In fog radio access networks (F-RANs), caching popular content at edge fog access points (FAPs) helps alleviate the burden on base stations and backhaul links. To improve signal quality and connectivity, this work integrates cooperative communication and non-orthogonal multiple access (NOMA) into content-centric F-RANs with unreliable backhauls. Specifically, a NOMA-enabled joint transmission scheme is considered, where cache-enabled FAPs are coordinated into clusters to perform non-coherent joint transmission and NOMA, enabling multiplexing signals for multiple users. Under a hybrid caching policy and non-uniform Nakagami-mfading channels, the system performance is analyzed in terms of the successful content delivery probability and outage achievable rate. To optimize FAP coordination, the clustering problem is formulated as a coalitional game, and a low-complexity transfer-based clustering algorithm is designed. Furthermore, a hierarchical hybrid NOMA-based algorithm is developed to enhance multi-user access efficiency. Simulation results demonstrate that: 1) The NOMA-enabled joint transmission scheme allows the FAPs efficiently leverage the cached content to mitigate backhaul unreliability; 2) The NOMA-based design outperforms the orthogonal multiple access-based design by guaranteeing improved signal quality while maintaining the efficiency of multi-user access; 3) The coalitional game-based clustering algorithm effectively manages co-channel interference and improves spectrum utilization.

This paper proposes a novel FL method called FedFNS, which integrates feature norm regularization and statistical aggregation. Specifically, a local model correction strategy is proposed to reduce client bias through incorporating a regularization term into the loss function. To mitigate the negative effects of unreliable communications on global model performance, a statistical weighted aggregation strategy is proposed, which leverages the transmission success probability of each client. The effectiveness of FedFNS is validated through extensive experiments, demonstrating its superiority over several classic FL methods in terms of accuracy.

Reconfigurable intelligent surfaces (RISs), as ar-tificial electromagnetic structures with programmable electro-magnetic characteristics, have the potential to enhance the signals collected by service base stations in multi-cell Internet of things (IoT) networks. This capability improves the information extraction and utilization in communication systems, presenting numerous promising applications in the sixth-generation (6G) communication systems-IoT network environment. This paper proposes an optimization framework for the transmission sum-rate in a multicell, multi-user wireless communication system assisted by RIS. Firstly, establish transmission power allocation constraints for training and data symbols based on the distances of users from the transmitter, along with corresponding sum-rate objective functions. Utilize the multidimensional feature parameters of the RIS and long short-term memory (LSTM) to establish the relationship between user mobility distance and transmission power. Then, based on the obtained power prediction data, calculate the corresponding sum-rate using the previously defined objective functions. The obtained predictions contribute to more accurately assessing future communication environments, thereby aiding in optimizing the performance of communication systems. Simulation results validate the significant potential of LSTM in RIS-assisted multi-user wireless network systems.

Non-orthogonal multiple access (NOMA) has drawn much attention due to its capability in massive connections. It enables various joint designs with advanced technologies, e.g., cooperative transmission and aerial base station (ABS)-assisted networks. In this paper, we consider an efficient NOMA enabled cross-tier joint transmission design. This design jointly applies zero-forcing beamforming and NOMA to realize joint transmission and regular transmission for the users in different tiers. We evaluate the performance of the design under a large-scale clustered ABS-assisted network scenario. Theoretical expressions for the outage probability and area outage spectral efficiency are derived. Numerical results show that, although splitting power may lead to slight degradation for the macro-cell users, the system can still expect a decreased overall outage probability because joint transmission improves the received signal quality for the ABS-tier users. The macro-cell users may not always suffer outage performance degradation since they can keep receiving signals instead of staying idle until the cross-tier joint transmission is suspended as in the orthogonal scheme. Besides, with properly selected NOMA power allocation coefficient, a more reliable communication link can be guaranteed for the macro-cell user, if compared with the conventional orthogonal scheme.

This work proposes the utilization of the quantum approximate optimization algorithm (QAOA) for user pairing in non-orthogonal multiple access (NOMA). By exploiting quantum concepts such as the quantum adiabatic theorem, a user pairing solution was derived that approximates a suboptimal sum rate. Moreover, an improved-QAOA is proposed to further enhance the performance by reducing the number of users in the cluster by dividing it into more clusters. Simulation results have demonstrated that the improved-QAOA yields a higher average achievable sum rate when compared to QAOA, and its solution is closer to the theoretical optimal value obtained by a brute-force enumeration method.

Reconfigurable intelligent surfaces (RISs)-assisted Internet of Things (IoT) networks have attracted a great deal of interest due to the potential contributions to the next generation wireless networks. In this article, an adaptive RIS clustering system with weak channels or obstacles is investigated. Ideally, there is a suitable RIS that adopts the self-organized RIS-assisted (SORA) scheme between a base station (BS) and a user equipment (UE) for reflection transmission. However, due to the nonideal channel scenarios, a single RIS may not be capable of connecting the BS with the UE. To tackle these nonideal cases, we propose a complementary RIS-cluster-assisted (C-RCA) strategy by reflecting signals among clusters to improve the performance of the overall system. The performances of the two strategies in terms of outage probability (OP) and ergodic capacity (EC), derived using approximate closed-form expressions, are analyzed. By increasing the numbers of complementary RISs and the reflecting elements on each RIS simultaneously, these performance metrics as well as the effective throughput and energy efficiency (EE) are evaluated under different signal-to-noise ratios (SNRs). The obtained results demonstrated that, in contrast to the ideal case, the network EE of the proposed C-RCA strategy is higher than the SORA scheme under the larger target spectral efficiency (SE).

Aerial base stations (ABS) provide promising solutions for wireless coverage in adverse scenarios. By jointly designing with cooperative transmission, the system performance can even be boosted. In this paper, we consider an ABS-assisted cooperative system, where multiple ABSs hover around the macro base station (MBS) and relay the downlink signals through non- coherent joint transmission (NC-JT) to the user equipment (UE). Interfering nodes are randomly distributed over the 2D plane. Non-uniform line-of- sight (LoS) channel model is assumed for the desired signal propagation, while the communication links between ground terminals follow a distance related probabilistic LoS and non-line-of-sight (NLoS) channel model. Based on stochastic geometry framework, we derived closed form success probability for the cooperative system. Numerical results verify the accuracy of our expressions and show that jointly transmitting signals from the sky can bring in significant enhancement for the coverage performance of the system.

The use of aerial base stations (ABSs) is gaining attention due to its potentials to provide a flexible wireless coverage in adverse scenarios. Investigations on key performance metrics are desirable to ensure the feasibility of these ABS-assisted networks, especially when they are jointly designed with advanced transmission technologies, e.g., cooperative transmissions and non-orthogonal multiple access (NOMA). In this paper, we consider an ABS-assisted cooperative system with NOMA enabled to boost connectivity ability. It is assumed that multiple ABSs hover around a macro base station to relay downlink signals to user equipments, while interfering nodes are randomly distributed on the ground. We assume a more realistic channel model featured with a distance-related probabilistic line-of-sight and non-line-of-sight propagation, as well as non-identical small-scale fading. We derive the outage probability, and study the impacts of various parameters on the system performance. Numerical results unveil that: 1) The reliability of backhauls plays an important role in the system and determines the outage performance floor. 2) Joint transmissions from the sky can bring in a significant performance enhancement for the system. 3) The NOMA based transmission outperforms the traditional orthogonal multiple access with an improved outage performance, provided a properly selected NOMA power allocation coefficient.

In this paper, we investigate distributed subchannel allocation problem in small cell network (SCN) with non-orthogonal multiple access (NOMA) enhancement. Different from existing studies, we exploit NOMA for the purpose of mitigating aggregate inter-cell and intra-cell interference. The problem is analyzed through a locally cooperative game model, in which information is exchanged only among neighboring small cell base stations (SBSs) instead of all SBSs in the SCN. The existence of Nash equilibrium (NE) is confirmed by proving the formulated game as an exact potential game, which allows the application of best response algorithm to solve the problem locally or globally. It is shown that the aggregate interference can be more efficiently suppressed in the NOMA system, compared with traditional orthogonal multiple access (OMA) system. Furthermore, as the network grows denser, higher percentage of SBSs have the incentive to multiplex users via the NOMA technique, revealing the superiority of NOMA over OMA in future ultra dense network.

Aerial base station (ABS) provides a flexible solution for hotspot scenarios in traditional cellular networks, where macro-cell base stations (MBSs) are challenged by overwhelming short-time traffic demands. However, due to stretched transmission distances from sky, the system performance of this ABS-scheme is sometimes questioned. In this paper, we study the system performance of ABS-assisted networks by tools from stochastic geometry. The two-tier network consisting of MBSs and ABSs is modeled as the superposition of a Poisson point process over the infinite plane and a binomial point process within an overlapped finite circular area. We consider a more general probabilistic line-of-sight and non-line-of-sight propagation model and derive coverage probability as well as area spectral efficiency. Based on the proposed analytical framework, we study the impacts of various parameters and compare the ABS-scheme with a benchmark scheme, in which network densification is realized through deploying additional ground base stations (GBSs). Simulation results unveil that: 1) the height and ABS number should be carefully designed to obtain the optimal performance and 2) when the number of assisting BSs is limited, the ABS-scheme can achieve even better performance than the GBS-scheme, which validates the feasibility of enhancing system performance through ABSs in hotspot scenarios.

The conventional nonorthogonal multiple access (NOMA) strategy has secrecy challenge in coordinated multipoint (CoMP) networks. Under the secrecy considerations, this paper focuses on the security‐based NOMA system, which aims to improve the physical layer security issues of conventional NOMA in the coordinated multipoint (NOMA‐CoMP) networks. The secrecy performance of S‐NOMA in CoMP, that is, the secrecy sum‐rate and the secrecy outage probability, is analysed. In contrast to the conventional NOMA (C‐NOMA), the results show that the proposed S‐NOMA outperforms C‐NOMA in terms of the secrecy outage probability and security‐based effective sum‐rate.

In the past few years, extensive research has focused its attention on interference alignment (IA) methods that are aimed at improving the interference networks potential. However, the channel state information (CSI) precision has a correlation with the functionality of IA. When the CSI is completely outdated then there is a possibility that performance effectiveness and gain of IA could be lost. In the current study, a completely outdated source-to-relay CSI within multi-user network is considered followed with the introduction of a collaborative relay system within such a situation to assist in improvement of the networks freedom levels. By examining various outdated CSI situations at transmitter (CSIT), the trade-off involving relay-aided IA (RIA) alongside non-relay-aided IA (NRIA) is obtained. Additionally, the total RIA rate alongside covariance-supported channel estimator is examined.

The non-orthogonal multiple access (NOMA) is regarded as a promising multiple access technique for 5G network. In this research, comparing with the joint transmission (JT) NOMA in Coordinated Multi-Point (CoMP) system, we propose a novel opportunistic NOMA (ONOMA) scheme, which aims to improve the efficiency of the successive interference cancellation (SIC) decoding in conventional NOMA. Besides, by comparing with the JT-NOMA in CoMP system, the data rate of the ONOMA is shown in the numerical results under the ideal and non-ideal scenarios.