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In intelligent vehicular networks, vehicles should be able to communicate with their surroundings while traveling. This results in more efficient, safer, and comfortable driving experiences, as well as new commercial prospects in a variety of industries. Connected vehicles and autonomous vehicles expect 100% reliable connectivity without any compromise in quality. However, due to challenges such as difficult channel terrains in urban scenarios and dead zones, the reliability of current vehicle-to-infrastructure (V2I) and vehicle-to-vehicle communication systems cannot be guaranteed. The performance of vehicular networks can be considerably enhanced with reconfigurable intelligent surfaces (RIS). Non-orthogonal multiple access (NOMA) allows for massive connectivity with the surroundings. In vehicular networks, the RIS-assisted NOMA can ensure regulated channel gains, better coverage, throughput, and energy efficiency. In this work, a blind RIS-assisted fixed NOMA (FNOMA) system is proposed for a downlink V2I scenario. The closed-form analytical outage probability and throughput expressions are derived by considering RIS as an intelligent reflector and as a roadside unit. It is observed that the analytical and Monte Carlo simulation results are closely related. In simulations, it has been discovered that RIS-assisted FNOMA outperforms the traditional NOMA variants in terms of outage and throughput. Even without precise channel knowledge, blind RIS transmission outperforms traditional NOMA variants due to huge array gain. The increase in the number of reflective elements also results in a significant improvement in signal-to-noise ratio gains. [ABSTRACT FROM AUTHOR]

Due to stochastic wireless environment, the process of modulation classification has become a challenging task. Because of its powerful feature extraction ability and promising performance over the conventional schemes, deep learning (DL) models are employed to automatic modulation classification (AMC) problems. Most of the conventional models proposed are tested for the limited set of modulation schemes transmitted over additive white Gaussian noise (AWGN) channels without considering the effect of multipath fading and Doppler shift. The next-generation networks use adaptive and higher-order quadrature amplitude modulation (QAM) schemes for higher spectral efficiency. The classification accuracy of conventional DL-based AMC schemes drastically reduces, when different order QAM modulation schemes are accommodated. In this work, different scaling factors are selected for the generation of M -QAM frames. The combination of scaling factors, which maximize the classification accuracy is chosen. A convolutional neural network (CNN) with six stages is employed for AMC. The simulation results show that the classification accuracy of proposed scheme is higher than the conventional DL-based schemes under various signal-to-noise ratio (SNR) conditions. The proposed scheme shows at least 4% improvement in classification accuracy over the other DL-based schemes. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) has been widely acclaimed as a promising solution to enhance spectral efficiency, increase user fairness, and scale up the number of users in wireless networks by enabling multiple users to share the symmetrical wireless resources. This work is concerned with the development and implementation of blind reconfigurable intelligent surface (RIS)-aided ordered NOMA (ONOMA) for smart reflector (SR) and access point (AP) configurations. For the RIS-SR-ONOMA and RIS-AP-ONOMA configurations, the closed-form probability of outage expressions is derived, and their performance is reported for distinct values of passive reflector elements. Through optimal power allocation, the downlink (DL) sum capacity is maximized. RIS-aided ONOMA reduces outage rates and increases sum capacity over the traditional ONOMA system. It is discovered that the RIS-aided ONOMA system increases the sum capacity by ≈33% at 20 dB signal-to-noise ratio (SNR) for 32 passive reflector elements. The addition of passive reflector elements and symmetrical allocation among users improves the performance of RIS-SR-ONOMA and RIS-AP-ONOMA in terms of outage probability, sum capacity, and probability of error. The proposed work can be employed in applications such as vehicular ad hoc networks, where obtaining precise channel information is difficult due to the rapid mobility of the vehicles. [ABSTRACT FROM AUTHOR]

Summary: Fifth‐generation (5G) networks are expected to offer unprecedented amounts of spectral and energy efficiency. Spatial modulation (SM) techniques have the capability to achieve an appealing trade‐off between these conflicting design parameters. Fully generalized SM (FGSM) and fully quadrature SM (FQSM) are the recent high‐rate SM variants, where the spectral efficiency is linearly proportional to the number of transmit antennas. The transmit antenna selection schemes can efficiently improve the average bit error rate (ABER) performance of SM techniques. The main objective of this work is to investigate the employment of transmit antenna selection schemes to FGSM and FQSM. Initially, Euclidean distance optimized antenna selection (EDAS) scheme is employed to FGSM and FQSM. It offers superior performance than conventional FGSM/FQSM without transmit antenna selection at the cost of higher computational complexity. In order to reduce the complexity cost, four suboptimal schemes based on channel capacity, correlation and combination of them are proposed and employed to FGSM and FQSM. The suboptimal transmit antenna selection based on capacity and correlation (TAS‐A‐C) offers a minimum gain of ∼6 dB over conventional FGSM/FQSM with significantly lower complexity. In addition, the performance of all schemes is investigated for increased number of available transmit antennas. As the proposed schemes address the spectral and energy efficiency trade‐off effectively, while corroborating better ABER performance, they have the potential to become a competing candidate for next‐generation networks. [ABSTRACT FROM AUTHOR]

The Vehicular Ad hoc NETworks (VANETs) are of high mobile and dynamic in nature. They are highly prone to network discontinuity, thereby the applications running on the vehicles get degraded in its service. The network selection for VANETs is done based on network attributes and user Quality of Service (QoS) demands. In this work, a two-phase access network selection scheme is proposed for VANETs. In the first phase, the available networks are ranked based on QoS demands using Weighted Sum Method (WSM). During the second phase, based on availability of resources, handoff decision and access network selection are carried out using game theory approach. Here, the vehicle and network play the game by adopting different strategies, thereby the optimum Nash Equilibrium (NE) is obtained. The simulation results validate that the proposed scheme outperforms the conventional Multiple Attribute Decision Making (MADM) schemes. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have fascinating applications that help mankind to get connected with the physical world. Since the last decade, wireless sensor networks are been researched as physical infrastructure of Internet of things technology. For such accomplishment, wireless sensor networks need to be scalable and self-organizing. As sensor nodes are battery driven, limited lifetime is the prime constraint. Clustering methods are popularly used to prolong the network lifetime, but cluster leader selection algorithms majorly affect total energy consumption of the network. This is because cluster leaders utilize more energy than other nodes. For scalable networks, selecting appropriate cluster leaders is a great challenge. In this research work, a distributed cluster leader selection algorithm is proposed to prolong the network lifetime. Real-time network parameters are used instead of random variables or constants in the formulation of cluster leader selection criteria. Due to this, minimal but sufficient number of cluster leaders are selected. This reduces number of transmissions toward the sink and significantly minimizes overall energy consumption. The simulation results indicate that the proposed algorithm enhances network lifetime efficaciously for varying node density and coverage area. Thus, the proposed algorithm can be suitably used for Internet of things applications. [ABSTRACT FROM AUTHOR]

In order to address the exponential growth of data traffic, the concept of device-to-device (D2D) communication has been introduced in fifth generation (5G). The seamless handover to the finest available access network is very essential in furnishing high quality of experience (QoE) to the devices involved in D2D communication. An intelligent, fast and reliable vertical handover (VHO) decision scheme is required for D2D to achieve seamless mobility and uninterrupted service. To address these issues, a two-stage fuzzy logic-based VHO scheme is proposed in this work. Here, fuzzy logic-based handover requirement analysis (HRA) is carried out in stage 1 based on received signal strength (RSS), data rate (DR) and latency (LA). This stage minimizes the unnecessary handovers. In stage 2, fuzzy-analytic hierarchy process (Fuzzy-AHP), fuzzy-technique for order preference by similarity to ideal solutions (Fuzzy-TOPSIS) are used in ranking and selecting the target access network. Through simulations, it has been proved that the proposed scheme offers improved performance than the classical and fuzzy-based multi-attribute decision-making (MADM) schemes. The proposed scheme offers 3.45 % , 7.33 % , 13.51 % , 40 % minimum improvement in data rate, handover decision delay, handover blocking probability and number of handovers executed over the classical MADM schemes considered. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are predominantly used for monitoring applications. The sensor nodes are resource-constrained devices, and hence efficient energy utilization of these nodes is one of the major challenges. The communication distances directly impact on the energy consumption of the sensor nodes. Clustering methods are popularly used to reduce communication distances and prolong the network lifetime. Multi-sink deployment is another method to reduce communication distances. It also resolves congestion and hotspot issues. In multi-sink WSNs, the number of sinks to be considered is a challenging task as it affects the network topology, lifetime and deployment cost. In this research work, multi-sink deployment and clustering scheme with sink selection algorithm are jointly proposed to maximize the network lifetime and minimize the deployment cost. An iterative filtering model is proposed to estimate optimal number of sinks, while sink positions are determined based on Fuzzy logic inference system (FLIS). Fuzzy-c-means algorithm is used to form balanced clusters in the network. Cluster representative and sink selection processes are based on FLIS. The proposed optimal multi-sink deployment scheme reduces the deployment cost and the propagation delay of the system, while enhancing the network lifetime. The proposed scheme is also energy efficient in the case of higher node density. Hence, the proposed scheme can be suitably implemented for large-scale monitoring applications of WSNs. [ABSTRACT FROM AUTHOR]

The network performance is an imperative factor for the customers to select a mobile network operator (MNO). The customers demand seamless mobility and services with minimal packet loss and ultra-low latency from the subscribed MNO. Device-to-Device (D2D) communication is one of the key enabling solutions of fifth generation (5G), which has the potential to enhance throughput, latency, packet loss rate (PLR) performances of the network. 5G is expected to support high mobility and smaller range heterogeneous cells. This leads to frequent handovers. The unessential handovers may cause wastage of network resources. The improper network selection may prompt extreme quality degradation. In this work, a three-stage fuzzy-logic-based handover necessity estimation and target selection scheme is proposed for general heterogeneous networks. The simulation results prove that PLR, number of handovers executed and throughput performances of the proposed scheme are superior than the conventional and fuzzy-based multi-attribute decision-making (MADM) schemes. Even though this scheme is demonstrated for D2D application, it can be extended for any heterogeneous network scenarios. [ABSTRACT FROM AUTHOR]

Summary: Spatial modulation techniques (SMTs) have emerged as promising multiple‐input and multiple‐output (MIMO) technology for fifth generation (5G) networks, which can achieve an appealing trade‐off between conflicting design objectives such as reliability, hardware cost, complexity, spectral efficiency, and energy efficiency. Most of the SMTs suffer from significant performance deterioration under correlated fading channels. In this paper, a novel spectral efficient SMT referred as enhanced redesigned spatial modulation (EReSM) is proposed, which is robust against adverse channel correlation effects. At any time instant, EReSM activates either one or two transmit antennas and employs a robust bits to antenna index mapping that ensures the selection of antenna subsets with maximum spatial separation to mitigate the effect of spatial correlation. EReSM also exploits phase rotation of transmitted symbols as an additional dimension to convey an extra information bit. The rotation angles used for bit mapping are optimized for various modulation schemes to maximize the minimum euclidean distance between the symbols. To analyze the performance, analytical upper bound expression for average bit error probability (ABEP) is derived for both uncorrelated and spatially correlated channel conditions. Monte Carlo simulation results substantiate the accuracy of the analytical results and also demonstrate that the proposed EReSM outperform conventional redesigned spatial modulation (ReSM) by at least 4 dB. [ABSTRACT FROM AUTHOR]

Spatial modulation (SM) is a spectrum and energy-efficient simple digital modulation scheme, which uses the transmitter antenna indices to convey the additional bits. The conventional SM variants have high complex receivers and offer poor performance under spatially correlated and line-of-sight (LOS) channel conditions. In this work, a new variant, modified spatial modulation (MSM) for 8 × 8 multiple input multiple output (MIMO) configuration is proposed, which uses one or two transmitter antennas based on the incoming bit patterns. The adaptive mapping used at the transmitter side for antenna selection and modified maximum likelihood (ML) detection used at the receiver side reduces the computational complexity. Every possible bit per channel use (bpcu) is mapped to a unique transmit symbol vector, which minimizes the receiver complexity, while combating the effect of spatial correlation. Through simulation results, it is observed that the average bit error rate (ABER) performance of the MSM-ML scheme is much better than that of the conventional SM-ML, generalized spatial modulation (GSM)-ML and redesigned spatial modulation (ReSM)-ML schemes under spatially correlated and LOS channel conditions. The promising results prove that the proposed scheme can be a better alternative to spatial multiplexing (SMX) in battery-driven compact handheld devices, which can be used for international mobile telecommunication-2020 (IMT-2020). [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication is expected to play a significant role in the fifth-generation (5G) networks. To support seamless mobility and service continuity, the device(s) undergoing D2D communication should be handed over to the best access network among all the available wireless access networks. A seamless vertical handover (VHO) across the heterogeneous wireless networks is the key enabling solution for achieving the seamless service continuity and mobility. The VHO algorithm should be intelligent, and the decisions should also consider the quality requirements other than the conventional received signal strength (RSS). In this work, a two-stage fuzzy-logic-based VHO decision algorithm is developed to select suitable access network based on the quality-of-service requirements. The quality parameters like data rate and latency are given as the fuzzy inputs along with RSS. The resource availability check is also carried out for the target network, which makes the decision more intelligent. The simulation results show that the proposed scheme offers better performance than the traditional multi-attribute decision-making schemes. [ABSTRACT FROM AUTHOR]

In a smart city environment, Intelligent Transportation System (ITS) enables the vehicle to generate and communicate messages for safety applications. There exists a challenge where the integrity of the message needs to be verified before passing it on to other vehicles. There should be a provision to motivate the honest vehicles who are reporting the true event messages. To achieve this, traffic regulations and event detections can be linked with blockchain technology. Any vehicle violating traffic rules will be issued with a penalty by executing the smart contract. In case any accident occurs, the vehicle nearby to the spot can immediately send the event message to Unmanned Aerial Vehicle (UAV). It will check for its credibility and proceed with rewards. The authenticity of the vehicle inside the smart city area is verified by registering itself with UAVs deployed near the city entrance. This is enabled to reduce the participation of unauthorized vehicles inside the city zone. The Secure Hash Algorithm (SHA256) and Elliptic Curve Digital Signature Algorithm (ECDSA-192) are used for communication. The result of computation time for certificate generation and vehicles involvement rate is presented. [ABSTRACT FROM AUTHOR]

In this article, we analyze the downlink transmission of a wirelessly powered hybrid cooperative non-orthogonal multiple access (C-NOMA) system relying on reconfigurable intelligent surfaces (RIS), where self-interference related to full-duplex (FD) and power efficiency are also considered. The network contains a single-antenna base station (BS), a RIS with many reflecting elements, a power beacon, and two users that can function in FD in comparison with the benchmark, i.e. half-duplex mode. In the proposed system, there are two communication paths from the BS to the far-user either through the RIS or via a near-user employing energy-harvesting from a power beacon. To comprehend the performance of the proposed system, we study and compare the outage probability under various parameters of interest such as power allocation coefficients, energy harvesting coefficients, number of RIS reflecting elements, and transmission rates. We aim to show the trade-off between these main parameters and system outage performance. Moreover, to highlight the advantages of the wireless-powered RIS-aided CNOMA system, we compare it against with benchmark, i.e. a wireless-powered RIS-aided cooperative orthogonal multiple access (C-OMA) system. All derived closed-form outage expressions are verified by employing Monte-Carlo simulations. Numerical results show that: (1) wireless powered RIS-aided FD C-NOMA is superior to the wireless-powered RIS-aided FD C-OMA in terms of outage probability in the high signal-to-noise ratio (SNR) region; and (2) in delay-to-tolerant transmission scenarios, the energy efficiency of the proposed wireless powered RIS FD C-NOMA outperforms the wireless powered RIS FD C-OMA in the high SNR region. [ABSTRACT FROM AUTHOR]

Summary: Wireless smart sensor networks (WSSNs) are emerging as the physical backbone of the internet of things (IoT) technology. On the basis of the IoT platform, web‐based systems and services are been developing such as e‐surveillance, industrial‐IoT, and precision agriculture. For farmland monitoring systems, WSSNs need to be scalable in terms of coverage area. Sensor nodes are energy‐constrained devices, and hence, many energy‐efficient clustering protocols are developed in the literature. But these methods overload the cluster leaders (CLs) with cluster computation and data communication costs. An improper CL selection may lead to the early death of such nodes and hence does not prolong the network lifetime stability. We propose a fuzzy logic (FL)–based distributed clustering protocol to enhance the energy efficiency of WSSN while maximizing the coverage area. The load of CLs is shared by originators and super‐CLs (SCLs) selected in the network. The wireless link and received signal strength (RSS) are greatly affected by environmental conditions and thus cannot be considered as ideal network parameters. We use FL systems to tackle the uncertainty of such network parameters. The proposed protocol is simulated for different scalable WSSNs. The results indicate that the proposed protocol provides better lifetime stability than the recent conventional protocols. The functionalities of the protocol are proposed considering the recent wireless standards. Hence, the proposed protocol can be suitably implemented for farmland monitoring systems. [ABSTRACT FROM AUTHOR]

Spatial Modulation techniques (SMTs) offer an exceptional trade-off between spectral and energy efficiencies. In this work, we propose a new SMT termed as permutation index-quadrature spatial modulation (PI-QSM), aiming for enhanced spectral efficiency and better average bit error rate (ABER) performance compared to rival SMTs. To enhance spectral efficiency, PI-QSM exploits permutations of active transmit antennas by conveying additional information bits innovatively through indices of active antenna permutations. PI-QSM also alleviates the major constraint in some of the SMTs, where the total number of transmit antennas need to be a power of two. At any time instance, PI-QSM transmits real and imaginary parts of two complex modulated symbols separately using four different active antennas. To avoid any ambiguities at the receiver and to improve the error performance of the overall system, a rotation angle is introduced between the two modulated symbols before transmission. The rotation angle is optimized for different M -quadrature amplitude modulation (QAM) constellations using extensive Monte Carlo simulations. Performance of PI-QSM scheme is analyzed by deriving closed-form expressions for upper bound and asymptotic average bit error probability (ABEP) over Rayleigh fading channels. The Simulation results substantiate the accuracy of analytical analysis and also indicate that the proposed PI-QSM scheme offers better ABER performance than rival SMTs such as QSM and generalized QSM (GQSM). [ABSTRACT FROM AUTHOR]

Multi input multi output (MIMO) based multi-hop relay (MHR) networks has become one of the promising technologies in improving the quality of wireless links. The optimal antenna selection is one of the suitable solutions to overcome the limitations of MIMO scheme. To attain the full benefits of transmitter antenna selection schemes, perfect channel quality information (CQI) is required at the transmitter. The time varying channel and the feedback delay make CQI at the transmitter outdated and also affect the antenna selection process. In this work, we have derived the symbol error probability (SEP) of M-ary quadrature amplitude modulation (QAM) for three different antenna selection schemes by considering the effect of delayed CQI. All these derived expressions are the function of correlation between CQI at the receiver and delayed CQI at the transmitter. The simulation results show that the antenna selection gain decreases with the decrease in correlation. It is also observed that scheme 1 based antenna selection is optimal for different constellations and more suited for MHR network. [ABSTRACT FROM AUTHOR]