Search Results (56)

We study UAV-assisted 5G uplink connectivity for disaster response, in which a UAV (unmanned aerial vehicle) acts as an aerial base station to restore service to ground users. We formulate a joint control problem coupling UAV kinematics (bounded acceleration and velocity), per-subchannel uplink power allocation, and uplink non-orthogonal multiple access (UL-NOMA) scheduling with adaptive successive interference cancellation (SIC) under a minimum user-rate constraint. The wireless channel follows 3GPP urban macro (UMa) with probabilistic line of sight/non-line of sight (LoS/NLoS), realistic receiver noise levels and noise figure, and user equipment (UE) transmit-power limits. We propose a bounded-action proximal policy optimization with generalized advantage estimation (PPO-GAE) agent that parameterizes acceleration and power with squashed distributions and enforces feasibility by design. Across four user distributions (clustered, uniform, ring, and edge-heavy) and multiple rate thresholds, our method increases the fraction of users meeting the target rate by 8.2–10.1 percentage points compared to strong baselines (OFDMA with heuristic placement, PSO-based placement/power, and PPO without NOMA) while reducing median UE transmit power by $64.6\%$. The results are averaged over at least five random seeds, with $95\%$ confidence intervals. Ablations isolate the gains from NOMA, adaptive SIC order, and bounded-action parameterization. We discuss robustness to imperfect SIC and CSI errors and release code/configurations to support reproducibility. Full article

This study investigates bit error rate (BER)-constrained power allocation for uplink non-orthogonal multiple access (NOMA) systems in which a base station employs one-bit analog-to-digital converters. Although one-bit quantization significantly reduces hardware costs and receiver power consumption, it also introduces severe nonlinear distortions that degrade detection performance. To address this challenge, a pairwise error probability expression is first derived for the one-bit quantized uplink NOMA model, from which an analytical upper bound on the BER is obtained. Based on this characterization, a fairness-driven max–min power allocation strategy is formulated to minimize the BER of the worst-performing user. A closed-form solution for the optimal power allocation is obtained under binary phase-shift keying (BPSK) signaling. Simulation results verify the tightness of the analytical BER bound and demonstrate that the proposed power allocation scheme provides noticeable BER improvements that compensate for the performance degradation caused by one-bit quantization. Full article

In modern communication systems, packets with different blocklengths often coexist, presenting new challenges for interference management and decoding. In scenarios where short-packet transmissions must meet strict latency and reliability requirements, conventional interference cancellation decoding strategies may be insufficient, especially when coexisting with long-packet services. This work proposes a novel interleaver design for polar codes that enables early decoding in successive interference cancellation (SIC) frameworks. To support this capability, a minimal yet essential modification to the interleaver used in the 5G New Radio (NR) polar coding scheme is introduced. This tailored interleaver facilitates the reliable recovery of short-packet signals before the complete decoding of coexisting long packets, substantially improving early decoding performance. Importantly, the proposed modification retains compatibility with the overall 5G NR polar code structure, ensuring practical implementability. Simulation results demonstrate that our approach yields significantly enhanced decoding accuracy in heterogeneous traffic scenarios representative of next-generation wireless systems. Full article

With the rapid growth of wireless devices, security has become a key research concern in beyond-5G (B5G) and sixth-generation (6G) networks. Non-orthogonal multiple access (NOMA), one of the supporting technologies, is a strong contender to enable massive connectivity, increase spectrum efficiency, and guarantee high-quality access for a sizable user base. Furthermore, the scientific community has recently paid close attention to the effects of hardware impairments (HIs). The safe transmission of NOMA in a two-user uplink relay network is examined in this paper, taking into account both hardware limitations and the existence of listening devices. Each time frame in a mobile network environment comprises two phases in which users use a relay (R) to interact with the base station ($BS$). The research focuses on scenarios where a malicious device attempts to intercept the uplink signals transmitted by users through the R. Using important performance and security metrics, such as connection outage probability (COP), secrecy outage probability (SOP), and intercept probability (IP), system behavior is evaluated. To assess the system’s security and reliability under the proposed framework, closed-form analytical expressions are derived for SOP, IP, and COP. The simulation results provide the following insights: (i) they validate the accuracy of the derived analytical expressions; (ii) the study significantly deepens the understanding of secure NOMA uplink transmission under the influence of HIs across all the network entities, paving the way for future practical implementations; and (iii) the results highlight the superior performance of secure and reliable NOMA uplink systems compared to benchmark orthogonal multiple access (OMA) counterparts when both operate under the same HI conditions. Furthermore, an extended model without a relay is considered for comparison with the proposed relay-assisted scheme. Moreover, the numerical results indicate that the proposed communication model achieves over 90% reliability (with a COP below 0.1) and provides approximately a 30% improvement in SOP compared to conventional OMA-based systems under the same HI conditions. Full article

Future wireless networks are expected to deliver enhanced spectral efficiency while being energy efficient. MIMO and other non-orthogonal transmission schemes, such as non-orthogonal multiple access (NOMA), offer substantial theoretical spectral efficiency gains. However, these gains have yet to translate into practical deployments, largely due to limitations in current signal processing methods. Linear transceiver processing, though widely adopted, fails to fully exploit non-orthogonal transmissions, forcing massive MIMO systems to use a disproportionately large number of RF chains for relatively few streams, increasing power consumption. Non-linear processing can unlock the full potential of non-orthogonal schemes but is hindered by high computational complexity and integration challenges. Moreover, existing message-passing receivers for NOMA depend on specially designed sparse signals, limiting resource allocation flexibility and efficiency. This work presents NL-COMM, an efficient non-linear processing framework that translates the theoretical gains of non-orthogonal transmissions into practical benefits for both the uplink and downlink. NL-COMM delivers over 200% spectral efficiency gains, enables 50% reductions in antennas and RF chains (and thus base station power consumption), and increases concurrently supported users by 450%. In distributed MIMO deployments, the antenna reduction halves fronthaul bandwidth requirements, mitigating a key system bottleneck. Furthermore, NL-COMM offers the flexibility to unlock new NOMA schemes. Finally, we present both hardware and software architectures for NL-COMM that support massively parallel execution, demonstrating how advanced non-linear processing can be realized in practice to meet the demands of next-generation networks. Full article

Non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RISs) are recognized as key technologies for beyond 5G and 6G wireless communications. To address the high computational complexity and non-convex optimization challenges, this letter proposes an optimization framework based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm. The proposed framework jointly makes use of sensor grouping, power allocation, an RIS computation strategy, and phase shifts to minimize the remote state estimation (RSE) error. Simulation results demonstrate that the MADDPG algorithm, when applied in an RIS-assisted NOMA system, significantly reduces the RSE error. Full article

In industrial wireless networks beyond 5G and toward 6G, combining uplink non-orthogonal multiple access (NOMA) with the Kalman filter (KF) effectively reduces interruption risks and transmission delays in remote state estimation. However, the complexity of wireless environments and concurrent multi-sensor transmissions introduce significant interference and latency, impairing the KF’s ability to continuously obtain reliable observations. Meanwhile, existing remote state estimation systems typically rely on oversimplified wireless communication models, unable to adequately handle the dynamics and interference in realistic network scenarios. To address these limitations, this paper formulates a novel dynamic wireless resource allocation problem as a mixed-integer nonlinear programming (MINLP) model. By jointly optimizing sensor grouping and power allocation—considering sensor available power and outage probability constraints—the proposed scheme minimizes both estimation outage and transmission delay. Simulation results demonstrate that, compared to conventional approaches, our method significantly improves transmission reliability and KF estimation performance, thus providing robust technical support for remote state estimation in next-generation industrial wireless networks. Full article

This paper investigated the configuration of the reflecting elements for uplink non-orthogonal multiple access (NOMA) unmanned aerial vehicle (UAV)–reconfigurable intelligent surface (RIS) systems. By analyzing the practical air-to-ground (A2G) channels and phase estimation errors, a closed-form expression for the range of reflecting elements has been formulated to enhance the reliability and security of the system. Considering the energy efficiency of the system, the number of reflecting elements is optimized, aiming to maximize the energy secrecy efficiency (ESE) index under the given constraints. The simulation results verified the correctness of the derivation, which offers theoretical guidance for configuring RISs in uplink NOMA UAV systems with heterogeneous service demands. The uplink NOMA UAV system outperforms traditional terrestrial systems. The results also show that when the number of eavesdroppers increases, the influence of the number of reflecting elements on the system’s ESE becomes more significant. This demonstrates the benefits of equipping UAVs with RISs for the security of multiple eavesdropping systems. Full article

A wireless-powered communication network (WPCN) provides sustainable power solutions for energy-intensive Internet of Things (IoT) devices in remote or inaccessible locations. This technology is particularly beneficial for applications in smart transportation and smart cities. Nevertheless, WPCN experiences performance degradation due to severe path loss and inefficient long-range energy and information transmission. To address the limitation, this paper investigates an intelligent reflecting surface (IRS)-enhanced multi-cell WPCN integrated with non-orthogonal multiple access (NOMA). The emerging IRS technology mitigates propagation losses through precise phase shift adjustments with symmetric reflective components. Asymmetric resource utilization in symmetric downlink and uplink transmissions is crucial for optimal throughput and quality of service. Alternative iterations are employed to optimize time allocation and IRS phase shifts in both downlink and uplink transmissions. This approach allows for the attainment of maximum sum throughput. Specifically, the phase shifts are optimized using two algorithms called semidefinite relaxation (SDR) and block coordinate descent (BCD). Our simulations reveal that integrating the IRS into multi-cell NOMA-WPCN enhances user throughput. This surpasses the performance of traditional multi-cell WPCN. In addition, the coordinated deployment of multiple hybrid access points (HAPs) and IRS equipment can expand communications coverage and network capacity. Full article

The rapid deployment and enhanced communication capabilities of unmanned aerial vehicles (UAVs) have enabled numerous real-time sensing applications. These scenarios often necessitate task offloading and execution under stringent transmission delay constraints, particularly for time-critical applications such as disaster rescue and environmental monitoring. This paper investigates the improvement of MEC-based task offloading services in energy-constrained UAV networks using backscatter communication (BackCom) with non-orthogonal multiple access (BAC-NOMA). The proposed BAC-NOMA protocol allows uplink UAVs to utilize downlink signals for backscattering tasks instead of transmitting through uplink NOMA. A resource allocation problem is formulated, aimed at minimizing offloading delays for uplink users. By converting the initially non-convex problem into a convex one, an iterative algorithm is developed to solve it. Simulation results demonstrate that the proposed protocol significantly reduces offloading delays relative to existing benchmarks. Full article

With the exponential growth of devices, particularly Internet of things (IoT) devices, connecting to wireless networks, existing networks face significant challenges. Spectral efficiency is crucial for uplink, which is the dominant form of asymmetrical network in today’s communication landscape, in large-scale connectivity scenarios. In this paper, an uplink transmission scenario is considered and user equipment (UE) aggregation is employed, wherein some users act as cooperative nodes (CNs), and help to forward received data from other users requiring coverage extension, reliability improvement, and data–rate enhancement. Non–orthogonal multiple access (NOMA) technology is introduced to improve spectral efficiency. To reduce the interference impact to guarantee the data rate, one UE can be assisted by multiple CNs, and these CNs and corresponding assisted UEs are clustered into joint transmission pairs (JTPs). Interference-free transmission can be achieved within each JTP by utilizing different successive interference cancellation (SIC) decoding orders. To explore SIC gains and maximize data rates in NOMA–based UE aggregation, we propose a primary user CN–based channel–sorting algorithm for JTP construction and apply a whale optimization algorithm for JTP power allocation. Additionally, a conflict graph is established among feasible JTPs, and a greedy strategy is employed to find the maximum weighted independent set (MWIS) of the conflict graph for subchannel allocation. Simulation results demonstrate that our joint collaborative NOMA (JC–NOMA) design with two–hop multi–path UE aggregation significantly improves spectral efficiency and capacity under limited spectral resources. Full article

This paper investigates the impacts of element grouping on the covert communication performance of an active reconfigurable intelligent surface (ARIS)-aided uplink non-orthogonal multiple access (NOMA) system. Through element grouping, each element of the ARIS works in either the reflecting mode to reflect the information signal or the jamming mode to generate a jamming signal. Optimizing the NOMA transmit power, ARIS beamforming, and receive beamforming jointly is necessary to maximize the covert communication rate. To tackle the unsolvable covert communication rate maximization problem, we decouple the original problem into three sub-problems of optimizing the NOMA transmit power, ARIS beamforming, and receive beamforming, respectively. To tackle the mixed-integer non-linear programming for the element grouping, we introduce the arithmetic- and geometric-mean-based penalty term and apply the Dinkelbach transform to reformulate the optimization problem. Next, we propose an alternating optimization algorithm to optimize the system parameters. The numerical results demonstrate the effectiveness of the element grouping in improving the covert communication rate. However, the element grouping scheme achieves a lower covert communication rate performance compared to the scheme without element grouping, indicating that using element grouping for covert communications in the ARIS-aided uplink NOMA system is not the preferred option. Full article

Utilizing unmanned aerial vehicles (UAVs) as mobile access points or base stations has emerged as a promising solution to address the excessive traffic demands in wireless networks. This paper investigates improving the detector performance at the unmanned aerial vehicle base stations (UAV-BSs) in an uplink grant-free non-orthogonal multiple access (GF-NOMA) system by considering the activity state (AS) temporal correlation of the different user equipments (UEs) in the time domain. The Bernoulli Gaussian-Markov chain (BG-MC) probability model is used for exploiting both the sparsity and slow change characteristic of the AS of the UE. The GAMP Bernoulli Gaussian-Markov chain (GAMP-BG-MC) algorithm is proposed to improve the detector performance, which can utilize the bidirectional message passing between the neighboring time slots to fully exploit the temporally correlated AS of the UE. Furthermore, the parameters of the BG-MC model can be updated adaptively during the estimation procedure with unknown system statistics. Simulation results show that the proposed algorithm can improve the detection accuracy compared to existing methods while keeping the same order complexity. Full article

Reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) are both highly promising technologies for future communication. Compared with traditional single-RIS-assisted NOMA systems, this paper considered multi-RIS-assisted NOMA uplink communication systems and proposed a sum-rate maximization scheme. At present, most research on RIS-assisted NOMA systems has not considered the joint optimization of users’ power, multi-RIS deployment, and multi-RIS phase shifts. Firstly, this paper proposed a sum-rate problem with multiple variates, which are involved in users’ power, multi-RIS deployments, and multi-RIS phase shifts. This problem is usually very complex and non-convex, which makes it very difficult to obtain an optimal solution. Then, the original problem was decomposed into three sub-problems through several derivations, which are relatively simple and easy to solve. Finally, the optimal multi-RIS deployment locations were obtained by a simulated annealing particle-swarm optimization algorithm, and a suboptimal solution based on positive semidefinite relaxation was adopted to solve the joint optimization problem of users’ power and multi-RIS phase shifts, respectively. The research results indicate that the sum-rate for the considered systems with the multi-RIS optimization algorithm can be improved by about 1 bps/Hz, compared with that of non-optimization, and under the same total number of RIS reflection units as a single-RIS scheme, the performance of the proposed scheme in this paper is superior to the single-RIS scheme, which proves the effectiveness of the proposed algorithm. Full article

This paper considers an uplink wireless powered multichannel internet of things (MC-IoT) system with multiple hybrid relays, each serves a group of wireless-powered IoTDs. For coordinating radio frequency wireless power transfer (RF-WPT) and wireless information transfer (WIT), two cooperative protocols integrating non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA), namely hybrid NOMA-frequency division multiple access (FDMA) and hybrid NOMA-time division multiple access (TDMA), is proposed. For both protocols, we investigate cooperative resource allocation problems and aim to maximize the sum data delivered by all the IoTDs, subject to the peak transmit power constraint and the total consumable energy constraint of the hybrid relays. The problem with the hybrid NOMA-FDMA is first decomposed into two subproblems, one for time and power allocation of each hybrid relay and its associated IoTDs, and the other one for channel allocation among them. After some properties of the optimal solution are discovered and a series of transformations is performed, the former subproblem is solved by the bisection search and the Lagrange duality method, and the latter subproblem is solved by the Kuhn–Munkres algorithm. The problem with the hybrid NOMA-TDMA is first convexified by proper variable transformations and then solved by the Lagrange duality method. We provide extensive simulations to demonstrate the superiority of the proposed schemes. It is shown that various system parameters play key roles in the performance comparison of the two schemes. Full article