In today's scenario, underwater wireless sensor network (UWSN) has raised as a most famous research areas for the researchers due to its advancement in the real world. In UWSNs, the sensor nodes sense the environment, and then this sensed information is conveyed to one of the sink node and finally to the base station for processing. It is a known fact that nearly about 70% of the total earth surface is filled with the water. It is difficult for the humans to get the valuable information from the seabed. Major applications of UWSN are marine surveillance, sea monitoring, deep sea archaeology, oil monitoring etc. Major goal of this work is to provide the broad survey of underwater sensor networks with its application, deployment techniques and routing algorithms. This study also provides a comparative analysis of the deployment techniques and routing algorithms that will aid the researchers to find the research gaps in the deployment and routing techniques. Moreover, some of the UWSN applications also reviewed, which provides varied and valuable information about the UWSN approach. This study presents an overview about the conventional technologies of UWSN and its major focus is to present the significant research approaches towards the UWSNs’ applications, deployment techniques, and routing process.

Timing estimation is the most crucial part of the modulation classification and demodulation of burst signals. The traditional methods in classical cooperative communication fail to provide satisfying accuracy in non-cooperative communication. A novel timing estimation method was proposed in this study, which involves a carefully designed optimisation function constituted by piecewise over code period. Moreover, a closed-form analytical solution of the proposed optimisation problem has been provided, which significantly increases the estimation performance with affordable complexity. In detail, the proposed method demonstrates almost five times higher accuracy than the traditional methods in the low signal-to-noise ratio (SNR) scenario, while approaches the modified Cramer–Rao bound in the high SNR scenario.

Since the analysis of cell coverage faces complex environments in unmanned aerial vehicle base station (UAV-BS) systems, general coverage probability in a typical cell is derived to analyse a UAV-BS multi-tier network, and this coverage probability is closely related with power difference among UAV-BSs, two-dimension (2D) and three-dimension (3D) UAV-BS deployment, and general interference fading models. Especially, closed-form coverage probability expressions are also derived in the form of 2D scenario and 3D scenario, when the interference fading coefficient is assumed to follow a Gamma distribution and an exponential distribution, respectively. It shows that there exists maximum spectral efficiency density (SED) as the BS density increases, and such a BS density achieving the max-SED is independent of noise power, but is affected by various propagation parameters.

Code-based digital signatures suffer from two main drawbacks: large public key size and slow signature generation. Large public key size is inherent in almost all the code-based cryptosystems and other post-quantum alternatives; however, slow signature generation is due to their specific structure. Most of the current code-based signature schemes are constructed based on Courtois, Finiasz, and Sendrier (CFS) signature. CFS uses a counter to produce decodable syndromes or the complete decoding technique that imposes some extra computational cost to the signing algorithm for many choices of codes. In this study, the authors propose an efficient digital signature, PolarSig, which can reduce both public key size and signing time simultaneously. PolarSig uses some specific instances of polar codes that enable us to decode every random syndrome. Moreover, they apply puncturing and randomised omitting of frozen bits to protect the authors’ scheme from commonplace attacks targeting former cryptosystems based on polar codes. Besides, they prove that their signature is existentially unforgeable under a chosen message attack secure in the random oracle model.

In this study, the authors propose a generalised switching protocol (GSP) for increasing the flexibility of energy harvesting (EH) protocol and enhancing the security of amplify-and-forward (AF) multi-antenna relaying system. The proposed GSP-based relaying [generalised switching relaying (GSR)] system is established with target node assisted interference and EH technologies. In phase I, while the source transmits certain signal to the relay, the destination transmits an artificial noise to interfere the passive eavesdropper. In this phase, the relay harvests energy from the two nodes. In phase II, the relay node processes the two different received signals, which are from the source and destination, then AF them by utilising the harvested energy. The authors also derive a new analytical formula for the proposed protocol on ergodic secrecy capacity. The effect of the number of relay antennas N, the source transmitted power , the destination transmitted power and EH efficiency factors and on ergodic secrecy capacity are investigated. The simulation results show that as N, , , and increase, the ergodic secrecy capacity of GSR system increases accordingly. Moreover, the GSR protocol can provide higher ergodic secrecy capacity than both time switching relaying and power splitting relaying protocols.

With the development of 5G network and big data and the popularity of mobile intelligent devices, the opportunistic social network has been further developed. At present, several existing routing algorithms based on node similarity use the context information of the node to select the best relay node. However, most opportunistic social algorithms only consider the social properties of nodes and ignore the importance of the similarity of the moving trajectories of the nodes. The transmission opportunity of messages in the opportunity social network is generated by the movement of the nodes, so this feature must betaken into account in the designing of the routing algorithm. Therefore, this study proposes a routing algorithm based on the triangular fuzzy layer model and multi-layer clustering for the opportunistic social network. In this study, the authors use the fuzzy analytic hierarchy process model to analyse the social similarity and trajectory similarity to determine the best message transmission node. This study compares the other four opportunistic social network routing algorithms in the simulation environment. In general, among the five routing algorithms, the transmission rate of the TFMC algorithm is the best. The average end-to-end delay and average network overhead are also the lowest.

Beacon-based indoor positioning is popular in recent years. In this work, the authors aim to enhance the positioning accuracy by proposing signal power ranking (SPR) and solving related optimisation-based deployment problem of beacons using wireless communication and Bluetooth 4.0 Bluetooth low-energy network technologies. The authors first adopt grid-based field to be the proposed deployment field. Second, they convert the received signal strength indicator (RSSI) to several levels called SPR. Third, an optimisation-based model for deployment problem of beacons in indoor positioning is proposed on the basis of the above two considerations. The proposed model is to minimise the number of beacons required under some fundamental conditions including full coverage and full discrimination, respectively. Finally, the algorithm of simulated annealing is applied to solve the linear programming problem in this model. By the optimal results, the user can obtain a vector table of RSSI for each location efficiently in the test field. On the other hand, the user in the test field can receive the beacon RSSI value at the same time. In order to determine the user's location, the received beacon RSSI value is compared with the values in the vector table.

In recent years, orthogonal frequency division multiplexing with index modulation (OFDM-IM) has been proposed due to its extra diversity gain. Specially, OFDM with all index modulation (OFDM-AIM) was proposed, which removed symbol bits and enhanced the diversity order compared to typical OFDM. However, the security issue of OFDM-AIM has not been given full attention. This paper proposes an encrypted subblock design aided OFDM with all index modulation (ESD-OFDMAIM) scheme to enhance physical layer security. Firstly, an encryption process of subblock design was put forward, which creates a random look-up table and thus the mapping rule of ESD-OFDM-AIM between information bits and subblock realisations becomes random and time varying. Moreover, the scrambling and rotation encryption based on chaotic sequences from channel state information is utilised to prevent the eavesdropper from stealing the information via wireless channel. For eavesdroppers, parameters of ESD-OFDM-AIM such as spectral efficiency (SE), constellation points and the length of look-up table are concealed by the encryption. Finally, analyses of attack models and the information entropy of constellations are also provided to measure the security of ESD-OFDM-AIM. Simulation results show that ESD-OFDM-AIM can effectively improve the system security without the affecting bit error rate performance.

This paper develops new suboptimal antenna selection (AS) schemes, majority based transmit antenna selection/maximal ratio combining (TAS-maj/MRC) and joint transmit and receive antenna selection (JTRAS-maj), in a multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) network. The impact of the channel estimation errors (CEEs) and feedback delay (FD) on the performance of the network is studied in Nakagami-m fading channels. First, the outage behavior of the network is investigated in a unified manner for the proposed AS schemes by deriving the closed-form expression of the exact outage probability (OP). Next, in the presence of the CEEs and FD, the corresponding upper bound of the OP is obtained. The OP expression in high signal-to-noise ratio region is then provided to illustrate an error floor value in the presence of the CEEs and FD as well as diversity and array gains in the absence of the CEEs and FD. Finally, the analytical results in the presence and absence of the CEEs and FD are verified by the Monte Carlo simulations. The numerical results show that the proposed majority based AS schemes are superior to both max-max-max and max-min-max based AS schemes and the system performance is more sensitive to the CEE than FD.

To alleviate the spectrum scarcity, the unlicensed 60 GHz band has raised increasing concerns due to its continuous large bandwidth. Considering IEEE 802.11ad/ay has already been deployed in this millimetre-wave band, the coexistence issues with new radio-based access to unlicensed spectrum should be weighed when deploying fifth generation (5G) network. Fortunately, the directional transmission on beams is able to reduce interference significantly, so beam selection can be combined with power control. To maximise spectrum efficiency (SE) of the 5G network while ensuring a friendly coexistence, the authors formulate an optimisation problem by jointly considering beam selection and resource allocation. More specifically, they design a spectrum planning mechanism to reduce the interference between 5G and WiFi, and then a block coordinate descent method is used to determine the user association, beam selection and power control for 5G users, while limiting the interferences to WiFi devices. Simulation results verify the effectiveness of the proposed algorithm in terms of complexity, convergence and SE.

In this study, a resource allocation problem considering physical layer security and power consumption for cognitive relay networks is studied. In a secondary network, the ratio of secret rate to power consumption is defined as a secret rate per watt (SRW). Fixed circuit power, dynamic circuit power, and transmit power are all considered in the power consumption model. Under the constraints of the maximum total transmit power of secondary user transmitters and relay nodes, minimum secret rate requirement of secondary user receiver and tolerable interference threshold of each primary user receiver, the authors propose a SRW maximisation algorithm to maximise SRW. The resource allocation problem is formulated as a non-linear fractional programming and it is transformed into an equivalent subtraction based on the Dinkelbach method. They incorporate the non-convex constraints into the objective function to convert the feasible region into a convex set and achieve an optimal resource allocation scheme with the nested loop iteration algorithm through the Lagrange dual theory and the difference of convex programming. By the Dinkelbach method and the nested loop iteration algorithm, the optimal SRW is obtained. Simulation results demonstrate the effectiveness and the out-performance of the proposed algorithm comparing with other algorithms.

The authors study the spectral efficiency (SE) of a multi-cell massive multiple-input multiple-output (MIMO) system with a spatially correlated Rician channel. The correlation between least squares (LS) estimator and its error complicates SE analysis, since signal and interference components become cross-correlated, too. Minimum mean square error (MMSE) estimators do not suffer from this burden. In some previous works, a proper part of the signal is referred to interference, which makes them cross-uncorrelated, and leads to a SE lower bound. In their modified approach, the authors extract and refer the cross-correlated part of interference to the signal to attain this objective. Here, they use this approach for calculating the instantaneous SE of maximum ratio combining (MRC) detector under LS and MMSE estimation methods. They further derive closed-form approximations of their ergodic SE. This approach is also applicable to other linear channel estimators or data detectors. Numerical results show that achievable SE surpasses that of the previous approach. Moreover, they show that their approximation is close enough to Monte Carlo simulation results, especially at the high number of the base station antennas.

The increase of power consumption around the world puts forward higher requirements for the robustness of the power grid. As a critical application of the smart grid, demand response (DR) has significant impacts on the stable operation of the grid. The source–grid–load system (SGLS) in Jiangsu Province of China has implemented three different types of DR. This study aims at promoting the survivability of the DR communication network, which can enhance the reliability of DR. In response to concurrent dual-link failure, the authors first present a capacity expansion algorithm with the minimum distance to enhance the topology of the DR communication network. Next, they design a multipath routing algorithm based on pre-estimation to configure multiple paths for every DR terminal according to the characteristics of the DR service. Then they propose a link capacity sharing algorithm for multipath to reduce the communication network cost for DR. Simulations demonstrate the proposed algorithm can improve survivability and reduce the cost of the DR communication network. Furthermore, they compare the multipath configuration algorithms in different topology enhancement schemes, which can give some suggestions on the construction of SGLS in the future.

In opportunistic networks, the path connecting two nodes is not continuous at any time instant. In such an environment, routing is an extremely taxing word owing to the ever-changing nature of the network and random connections between nodes. Routing in such networks is done by a store carry forward mechanism, in which local information is used to make opportunistic routing decisions. In this study, the authors present a novel dynamic and intelligent self-learning routing protocol that is an improvement of the history-based routing protocol for opportunistic (HiBOp) networks. The proposed method presents a novel solution for the estimation of average latency between any two nodes, which is used along with reinforcement learning to dynamically learn the nodes' interactions. Simulation results on a real mobility trace (INFOCOM 2006) show that latency-aware reinforced routing for opportunistic network applied to HiBOp outperforms the original HiBOp protocol by 14.4% in terms of delivery probability, 15% in terms of average latency and 34.7% in terms of overhead ratio.

This study concentrates on the optimal resource allocation problem in a wireless sensor network with rare spectrum resources and improper topology structure. To explore the interdependence of various resources and achieve better anti-interference property, the authors analyse the problem of joint power control and channel allocation based on bit error rate (BER) model and energy consumption model. Specifically, low-energy consumption and BER are both crucial design objectives for a number of multi-hop wireless network applications with constrained network resources and battery-powered sensors. As these two objectives that influenced by power control and channel allocation are conflicting with each other, it becomes important to achieve the trade-off between them. Aiming at the aforementioned problem, this study formulates a multi-objective optimisation model to minimise BER and energy consumption under the constraints of link interference, link capacity, and network connectivity. On the basis of this model, they propose a distributed resource allocation optimisation algorithm based on particle swarm optimisation (DRAPSO) to achieve Pareto optimal solutions. Furthermore, the information complexity and time complexity of DRAPSO are theoretically analysed. The simulation results show that DRAPSO can effectively increase network capacity, decrease energy consumption, and BER. Besides, the trade-off of multi-performances can be significantly achieved.

The coordination between aerial and ground nodes has enhanced the versatility and quality of the traditional networks. The application of aerial systems in mission-critical operations, as well as civilian applications, brings in the context of safeguarding unmanned aerial systems (UAS) from malicious attackers. This study discusses the threats and attacks mounted on UAS, alongside the challenges introduced by the unmanned aerial vehicle (UAV) network structure itself. A framework for safeguarding UAS against malicious attackers and recovering the rogue UAVs is proposed in the study. The proposed framework enforces a dynamic conceptual grid-based layout over the actual geographical deployment. The dynamically shuffling grid ascertains the security of transmission channels, as every time the grid is shuffled periodically or based on abnormal behaviour, the safety paradigm is reinitiated. Public key cryptographic algorithms are deployed for securing the communication links. Neural networks-based predictions are used for detecting abnormality in behavioural, statistical, and mobility patterns. Principal component analysis based on multivariate statistical analysis is used for detecting outliers in the aerial network environment. The behaviour prediction and outlier detection algorithms significantly improve the overall performance of the network and provide immunity against the intruders with reduced false positives, high accuracy, and better detection rate.

In this study, the performance of wirelessly powered relay-aided non-orthogonal multiple access networks is investigated in terms of outage probability. Specifically, two relay selection strategies, i.e. two-stage relay selection (TRS) and maximum energy harvesting relay selection (MEHS), and two energy harvesting scenarios, i.e. time switching (TS) and power splitting (PS) are considered. In each setup, outage probabilities' analytical expressions and their asymptotics are derived. Monte-Carlo simulations are also carried out to verify the correctness of the analysis. The results show that regardless of relay selection and energy harvesting strategies, increasing transmit power can improve the proposed system performance. However, TRS can achieve a full diversity order, while MEHS has a unit diversity order. Besides, the results recommend parameter selections of PS and TS coefficients for optimal performance in term of outage probability.

In this study, the authors first propose an analytical model for investigating the impacts of power allocation (PA) and cell density allocation (CDA) on coverage efficiency (CE) of heterogeneous wireless cellular networks (HWCNs) under limited resources. It is shown that the interference among cells that belong to different tiers is reduced significantly in higher path loss environment and results in a higher coverage. The network coverage of the HWCN can be further extended with the deployment of a higher cell density in a more lossy environment. This accordingly leads us to develop an optimisation problem (OP) to maximise the CE by optimising the PA and CDA under the constraint of limited cell power and total power available in the downlink HWCN. In particular, they proposed a two-stage approach for solving the OP to sequentially obtain the heuristic value of the CDA and PA due to complicated objective function along with various involved parameters. Numerical results reveal that the coverage obtained by the heuristic solution at the first-stage is significantly improved with lower power than the conventional approach. Furthermore, an enhanced overall CE is achieved for all cases of the power constraint when applying fully two stages in their proposed algorithm.

The lightening growth in Internet of Things (IoT), forced the deployment of various types of applications. Due to the likelihood of sensor failures, the applications of IoT cannot be benefited. These node failures can transform the fully-connected network into multiple disjoint sub-networks, named network partitioning problem where the nodes fail to perform intended services. The federation of these isolated network segments is essential. In this study, a distributed approach FRTP (Failure Recovery using Relay Nodes at Torricelli points ()) is proposed, where the restoration of the disconnected network is initiated using the relay nodes (RNs). The performance of FRTP is evaluated using network simulator tool NS-2 and the experimental results show that it achieves better performance than the existing approaches. The main goal of the proposed approach is to minimise the number of HRNs (Healing Relay Nodes), APL (Average path length), recovery time of the network and to maximise the average node degree. The average improvement in minimisation of number of HRN, APL, and recovery time of the network for radio range of 100 m are 21.57, 13.23, and 9.96%, respectively, and the maximisation of average node degree is 9.83%.

This study proposes a novel memetic algorithm (MA) for the blind equalisation of digital multiuser channels with direct-sequence/code-division multiple-access sharing scheme. Equalisation involves two different tasks, the estimation of (i) channel response and (ii) transmitted data. The corresponding channel model is first analysed and then the MA is developed for this specific communication system. Convergence, population diversity and near–far resistance have been analysed. Numerical experiments include comparative results with traditional multiuser detectors as well as with other nature-inspired approaches. The proposed receiver is proved to allow higher transmission rates over existing channels while supporting stronger interferences as well as fading and time-variant effects. Required computation requisites are kept moderate in most of the cases. The proposed MA saves 80% of computation time with respect to a standard genetic algorithm and about 15% with respect to a similar two-stage MA, while keeping a statistically significant higher performance. Besides, complexity increases only by a factor of 5, when the number of active users doubles, instead of found for the optimum maximum likelihood algorithm. The proposed method also exhibits high near–far resistance and achieves accurate channel response estimates, becoming an interesting and viable alternative to so far proposed methods.

This study proposes a chaos-based security model applied to the physical (PHY) layer of visible light communication (VLC) systems in accordance with the IEEE 802.15.7 standard. The proposed model employs a chaotic signal generated by a Colpitts oscillator to encrypt the header of IEEE 802.15.7 VLC frames in the PHY layer to prevent eavesdropping, traffic analysis and error function attacks. The encryption method employed here is chaotic inclusion or embedding, which is known as one of the most secure chaos-based approaches. Thus, the essential information pertaining to the employed chaotic oscillator, i.e. its structure, parameter set, the utilised modulation and synchronisation methods is not visible or traceable to the eavesdropper. Moreover, the unencrypted payload is extended by an additional number of random padding bits which can only be determined by decrypting the header of the VLC frame hence the payload is unrecognisable to eavesdroppers though it has not been encrypted. At the legitimate receiver side, the received IEEE 802.15.7 frames are successfully recovered by removing the chaotic wave using chaotic synchronisation techniques. The simulation results show that the encrypted header and the unencrypted payload of the IEEE 802.15.7 frames are well protected and successfully recovered by legitimate receivers.

With the increasing demand for high-speed mobile transmissions for 5G networks, the cooperative relay-aided non-orthogonal multiple access (CR-NOMA) has been highly considered. An efficient and reliable CR-NOMA not only depends on the network mechanism but on the network coding strategy at the relay. Even though conventional strategies have broadly been studied, they suffer from noise accumulation and interference. Lately, the compute-and-forward (CpF) strategy has been identified as a potential technique to mitigate interference and enhance outage probability. In this study, the authors present a mathematical formulation to examine the performance of CpF on downlink CR-NOMA. In the proposed formulation, a two-stage downlink cooperative relay network is considered to obtain analytical closed-form expressions of outage probability and bit error rate. The outage probabilities and bit error rates of existing relaying strategies are compared regarding the network model. The theoretical analysis shows that CpF requires half the number of relays desirable in amplify-and-forward and decode-and-forward strategies to achieve a proportionate outage probability in CR-NOMA. Finally, we present results to show that at a lower signal-to-noise ratio, the integration of CpF and NOMA enhances error performance irrespective of the number of users.

Cooperative non-orthogonal multiple access (NOMA) system has demonstrated the ability to improve spectral efficiency, massive connectivity, and spectral efficiency. In this study, the authors propose a novel dual-ordered NOMA in a decode and forward (DF) relaying network, where a dynamic channel ordering is considered at both source and relay nodes during the symbol transmission period. The proposed NOMA system uses instantaneous channel gain as the channel state information (CSI) measure for channel ordering of the NOMA users in contrast to the more popular statistical CSI measures. We have established the efficiency of the proposed method through investigation of three different performance metrics: outage probability, ergodic rate analysis, and fairness of the proposed scheme in a downlink NOMA network with DF relaying. The results obtained show superior performance of the double ordered NOMA as compared to the single-ordered NOMA.

In this study, the authors have developed an analytical model for reducing the peak-to-average-power ratio (PAPR) using non-linear companding transform (NCT) based on inverse hyperbolic sine function. As a consequence of non-linear transform, this study compensates the system bit error rate (BER) degradation with the help of an error efficient hybrid modulation. By means of an inflexion point and companding parameter, more design flexibility is achieved; as a result, a trade-off between PAPR and BER has reasonably been more precise. To the best of the authors’ awareness, no findings have yet been reported on the performance evaluation of the optical orthogonal frequency division multiplexing (OOFDM) system using a hybrid modulation technique. To find out the advantages of hybrid modulation with NCT, the authors inspect the nature of PAPR reduction, and BER improvement through numerical simulations. The numerical BER results exhibit roughly 3 dBm decay in the power efficiency of hybrid modulation with NCT over discrete Fourier transform (DFT) precoding technique. On the other hand, the NCT technique with hybrid modulation has 6 dB less PAPR than the DFT precoding technique.

We consider, as a game, the competition between sensors' transmissions in a structure-free wireless sensor network. They contemplate two nodes at the same level strategically optimising their decisions over a finite set of strategies. Specifically, they consider two strategies are available to each node. Nodes can choose to transmit to keep the network updated, but at the risk of not sensing during the transmission time and the potential of sending repeated information if other nodes have already transmitted that information. Nodes can choose to sense the environment to detect new events, but this strategy leaves the network with outdated information if all nodes adopt it. As a result, nodes have to strategically make their decisions depending on the nodes' parameters, the importance of information, and the locations of the head nodes. They tackle this decision-making problem using two game theoretic models: a non-cooperative two-player game model and a potential game model. They derive the Nash equilibria (NE) and highlight their existence conditions. Finally, they use learning algorithms that use local information at each node to reach the NE. These algorithms are the fictitious play (FP) algorithm and a modified FP that is inspired by the cumulative proportional reinforcement algorithm.