitations and providing improved performance in multi-antenna systems. RSMA ruptures user messages into common as well as private parts – the common part is decoded by all users to mitigate interference while the private part is decoded only by the intended user. This bridges orthogonal and non-orthogonal multiple access schemes. Benefits of RSMA include optimal performance in many scenarios, robustness against imperfect CSIT, lower feedback overhead and complexity compared to alternatives. RSMA has many potential applications in 6G use cases like mMTC, URLLC, V2X, and integrated sensing-communications. Ongoing research is still needed, especially on implementation and standardization. The current study focuses on the notion of rate splitting, the benefits of RSMA, working principle of RSMA, implementation challenges, RSMA's implementation in 5G and beyond, a comparison with other multiple access techniques, as well as its problems and future trends in wireless networks.

Cooperative user relaying (CUR) is emerged as an effective framework for 6G networks to address and improve the coverage, system capacity, and transference reliability, without the limitation of antennas at the transceivers. Based on the principle of CUR, CUR allows some users to receive information from the transmitter and forward them to other users. Rate Splitting Multiple Access (RSMA) currently has been noticed as a promising scheme for the management strategies of interference, the design of multiple access (MA) systems, and optimization of non-orthogonal transmission (non-OT) for 6G networks. Recently, one of the most outstanding schemes and interference strategies for CUR is RSMA. This paper presents a comprehensive tutorial on Cooperative User Relaying with RSMA of wireless network 6G. After analyzing the overview of CUR with RSMA and the cooperative rate-slipping (CRS) scheme, the core challenges of CUR with RSMA will be exploited. Finally, the future directions of CUR with RSMA are defined, aiming to conduct the optimization system of CUR with RSMA into 6G networks.

Mobile communication systems are continuously evolving and the search for new technologies is a never-ending activity in industry and academy. Rate-Splitting Multiple Access (RSMA) is a recent multiple access scheme for multi-antenna wireless networks that enjoys the advantages of both Space Division Multiple Access (SDMA) and non-orthogonal multiple access (NOMA). Considering a multicarrier RSMA-based system, this work studies the user matching, subcarrier assignment and power allocation among subcarriers with the objective of maximizing the weighted sum rate. So as to solve this problem, we propose a two-step solution. In the first part, assuming equal power allocation, we solve the Integer Linear Programming (ILP) problem for the user matching and subcarrier assignment by converting it into a Linear Programming (LP) problem by leveraging the properties of unimodular matrices in problem constraints. In the second part, we optimize the power allocation among subcarriers using a gradient descent method. Simulations results show the impact of the number of subcarriers and number of users in the sum rate, how the weights can be used to ensure user fairness, and the advantages of our proposed solution over benchmarking solutions.

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.

Non-orthogonal multiple access (NOMA) and mmWave are considered to be promising techniques for 5G and beyond cellular network communication systems. While the mmWave band provides a very wide under-utilized bandwidth, NOMA enhances the spectral efficiency compared to orthogonal multiple access (OMA). The combination of these two techniques could be considered as the key solution to the high required data rates in next-generation communication systems. The implementation of NOMA is studied and verified under an ideal condition with perfect knowledge of the channel state information (CSI) at the base station (BS). However, under the practical conditions, the fluctuation of the wireless channel makes perfect CSI unachievable at the BS. Hence, we proposed to use the angle of departure (AoD) as feedback information from UEs to the BS. We assume that, mobile users (UEs) perfectly estimate the channel by detecting the pilot signals. Then, UEs quantize the AoD and feed back to the BS. Finally, the BS uses the AoD to perform user clustering, power allocation and beamforming. To reduce the feedback overhead further, we proposed a user clustering algorithm which uses one-bit feedback to determine the change of the AoD. Numerical results demonstrate that the proposed NOMA system outperforms the conventional orthogonal multiple-access (OMA) system with the same amount of feedback information.

Non-orthogonal multiple access (NOMA) and millimeter wave (mmWave) are two key enabling technologies for the fifth generation (5G) wireless networks. In this paper, we develop a general performance analysis framework for mmWave-NOMA networks with spatially random users taking into account link blockage and directional beamforming. To facilitate NOMA transmission in mmWave networks, we propose an angle-based user pairing strategy. Specifically, the base station first randomly selects one user and then pairs it with the line-of-sight user that has the minimum relative angle difference. NOMA is enabled when the beamwidth of the main lobe created by directional beamforming is not smaller than the angle difference between the paired NOMA users. Tools from stochastic geometry are utilized to derive the coverage probability and the sum rate of the proposed NOMA scheme, where beam misalignment at both the base station and the users is taken into account. Simulations validate the performance analysis and show that the proposed NOMA scheme achieves a larger coverage probability and a higher sum rate than conventional NOMA with distance-based user pairing and orthogonal multiple access.

In this letter, we investigate the performance of Rate-Splitting Multiple Access (RSMA) for an uplink communication system with finite blocklegnth (FBL). Considering a two-user Single-Input Single-Output (SISO) Multiple Access Channel (MAC), we study the impact of blocklength and target rate on the throughput and error probability performance of RSMA where one user message is split. We demonstrate that RSMA can outperform Non-Orthogonal Multiple Access (NOMA) in terms of throughput and error probability performance.