Asynchronous code-division random access using convex optimization

Many applications in cellular systems and sensor networks involve a random subset of a large number of users asynchronously reporting activity to a base station. This paper examines the problem of multiuser detection (MUD) in random access channels for such applications. Traditional orthogonal signaling ignores the random nature of user activity in this problem and limits the total number of users to be on the order of the number of signal space dimensions. Contention-based schemes, on the other hand, suffer from delays caused by colliding transmissions and the hidden node problem. In contrast, this paper presents a novel pairing of an asynchronous non-orthogonal code-division random access scheme with a convex optimization-based MUD algorithm that overcomes the issues associated with orthogonal signaling and contention-based methods. Two key distinguishing features of the proposed MUD algorithm are that it does not require knowledge of the delay or channel state information of every user and it has polynomial-time computational complexity. The main analytical contribution of this paper is the relationship between the performance of the proposed MUD algorithm in the presence of arbitrary or random delays and two simple metrics of the set of user codewords. The study of these metrics is then focused on two specific sets of codewords, random binary codewords and specially constructed algebraic codewords, for asynchronous random access. The ensuing analysis confirms that the proposed scheme together with either of these two codeword sets significantly outperforms the orthogonal signaling-based random access in terms of the total number of users in the system.     

Secrecy communications of intelligent reflecting surfaces aided NOMA networks

This paper investigates the physical layer security of an intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) networks, where a remote user is regarded as an eavesdropper to intercept the information of nearby user. To evaluate the security performance of IRS-aided NOMA networks, a problem of maximizing achievable secrecy rate is formulated via jointly optimizing the beamforming and phase shifting. More specifically, we aim to tackle the non-convex problem by optimizing beamforming vector as well as phase shifting matrix with the assistance of block coordinate descent (BCD) and minorization maximization (MM) algorithms. Numerical results illustrate that: 1) The secrecy rates of IRS-aided NOMA with BCD and MM algorithms are superior to that of orthogonal multiple access schemes; 2) With increasing the number of reflecting elements, the secrecy rates of IRS-aided NOMA networks are achieved carefully; and 3) The IRS-aided NOMA networks are capable of relieving the transmission pressure of base station.     

Network selection algorithm based on link quality parameters for heterogeneous wireless networks

Next generation wireless networks consist of heterogeneous access technologies. In order to provide global ubiquitous communication, it is required to provide a framework in which user can move across multiple access interfaces while maintaining its ongoing communication at perceived quality of service. Given the scenario of multiple access networks, it is further required to select the optimum network out of multiple candidate networks to meet the requirements of the ongoing session. The selection of optimum network in such heterogeneous environment is generally based on network conditions and user preference. In this paper, we propose an algorithm for network selection based on averaged received signal strength, outage probability and distance. The proposed algorithm comprises of two stages. Assuming that network conditions are dominant in network selection, in first stage, overlapping region is identified through distance estimation. Network selection algorithm based on averaged received signal strength plus outage is invoked in second stage to select the optimum network. Numerical results are obtained through a simulation model of two disparate networks – GSM and UMTS. It has been shown that the proposed algorithm offers 68% improved performance in terms of network selection rate.     

Particle swarm optimization based network selection in heterogeneous wireless environment

Deployment of heterogeneous wireless networks is spreading throughout the world as users want to be connected anytime, anywhere, and anyhow. Meanwhile, users are increasingly interested in multimedia applications such as audio, video streaming and Voice over IP (VoIP), which require strict Quality of Service (QoS) support. Provisioning of Always Best Connected (ABC) network with such constraints is a challenging task. Considering the availability of various access technologies, it is difficult for a network operator to find reliable criteria to select the best network that ensures user satisfaction while reducing multiple network selection. Designing an efficient Network selection algorithm, in this type of environment, is an important research problem. In this paper, we propose a novel network selection algorithm utilizing signal strength, available bit rate, signal to noise ratio, achievable throughput, bit error rate and outage probability metrics as criteria for network selection. The selection metrics are combined with PSO for relative dynamic weight optimization. The proposed algorithm is implemented in a typical heterogeneous environment of EDGE (2.5G) and UMTS (3G). Switching rate of the user between available networks has been used as the performance metric. Moreover, a utility function is used to maintain desired QoS during transition between networks, which is measured in terms of the throughput. It is shown here that PSO based approach yields optimal network selection in heterogeneous wireless environment.     

Power allocation for cognitive underlay networks with spectrum band selection

In this paper, we study the cooperative communication of a cognitive underlay network by utilizing the diversity of multiple spectrum bands. In particular, we assume that the transmission power of the secondary user (SU) is subject to different joint constraints, such as peak interference power of the multiple primary users (PUs), peak transmission power of the SU, outage tolerate interference, and outage probability threshold. Accordingly, two power allocation schemes are considered on the basis of the minimum interference channel from the SU to the PU and the channel state information of the primary user link. Furthermore, the SU can select one of the three transmission modes following the channel state conditions, namely as cellular, device-to-device, or switching mode, to transmit the signal to the secondary user receiver. Given this setting, two power allocation schemes over a spectrum band selection strategy are derived. In addition, closed-form expressions for the outage probability of three modes are also obtained to evaluate the performance of the secondary network. Most importantly, a closed-form expression for the peak interference power level of the PU, which is considered as one of the most important parameters to control the SU’s transmission power, is derived by investigating the relation of two considered power allocation schemes in the practise. Finally, numerical examples show that the outage performance of secondary network in the switching mode outperforms the one of the cellular and device-to-device (D2D) mode for all considered power allocation schemes.     

On the performance of a virtual user pairing scheme to efficiently utilize the spectrum of unpaired users in NOMA

This paper evaluates the performance of a virtual user pairing scheme that efficiently utilizes the spectrum of unpaired users in non-orthogonal multiple access (NOMA), termed as VP-NOMA. The scheme aims at utilizing the frequency bands of those users which remain unpaired due to the non-uniform distribution of users in a cellular area. We consider a case where the cell edge users are more than the cell center users, so that complete one-to-one correspondence does not exist between all cell center and cell edge users to be accommodated/paired using conventional NOMA (C-NOMA) user pairing. Thus, some cell edge users remain unpaired, and are served using conventional multiple access (OMA) schemes. In such scenario, VP-NOMA pairs a single cell center user with two or more clustered (closely located) cell edge users over non-overlapping frequency bands, thus enabling the cell center user to efficiently use the frequency bands of these previously unpaired cell edge users. Performance of VP-NOMA in terms of ergodic sum capacity (ESC), outage probability (OP), and outage sum capacity (OSC), is analyzed through comprehensive mathematical derivations and simulations for a generalized system model. Moreover, the mathematical analysis is validated through close concordance between analytical and simulation results of ESC, OP, and OSC.     

Joint user grouping and power allocation in VLC-NOMA system

With the energy consumption of wireless networks increasing, visible light communication (VLC) has been regarded as a promising technology to realize energy conservation. Due to the massive terminals access and increased traffic demand, the implementation of non-orthogonal multiple access (NOMA) technology in VLC networks has become an inevitable trend. In this paper, we aim to maximize the energy efficiency in VLC-NOMA networks. Assuming perfect knowledge of the channel state information of user equipment, the energy efficiency maximization problem is formulated as a mixed integer nonlinear programming problem. To solve this problem, the joint user grouping and power allocation (JUGPA) is proposed including user grouping and power allocation. In user grouping phase, we utilize the average of channel gain among all user equipment and propose a dynamic user grouping algorithm with low complexity. The proposed scheme exploits the channel gain differences among users and divides them into multiple groups. In power allocation phase, we proposed a power allocation algorithm for maximizing the energy efficiency for a given NOMA group. Thanks to the objective function is fraction form and non-convex, we firstly transform it to difference form and convex function. Then, we derive the closed-form optimal power allocation expression that maximizes the energy efficiency by Dinkelbach method and Lagrange dual decomposition method. Simulation results show that the JUGPA can effectively improve energy efficiency of the VLC-NOMA networks.     

A power allocation method for $$2 \times 2$$ VLC-MIMO indoor communication

Visible light communication (VLC) has been a promising field of optical communications which focuses on visible light spectrum that humans can see. Unlike existing studies which mainly discuss point-to-point communication, in this paper, we consider a VLC network, in particular a \(2 \times 2\) system. Our focus is on dealing with interference in this network. The objective is to maximize the signal to interference plus noise ratio (SINR) of one receiver for a given SINR of another receiver. We formulate a power allocation optimization problem to deal with such interference, and introduce dichotomy to solve this optimization problem. Simulation results have twofold meaning: First, \(\mathrm{SINR}_1\) increases with the growth of \(\mathrm{SINR}_2\), which are the SINR of the two receivers, respectively. Second, our proposed scheme outperforms the classical time-division multiple access technique in terms of transmit powers of both light sources when the data rate for these two schemes are set to be identical for each user, respectively.     

Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems

In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.     

Optimization design of RIS-assisted high-capacity visible light communications based on HDMA

In this paper, a new non-orthogonal multiple access (NOMA) scheme is proposed for the reconfigurable intelligent surface (RIS) assisted high-capacity visible light communication (VLC) system, which is named hybrid domain multiple access (HDMA). HDMA enjoys the benefit of hybrid-domain signals, including the power domain, code domain, and frequency domain, where the message passing algorithm (MPA) and successive interference cancellation (SIC) detectors are jointly used at the HDMA receiver. Furthermore, to achieve a higher communication capacity for the VLC system, we proposed an optimization model by jointly optimizing the power allocation ratio and RIS reflection units. The simulation results verified the proposed scheme. By comparing the system capacity of different RIS allocation schemes and multiple access methods, the VLC system based on HDMA proposed in this paper can significantly improve its communication capacity.     

Outage probability and ergodic capacity analysis of satellite–terrestrial NOMA system with mixed RF/mmWave relaying

This paper investigates the performance of hybrid radio frequency/millimeter wave (RF/mmWave) satellite–terrestrial relay network with non-orthogonal multiple access (NOMA) scheme. In particular, the satellite network operates at the Ka-band while the mmWave band is adopted at decode-and-forward (DF) relay–destination link. The blockage effect in mmWave communication is considered to deduce the ordered probability density function (PDF) of the user equipment (UE) distance. However, the randomness of the UEs’ location and the random beamforming design cause the difficulty of the performance analysis. Herein, we provide a closed-form approximation for the outage probability. Moreover, the system diversity order is derived from the asymptotic expressions of the outage probability at high signal-to-noise ratio (SNR) slopes. Besides, approximate ergodic capacity performances of the multi-UEs are evaluated with numerical integration. Simulations are applied to demonstrate the accuracy of the theoretical analysis and show that the performance of the ordered selection NOMA scheme outperforms the orthogonal multiple access scheme and random selection scheme.     

RAT selection for IoT devices in HetNets: Reinforcement learning with hybrid SMDP algorithm

Due to the increasing deployment of heterogeneous networks (HetNets), the selection of which radio access technologies (RATs) for Internet of Things (IoT) devices such as user equipments (UEs) has recently received extensive attention in mobility management research. Most of existing RAT selection methods only optimize the selection strategies from the UE side or network side, which results in heavy network congestion, poor user experience and system utility degradation. In this paper the UE side and the network side are considered comprehensively, based on the game theory (GT) model we propose a reinforcement learning with assisted network information algorithm to overcome the crucial points. The assisted information is formulated as a semi-Markov decision process (SMDP) provided for UEs to make accurate decisions, and we adopt the iteration approach to reach the optimal policy. Moreover, we investigate the impacts of different parameters on the system utility and handover performance. Numerical results validate that our proposed algorithm can mitigate unnecessary handovers and improve system throughputs.     

Optimization Algorithms for Joint Power and Sub-Channel Allocation for NOMA-Based Maritime Communications

This paper investigates resource optimization schemes in a marine communication scenario based on non-orthogonal multiple access (NOMA). According to the offshore environment of the South China Sea, we first establish a Longley–Rice-based channel model. Then, the weighted achievable rate (WAR) is considered as the optimization objective to weigh the information rate and user fairness effectively. Our work introduces an improved joint power and user allocation scheme (RBPUA) based on a single resource block. Taking RBPUA as a basic module, we propose three joint multi-subchannel power and marine user allocation algorithms. The gradient descent algorithm (GRAD) is used as the reference standard for WAR optimization. The multi-choice knapsack algorithm combined with dynamic programming (MCKP-DP) obtains a WAR optimization result almost equal to that of GRAD. These two NOMA-based solutions are able to improve WAR performance by 7.47% compared with OMA. Due to the high computational complexity of the MCKP-DP, we further propose a DP-based fully polynomial-time approximation algorithm (DP-FPTA). The simulation results show that DP-FPTA can reduce the complexity by 84.3% while achieving an approximate optimized performance of 99.55%. This advantage of realizing the trade-off between performance optimization and complexity meets the requirements of practical low-latency systems.     

Outage performance of CoMP-CNOMA networks with duplex mode selection

This paper investigates the outage performance of a downlink coordinated multipoint cooperative non-orthogonal multiple access (CoMP-CNOMA) network, where two near users cooperatively relay the information to a far user. It is assumed that the near users support both the half-duplex relaying mode and the full-duplex relaying mode. Since the full-duplex mode may be inferior to the half-duplex mode due to the residual self-interference under the full-duplex mode, we propose a duplex mode selection strategy for the near users to dynamically choose the duplex mode for relaying. Under the proposed duplex mode selection strategy, the closed form expressions for the outage probabilities of all the users are derived. The theoretical results match well with the Monte Carlo simulations. It is shown that the proposed duplex mode selection strategy can provide low outage probabilities of all the users simultaneously, while the existing duplex mode selection strategies either achieve higher outage probabilities of all the users or achieve slightly better outage performance of the far user at the sacrifice of much worse outage performance of the near users.     

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Game theory and power control in ultrawideband networks

This paper describes a theoretical framework for the design and analysis of power control algorithms for high-throughput wireless networks using ultrawideband (UWB) technologies. The tools of game theory are shown to be expedient for deriving scalable, energy-efficient, distributed power control schemes to be applied to a population of battery-operated user terminals in a rich multipath environment. In particular, the power control issue is modeled as a dynamic noncooperative game in which each user chooses its transmit power so as to maximize its own utility, which is defined as the ratio of throughput to transmit power. Although distributed (noncooperative) control is known to be suboptimal with respect to the optimal centralized (cooperative) solution, it is shown via large-system analysis that the game-theoretic distributed algorithm based on Nash equilibrium exhibits negligible performance degradation with respect to the centralized socially optimal configuration. The framework described here is general enough to also encompass the analysis of code division multiple access (CDMA) systems and to show that UWB slightly outperforms CDMA in terms of achieved utility at the Nash equilibrium.     

Teleportation of Unknown Atomic Entangled States Using GHZ Class States

We propose two physical schemes, which can teleport unknown atomic entangled states from user A （Alice） to user B （Bob） via GHZ class states as quantum channel The two schemes are both based on cavity QED techniques. In the two schemes, teleportation and distillation procedures can be realized simultaneously. The second teleportation scheme is more advantageous than the first one.     

A fuzzy extension of VIKOR for target network selection in heterogeneous wireless environments

In a highly integrated ubiquitous wireless environment, the selection of a network that can fulfill end-users’ service requests while keeping their overall satisfaction at a high level, is vital. The wrong selection can lead to undesirable conditions such as unsatisfied users, weak Quality of Service (QoS), network congestions, dropped and/or blocked calls, and wastage of valuable network resources. The selection of these networks is performed during the handoff process when a Mobile Station (MS) switches its current Point of Attachment (PoA) to a different network due to the degradation or complete loss of signal and/or deterioration of the provided QoS. Traditional schemes perform the handoff necessity estimation and trigger the network selection process based on a single metric such as Received Signal Strength (RSS). These schemes are not efficient enough, as they do not take into consideration the traffic characteristics, user preferences, network conditions and other important system metrics. This paper presents a novel multi-attribute vertical handoff algorithm for heterogeneous wireless networks which achieves seamless mobility while maximizing end-users’ satisfaction. Two modules are designed to estimated the necessity of handoff and to select the target network. These modules utilize parallel Fuzzy Logic Controllers (FLCs) with reduced rule-set in combination with a network ranking algorithm developed based on Fuzzy VIKOR (FVIKOR). Simulation results are provided and compared with a benchmark.     

Joint User Scheduling,Relay Selection,and Power Allocation for Multi-Antenna Opportunistic Beamforming Systems

Opportunistic beamforming (OBF) is a potential technique in the fifth generation (5G) and beyond 5G (B5G) that can boost the performance of communication systems and encourage high user quality of service (QoS) through multi-user selection gain. However, the achievable rate tends to be saturated with the increased number of users, when the number of users is large. To further improve the achievable rate, we proposed a multi-antenna opportunistic beamforming-based relay (MOBR) system, which can achieve both multi-user and multi-relay selection gains. Then, an optimization problem is formulated to maximize the achievable rate. Nevertheless, the optimization problem is a non-deterministic polynomial (NP)-hard problem, and it is difficult to obtain an optimal solution. In order to solve the proposed optimization problem, we divide it into two suboptimal issues and apply a joint iterative algorithm to consider both the suboptimal issues. Our simulation results indicate that the proposed system achieved a higher achievable rate than the conventional OBF systems and outperformed other beamforming schemes with low feedback information.     

A cognitive MAC protocol for QoS provisioning in ad hoc networks

In this paper, we consider an ad hoc network overlaying a legacy time-division multiple access (TDMA) system. This kind of ad hoc and infrastructure-based coexisting architecture can have an important application for the future cognitive radio (CR) network. To establish an overlaying ad hoc network in the presence of primary users, the medium access control (MAC) protocol shall achieve high spectrum utilization, avoid interfering the primary user and establish the link quickly. To this end, we propose four enhanced mechanisms for the carrier sense multiple access with collision avoidance (CSMA/CA) MAC protocol: (1) a neighbor list establishment mechanism for recognizing spectrum usage opportunities, (2) a set of contention resolution methods to reduce the collision and delay variance, (3) an invited reservation procedure for meeting the delay requirements of real-time traffic, and (4) a distributed frame synchronization mechanism for coordinating transmission without a centralized controller. Compared to the legacy IEEE 802.11 MAC protocol, the proposed CSMA/CA MAC protocol enhancement can improve the system throughput by 50% through analysis and NS-2 simulations, while keeping the dropping rate lower than 2% for delay-sensitive traffic. Furthermore, the standard deviation of the access delay is reduced by five times. With these QoS enhanced mechanisms, the proposed cognitive CSMA/CA MAC protocol can allow an ad hoc network to coexist with the legacy TDMA system.