Integrated sensing and communication (ISAC) technology is a key enabler for 6G Internet of Things (IoT) networks due to its efficient spectrum utilization and functional integration. By leveraging reconfigurable intelligent surfaces (RIS), ISAC systems can dynamically manipulate propagation environments, enhance signal quality and coverage in complicated scenarios, particularly for unmanned aerial vehicle (UAV) networks. This paper proposes a novel framework for jointly optimizing trajectory and beamforming in RIS-aided ISAC systems, where the downlink non-orthogonal multiple access (NOMA)-enabled UAV network is considered. The framework aims to maximize the average achievable rate (AAR) by jointly optimizing UAV trajectory, base station (BS) beamforming, and RIS phase shifts, under communication and sensing constraints. The maximization problem is decomposed into three subproblems, i.e., BS beamforming optimization, RIS phase shift and UAV trajectory design. Successive interference cancellation (SIC) is employed to transform the first two subproblems into semidefinite programming (SDP) problems, and the non-convex trajectory optimization is addressed by using the successive convex approximation (SCA) method. Numerical results demonstrate that the proposed RIS-UAV-assisted system significantly outperforms traditional ISAC schemes in terms of communication and sensing efficiency. Simulation results also reveal the superiorities of the joint optimization algorithm compared to its counterparts.

Blockage effects can dramatically deteriorate high frequency cellular network performance. One practical solution is to apply macro-diversity technique, where the user associates with more than one Base Station (BS), to improve the chance of Light-Of-Sight (LOS) link availability. However, how the correlations are brought by both blockages and cooperative BSs is still unclear due to the analytical complexity. In addition, these two kinds of correlations are highly coupled and further impact macro-diversity gain. On basis of the cascade blockage model, this paper proposes a new functional framework to evaluate macro-diversity gains from the perspective of a typical user subjected to three metrics: joint LOS probability, conditional LOS probability and coverage probability. We first derive a set of tractable functional equations to describe three performance metrics. Then corresponding iterative algorithms that can be solved efficiently are designed respectively for three metrics. This analytical framework gains insight into contradictory requirements for macro-diversity, which not only guide the usage of Coordinated MultiPoint (CoMP) in realistic environments, but also determine the beamforming usage in mmWave band. We demonstrate the feasibility and flexibility of this functional framework by a simplified joint transmission example.

We consider a robust energy-efficient reconfigurable intelligent surface (RIS)-aided multi-antenna decode-and-forward (DF) relay cooperative multiple-input multiple-output (MIMO). Although RIS and relay share some similarities in common, they have fundamental differences and can indeed complement each other. Due to the passive characteristic of RIS, it is much challenging to obtain the perfect channel state information (CSI) and the channel estimation error (CEE) is inevitable in practice. Taking into account the imperfect CSI, we formulate the robust energy efficiency (EE) optimization problems under the bounded CEE and statistical CEE models, where the precoding matrices at the source and relay, and the passive beamforming at the RIS in two slots are jointly designed. At first, the original problems under two CEE models are transformed into deterministic forms with the help of S-procedure and Bernstein-type Inequality, respectively. Subsequently, the reformulated problems are solved by the alternating optimization (AO)-based Dinkelbach algorithm in an iterative manner. Particularly, for the passive beamforming subproblem, the semi-definite relaxation (SDR) method and penalty concave-convex procedure (PCCP) method are utilized to deal with the rank-one constraint. Numerical simulations demonstrate that the EE performance of the considered scheme obviously outperforms the benchmarks. Simulation results also show the superiorities of the robust EE optimization compared with the non-robust optimization.

Massive multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), and millimeter-wave (mmWave) are key technologies in the upcoming beyond fifth generation (B5G)/sixth generation (6G) era. As mmWave massive MIMO will likely use hybrid beamforming (HBF) to reduce radio frequency (RF) chains without an obvious performance loss to fulfill the urgent requirement for immense connectivity and huge throughput, it is necessary to integrate mmWave massive MIMO-NOMA with HBF structure. This work devises a novel structure for uplink mmWave massive MIMO-HBF-NOMA system based on group-level successive interference cancellation (GSIC), aiming at maximizing the spectrum efficiency (SE) of the whole system. In our paradigm, users are grouped in terms of channel gain. Space division multiple access (SDMA) is deployed between users in the same group, while NOMA is applied among different groups. The analog beamforming vectors are selected through beam sweeping. An iterative algorithm is proposed to optimize the power allocation and the digital beamforming matrix. Therein, a quadratic transform (QT) algorithm is introduced to solve the power allocation and zero forcing (ZF) method is invoked to obtain the digital beamformer. According to the simulation, the novel GSIC-based structure outperforms the benchmark clustering-based successive interference cancellation (SIC) schemes in SE and energy efficiency (EE) measurably.

To accommodate the stringent requirements of massive connectivity and ultra-high throughput, both reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) have been perceived as the key techniques for future communication networks. In this paper, a versatile framework is conceived to boost transmit power efficiency for RIS-enabled multi-group NOMA networks in the presence of coordinated multi-point (CoMP) reception and imperfect successive interference cancellation (SIC). Particularly, a group-level SIC (GSIC) method is proposed to eliminate the decoded group’s interference together with the well-designed transceivers to mitigate the aggregated interference, including the intra-group interference, the residual interference caused by imperfect SIC, and the interference of NOMA users decoded later. According to the novel framework, a power minimization problem is formulated by collaboratively optimizing the transmit power and the phase shifts. To render the problem tractable, an alternating scheme is developed to optimize the transmit power and the phase shifts iteratively. Specifically, the transmit powers for the users in the same group are devised by a parallel iteration algorithm, whilst the phase shifts are optimized by a sequential rotation method. In simulations, it is shown that the proposed scheme requires less transmit power than various benchmark methods under the constraint of each user’s quality of service.

This paper proposes a cascade blockage model for analyzing the vision that a user has of a wireless network. This model, inspired by the classical multiplicative cascade models, has a radial structure meant to analyze blockages seen by the receiver at the origin in different angular sectors. The main novelty is that it is based on the geometry of obstacles and takes the joint blockage phenomenon into account. We show on a couple of simple instances that the Laplace transforms of total interference satisfies a functional equation that can be solved efficiently by an iterative scheme. This is used to analyze the coverage probability of the receiver and the effect of blockage correlation and penetration loss in both dense and sparse blockage environments. Furthermore, this model is used to investigate the effect of blockage correlation on user beamforming techniques. Another functional equation and its associated iterative algorithm are proposed to derive the coverage performance of the best beam selection in this context. In addition, the conditional coverage probability is also derived to evaluate the effect of beam switching. The results not only show that beam selection is quite efficient for multi-beam terminals, but also show how the correlation brought by blockages can be leveraged to accelerate beam sweeping and pairing.

Multiaccess edge computing (MEC), which brings computing capability close to the user equipment (UE) within a radio access network (RAN), is a promising technique to meet the challenges of explosive growth in edge data traffic and the number of connected devices. Nevertheless, MEC offloading failures, i.e., interruption of task offloading due to UE mobility and limited battery capacity, are still an important issue. In this article, we aim to minimize the total energy consumption in dual connectivity (DC)- and nonorthogonal multiple access (NOMA)-assisted computation offloading systems. This problem is formulated as a mixed-integer nonlinear programming (MINLP) problem with nonconvex constraints, which is a nondeterministic polynomial-time (NP)-hard and perplexing problem. To address this problem, we propose an iterative optimization algorithm to obtain a suboptimal time scheduling and task allocation solution. Specifically, we solve the nonconvex constrained MINLP problems by exploiting the successive convex approximation (SCA) algorithm and the nonlinear optimization algorithm with the mesh adaptive direct search (MADS) (NOMAD). Furthermore, a deep learning-based intelligent offloading scheme is introduced, called a cyclic branch network, to fully utilize data traffic and the computing capability on the network edge. Numerical results show that the proposed intelligent offloading scheme has comparable performance and dramatically reduces the inference time compared with the traditional optimization algorithm.

With the evolution of the fifth generation (5G) and beyond heterogeneous wireless networks, telecommunications operators and researchers are driven to develop advanced transmission technologies that enable the coexistence of multiple radio access technologies (multi‐RATs). By employing the efficient implementation of filter‐bank multi‐carrier (FBMC) transceiver and the scalable matrix transformation (SMT) module, in this study, a unified multiple access architecture termed as FBMC‐SMT is proposed, which is capable of flexibly integrating with both 3G and 4G transmission schemes and improving the system performance. As a special case of FBMC‐SMT, the performance evaluation of FBMC‐CDMA is conducted by extensive simulation. It is verified that FBMC‐CDMA with 16 subbands allocated outperforms the traditional single carrier wideband code division multiple access when the number of code channels assigned is larger than 5. Moreover, the signal‐to‐interference‐plus‐noise ratio analysis of FBMC‐SMT is also given and matches the simulation results very well. Hence, the proposed FBMC‐SMT can serve as a unified architecture to flexibly integrate multi‐RATs, thus to meet variable application requirements in 5G and beyond heterogeneous wireless networks.

To achieve reliable and green communication in the internet of things (IoT) networks, the authors extend the traditional half‐duplex quantise‐and‐forward (QF) cooperation into the simultaneous wireless information and power transfer (SWIPT) regime. This study investigates the achievable rate of the SWIPT‐based half‐duplex QF cooperation with the channel state information available only at the receivers. The source and destination are provided by the external power supply and the relay simultaneously implements the information transmission and the energy harvesting by SWIPT technology with the power‐splitting protocol. The achievable rate of the proposed system over the additive white Gaussian noise channels is analysed and further maximised by optimising the power‐splitting factor. Furthermore, the expected rate of the proposed system over the slow‐fading channels is analysed. Theoretical analysis and simulation results show that the achievable rate or expected rate of the SWIPT‐based QF cooperation is obviously superior to that of the SWIPT‐based amplify‐and‐forward or SWIPT‐based decode‐and‐forward cooperation. Meanwhile, the SWIPT‐based QF cooperation can achieve similar performance to the traditional QF cooperation when the external power supply at the relay is not provided.

Both small cells and non-orthogonal multiple access (NOMA) are cutting-edge technologies to boost the system capacity for the future wireless communications. In this paper, an analytical framework for small cell uplinks using NOMA transmissions is developed. To facilitate the detection of both near and far user signals, dual path loss compensation factors (PLCFs) are exploited for uplink power control. With the aid of stochastic geometry, the average successful transmission probability are derived for small cell networks with opportunistic NOMA transmissions and dual PLCFs. Based on the derived results, optimal PLCFs are obtained by two-dimension search methods. It is shown by simulation that the proposed NOMA scheme with optimal dual PLCFs outperforms the existing NOMA scheme with a unique PLCF in terms of both average successful transmission probability and spectrum efficiency.

This paper presents an efficient channel estimation scheme of the non-orthogonal multiple access system which named CDMA-FMT in 5G wireless networks. The proposed channel estimation scheme is theoretically analyzed based on the equivalent sub-band channel model. Moreover, the simulation results show that, by using the proposed channel estimation scheme, the BLER performance of the CDMA-FMT system outperforms the traditional CDMA system.

Multiuser multiple‐input–multiple‐output (MIMO) has great potential to substantially improve throughput of wireless networks. Unfortunately, it requires a significant amount of feed back for user selection, which prevents practical implementation. The authors propose a feed back reduced downlink multiuser MIMO system, where a signal‐to‐interference‐plus‐noise ratio (SINR) threshold is carefully designed. Only the users whose SINRs are above the threshold feed back their SINRs and channel direction information (CDI) to the base station. They establish a monotonic relation between the threshold and the average feed back overhead. Based on the established relation, they design the threshold that balances the tradeoff between the feed back load and the sum rate. Simulation results show that the proposed approach can achieve the same performance as the conventional full‐feed back scheme (where every user feeds back its SINR and CDI), while the proposed approach is able to reduce the system overhead by more than 40%.

We propose a feedback strategy based on SINR threshold for downlink multiuser wireless systems. By using the proposed strategy the base station receives feedback only from those users whose SINRs are above a threshold which is elaborately chosen and broadcast to all users in the cell by the base station. So not all users need send their channel direction information (CDI) and channel quality information (CQI) to the base station. It is proved that downlink wireless systems using the proposed strategy can achieve the multiplexing diversity and multiuser diversity gain with greatly reduced the sum feedback rate.

This paper presents a new receive scheme applied to orthogonal frequency-division multiplexing (OFDM) systems for reducing inter-carrier interference (ICI) caused by frequency offset at the receiver. The proposed scheme uses a class of time domain second order polynomial Nyquist window on the receive side. The signal to interference plus noise ratio (SINR) and bit error ratio (BER) performances of the receiver are analyzed in this paper. We also propose a method to find the optimum window parameters to maximize the SINR of the receiver thus providing an adaptive receiving capability. The results show that the proposed method that enables the use of unity roll-off factor provides better SINR and BER than conventional receive methods whose roll-off factors are generally less than one. The new second order polynomial window is shown to provide better performance than raised cosine and "better than" Nyquist window.