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.     

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.     

Binary power allocation for cognitive radio networks with centralized and distributed user selection strategies

Motivated by the desire for efficient spectral utilization, we present a novel algorithm based on binary power allocation for sum rate maximization in Cognitive Radio Networks (CRN). At the core lies the idea of combining multi-user diversity gains with spectral sharing techniques and consequently maximizing the secondary user sum rate while maintaining a guaranteed quality of service (QoS) to the primary system. We consider a cognitive radio network consisting of multiple secondary transmitters and receivers communicating simultaneously in the presence of the primary system. Our analysis treats both uplink and downlink scenarios. We first present a distributed power allocation algorithm that attempts to maximize the throughput of the CRN. The algorithm is simple to implement, since a secondary user can decide to either transmit data or stay silent over the channel coherence time depending on a specified threshold, without affecting the primary users’ QoS. We then address the problem of user selection strategy in the context of CRN. Both centralized and distributed solutions are presented. Simulation results carried out based on a realistic network setting show promising results.     

Quality of Service based resource allocation in D2D enabled 5G-CNs with network slicing

With the rapid new advancements in technology, there is an enormous increase in devices and their versatile need for services. Fifth-generation (5G) cellular networks (5G-CNs) with network slicing (NS) have emerged as a necessity for future mobile communication. The available network is partitioned logically into multiple virtual networks to provide an enormous range of users’ specific services. Efficient resource allocation methods are critical to delivering the customers with their required Quality of Service (QoS) priorities. In this work, we have investigated a QoS based resource allocation (RA) scheme considering two types of 5G slices with different service requirements; (1) enhanced Mobile Broadband (eMBB) slice that requires a very high data rate and (2) massive Machine Type Communication (mMTC) slice that requires extremely low latency. We investigated the device-to-device (D2D) enabled 5G-CN model with NS to assign resources to users based on their QoS needs while considering the cellular and D2D user’s data rate requirements. We have proposed a Distributed Algorithm (DA) with edge computation to solve the optimization problem, which is novel as edge routers will solve the problem locally using the augmented Lagrange method. They then send this information to the central server to find the global optimum solution utilizing a consensus algorithm. Simulation analysis proves that this scheme is efficient as it assigns resources based on their QoS requirements. This scheme is excellent in reducing the central load and computational time.     

Bandwidth allocation in cooperative wireless networks: Buffer load analysis and fairness evaluation

In modern cooperative wireless networks, the resource allocation is an issue of major significance. The cooperation of source and relay nodes in wireless networks towards improved performance and robustness requires the application of an efficient bandwidth sharing policy. Moreover, user requirements for multimedia content over wireless links necessitate the support of advanced Quality of Service (QoS) features. In this paper, a novel bandwidth allocation technique for cooperative wireless networks is proposed, which is able to satisfy the increased QoS requirements of network users taking into account both traffic priority and packet buffer load. The performance of the proposed scheme is examined by analyzing the impact of buffer load on bandwidth allocation. Moreover, fairness performance in resource sharing is also studied. The results obtained for the cooperative network scenario employed, are validated by simulations. Evidently, the improved performance achieved by the proposed technique indicates that it can be employed for efficient traffic differentiation. The flexible design architecture of the proposed technique indicates its capability to be integrated into Medium Access Control (MAC) protocols for cooperative wireless networks.     

Stochastic geometry analysis of coverage probability in energy efficient dense heterogeneous network with sleep control mechanism

The upsurge of data traffic in the macrocell networks has led to the massive deployment of small cells (SCs) for load sharing. Though small cell power consumption is low individually, significant aggregate power consumption, together with the MBS transmission power that is exponentially increasing over its served user load, deteriorates the network energy efficiency (EE). Consequently, EE is seen as a critical requirement for wireless network design in future. The challenge of EE maximization in dense heterogeneous networks is investigated in this research through a strategic small cell sleeping technique. A heuristic method based on distance and load awareness strategy in which the small cells with fewer users near the macrocell will be put into sleep mode. User equipments (UEs) under the service of the sleep small cells will be offloaded to the MBS. A dense heterogeneous network is considered with overlapped small cell coverage regions. All the edge area SCs will be kept ON to avoid QoS degradation. Simulation analysis on the stochastic geometry model indicates that the proposed sleep strategy significantly improves the network EE than the prevailing sleep control strategies while assuring seamless, efficient coverage in the sleep cell areas.     

A Traffic Splitting Algorithm for Load Balancing in Tor

As the most popular anonymous communication system, Tor provides anonymous protection for users by sending their messages through a series of relays. Due to the use of the bandwidth-weighted path selection algorithm, many more users choose routers with high bandwidth as relays. This will cause the utilization of high bandwidth routers to be much higher than that of low bandwidth routers, which will bring congestion risk. The Quality of Service (QoS) is difficult to guarantee for users who need delay-sensitive services such as web browsing and instant messaging. To reduce the average load of routers and improve the network throughput, we propose a circuit construction method with multiple parallel middle relays and conduct a dynamic load allocation method. The experiment demonstrates that our proposed method can provide better load balancing. Compared with other multipath anonymous communication networks, our proposed method can provide better anonymity.     

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.     

Reputation-based network selection mechanism using game theory

Current and future wireless environments are based on the coexistence of multiple networks supported by various access technologies deployed by different operators. As wireless network deployments increase, their usage is also experiencing a significant growth. In this heterogeneous multi-technology multi-application multi-terminal multi-user environment users will be able to freely connect to any of the available access technologies. Network selection mechanisms will be required in order to keep mobile users “always best connected” anywhere and anytime. In such a heterogeneous environment, game theory techniques can be adopted in order to understand and model competitive or cooperative scenarios between rational decision makers. In this work we propose a theoretical framework for combining reputation-based systems, game theory and network selection mechanism. We define a network reputation factor which reflects the network’s previous behaviour in assuring service guarantees to the user. Using the repeated Prisoner’s Dilemma game, we model the user–network interaction as a cooperative game and we show that by defining incentives for cooperation and disincentives against defecting on service guarantees, repeated interaction sustains cooperation.     

Advanced modulation formats for delivery of heterogeneous wired and wireless access networks

It is believed that the integration of wired and wireless access networks (or heterogeneous network) will provide high bandwidth and flexibility for both fixed and mobile users in a single and cost-effective platform. Here, we propose and demonstrate a signal remodulated wired and wireless network with wireless signal broadcast. Dark-return-to-zero (DRZ) and polarization-shift-keying (PolSK) signals are used for the downstream wired and wireless applications respectively. At the remote antenna unit (RAU), the PolSK signal is demodulated to produce the binary-phase-shift-keying (BPSK) signal, which will be used for the wireless broadcast application. Signal remodulation is demonstrated using reflective semiconductor optical amplifier (RSOA) as a colorless reflective modulator in the optical networking unit (ONU)/RAU. The downstream signal is remodulated at the ONU/RAU to produce the non-return-to-zero (NRZ) upstream signal.     

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.     

Scheduling for end-to-end performance in multi-rate CDMA/HDR systems

An interesting feature of the third generation (3G) cellular networks is their ability to support multiple data rates for data services. Thus, it is important to understand the end-to-end delay and throughput performance over these multi-rate cellular systems. In this work, we consider a multi-rate system such as High Data Rate (HDR) and represent the possible data rates using a Markov chain. Using a M/G/1 queuing model, we calculate the expected data rate and the corresponding link layer delay for each of the initial states. We study the effects of various link layer scheduling techniques for the radio link protocol (RLP) frames destined for multiple user. Though the commonly used link layer scheduling techniques work well, they do not provide the best performance for when end-to-end semantics need to be maintained. In this regard, we propose a scheduling algorithm that aids the transport protocol, for example TCP. Our research shows that the proposed remaining frames first scheduler enhances the transport layer performance compared to the commonly used “best channel scheduler”. Comparative results, based on simulations, are shown with respect to radius of cell, distance of user, number of users, and varying bit error rate.     

A Device-to-Device direct discovery algorithm to mitigate the collision caused by hidden users

Device-to-Device (D2D) discovery is an essential constituent in D2D communications as a future generation of wireless communication networks. Direct discovery enables users to discover their neighbors to exchange traffic without the cellular-networks assistance in order to enhance spectral efficiency and throughput. Despite its role to reduce signaling load, few works pay sufficient attention to direct discovery. According to the latest density of users detected by User Equipments (UEs) and their neighbors, this study suggests an adaptable, neighborhood-aware D2D direct discovery technique. To distinguish concealed UEs from other UEs, this technique employs a novel classification method. It also uses its neighborhood-aware capability to avoid severe collisions among all users, including hidden users. The performance of the proposed algorithm is compared with the recent adaptive algorithms and the algorithm recommended by the 3GPP standard. We evaluate algorithms in metrics such as discovery delay and the number of beacons required to terminate the discovery process. The simulation results show that the number of beacons, collision, and discovery delay considerably decrease via the proposed algorithm.     

Spectrum Slicing for Multiple Access Channels with Heterogeneous Services

Wireless mobile networks from the fifth generation (5G) and beyond serve as platforms for flexible support of heterogeneous traffic types with diverse performance requirements. In particular, the broadband services aim for the traditional rate optimization, while the time-sensitive services aim for the optimization of latency and reliability, and some novel metrics such as Age of Information (AoI). In such settings, the key question is the one of spectrum slicing: how these services share the same chunk of available spectrum while meeting the heterogeneous requirements. In this work we investigated the two canonical frameworks for spectrum sharing, Orthogonal Multiple Access (OMA) and Non-Orthogonal Multiple Access (NOMA), in a simple, but insightful setup with a single time-slotted shared frequency channel, involving one broadband user, aiming to maximize throughput and using packet-level coding to protect its transmissions from noise and interference, and several intermittent users, aiming to either to improve their latency-reliability performance or to minimize their AoI. We analytically assessed the performances of Time Division Multiple Access (TDMA) and ALOHA-based schemes in both OMA and NOMA frameworks by deriving their Pareto regions and the corresponding optimal values of their parameters. Our results show that NOMA can outperform traditional OMA in latency-reliability oriented systems in most conditions, but OMA performs slightly better in age-oriented systems.     

Exploitation of the Fiber Capacity in Optical Networks Using Time,Frequency, and Space Division Multiple Accesses

In this work we investigate how to obtain very high capacity transmissions in optical networks taking into account the limitations due to the physical channel. We consider both the case in which all the users are connected by a star coupler and the case in which the users are directly connected by the network topology. As a reference, we consider a ring network and a Shuffle Multihop Network (SMN). The use of optical systems to implement high-capacity networks is numerically investi gated by means of numerical simulations taking into consideration the channel limitations due to the chromatic dispersion, the Kerr effect, and the amplified spontaneous emission (ASE) noise of the optical amplifiers. In our model, we consider that the signal, during the routing process that is performed at the user position, undergoes only an attenuation. We suppose the use of intensity modulated signals and receivers with direct detection. Packet switching and digital transmission are assumed with soliton and conventional nonreturn to zero signals. Both wave length and time division multiple accesses are considered. The results show that, in the case of the Time Division Multiple Access (TDMA) technique, the use of a star coupler to connect the users reduces the capacity of a network with respect to the case in which a direct connection of the users is used. This is due to the strong power fluctuations that are present during the signal propagation and to the large quantity of accumulated ASE noise. On the other hand, the use of a star coupler shows the advantage to being easily reconfigurable. The Wavelength Divison Multiple Access (WDMA) technique permits us to achieve higher capacities with respect to the TDMA. This is due to the fact that in the propagation conditions, due to the presence of a star coupler, high bit rate signals are strongly degraded. On the other hand, several low bit rate signals operating at different wavelengths can propagate with a low power level, avoiding strong degradation due to the Four Wave Mixing (FWM) effect. Among the topologies considered in this work, the SMN is the one that generally permits us to reach the highest throughput because in the SMN the signal hops in a limited number of Network Interface Units (NIUs) before reaching the final destination.     

Exploitation of the Fiber Capacity in Optical Networks Using Time, Frequency, and Space Division Multiple Accesses

In this work we investigate how to obtain very high capacity transmissions in optical networks taking into account the limitations due to the physical channel. We consider both the case in which all the users are connected by a star coupler and the case in which the users are directly connected by the network topology. As a reference, we consider a ring network and a Shuffle Multihop Network (SMN). The use of optical systems to implement high-capacity networks is numerically investi gated by means of numerical simulations taking into consideration the channel limitations due to the chromatic dispersion, the Kerr effect, and the amplified spontaneous emission (ASE) noise of the optical amplifiers. In our model, we consider that the signal, during the routing process that is performed at the user position, undergoes only an attenuation. We suppose the use of intensity modulated signals and receivers with direct detection. Packet switching and digital transmission are assumed with soliton and conventional nonreturn to zero signals. Both wave length and time division multiple accesses are considered. The results show that, in the case of the Time Division Multiple Access (TDMA) technique, the use of a star coupler to connect the users reduces the capacity of a network with respect to the case in which a direct connection of the users is used. This is due to the strong power fluctuations that are present during the signal propagation and to the large quantity of accumulated ASE noise. On the other hand, the use of a star coupler shows the advantage to being easily reconfigurable. The Wavelength Divison Multiple Access (WDMA) technique permits us to achieve higher capacities with respect to the TDMA. This is due to the fact that in the propagation conditions, due to the presence of a star coupler, high bit rate signals are strongly degraded. On the other hand, several low bit rate signals operating at different wavelengths can propagate with a low power level, avoiding strong degradation due to the Four Wave Mixing (FWM) effect. Among the topologies considered in this work, the SMN is the one that generally permits us to reach the highest throughput because in the SMN the signal hops in a limited number of Network Interface Units (NIUs) before reaching the final destination.     

Group mobility assisted network selection framework in 5G vehicular cognitive radio networks

The heterogeneity nature of networks is the most eminent characteristic in 5G vehicular cognitive radio networks across complex radio environments. Since multiple communicating radios may be in motion at the same time in a vehicle. So, group mobility is the most prominent characteristic that requires to be a deep investigation. Therefore, different communication radios that are moving on a train/bus needed to select the networks simultaneously. Without considering the group mobility feature, there is a possibility that the same network may be selected by each moving node and cause congestion in a particular network. To overcome this problem, a novel network selection technique considering the group mobility feature is proposed to improve the throughput of the network. In this work, a 5G vehicular cognitive radio network scenario is also realized using USRP-2954 and LabVIEW communications system design suite testbed. The performance metrics like transmission delay, packet loss rate, reject rate and, channel utilization for vehicular nodes, are gained to analyze the proposed technique in vehicular cognitive radio networks environment. The proposed technique demonstrates a remarkable improvement in channel utilization for vehicular nodes and outperformed conventional schemes.     

Fairness and throughput performance of infrastructure IEEE 802.11 networks with hidden-nodes

The fairness behavior and throughput performance of IEEE 802.11 distributed coordination function and request-to-send/clear-to-send channel access scheme in the presence of hidden nodes are investigated. A mathematical model which accurately predicts a user’s throughput performance and packet collision probability in non-saturated traffic and asymmetric hidden node environments is developed. The model allows us to see many interesting results in networks with hidden nodes. In an asymmetric hidden node network environment, the network fairness performance depends on the traffic load. In low traffic conditions, users get their fair share of the resources. However, in moderate-to-high traffic conditions, users that experience less number of hidden nodes dominate the network, causing badly located stations in a network to starve. In addition, the performance of request-to-send/clear-to-send channel access scheme, which is developed as a solution to hidden node problem, in networks with hidden nodes, is also estimated. It is shown that request-to-send/clear-to-send contention resolution scheme greatly improves the network fairness performance in hidden node scenarios. The developed model enables us to more accurately estimate the performance of practical wireless local area networks, where hidden node occurrence is common. Theoretical analysis presented in the paper is validated with simulation results.     

Techno-Economic Analysis of FiWi Access Networks Based on 802.11ac WLAN and NG-PON2 Networks

In this article, techno-economic analysis of a fiber-wireless access network is presented. With high bandwidth capacity of the gigabit passive optical network and with cost-effectiveness of very high throughput 802.11ac wireless local area networks that enable user mobility in the wireless segment, fiber-wireless access networks can be considered as an alternative to the fiber-to-the-home architecture for next generation access networks. Analysis based on the proposed scenario here, shows that a fiber-wireless access network is a more cost-effective solution in densely populated areas, but with some introduced improvements, even other geotypes can be considered as a commercially-viable solution.     

D2D-assisted user-centric adaptive video transmission in next generation cellular networks

Next-generation cellular networks need to provide seamless connectivity with higher data rates, increased capacity, and enhanced network coverage. As multimedia service demands in various heterogeneous devices grow rapidly compared to the underlying network’s capacity and bandwidth, the adaptation in multimedia streaming services is essential for providing satisfactory Quality of Experience (QoE). This paper develops a Device-to-Device (D2D)-assisted Utility-based Adaptive Multimedia (video) Streaming scheme (UAMS) using D2D communication in a 5th Generation (5G) cellular network where low-battery users may extend their streaming duration by spending lower reception energy with the help of D2D-assisted communication. The adaptation algorithm considers four utility functions: quality, power consumption, packet error ratio, and remaining battery of the user devices to adapt the bitrate dynamically and augment viewers’ experience. We formulate an optimization problem to maximize the joint utility function to provide the best adaptive multimedia content selected for transmission to the end-users either directly or via D2D Relay Nodes (DRNs) in every scheduling interval. We use a graph theoretic approach for choosing the best DRNs. Extensive simulations show the efficacy of the proposed scheme in terms of saved battery energy, churn rate, and QoE metrics compared to a few well-known existing schemes in the literature that do not use D2D communication.