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This paper provides a comprehensive performance comparison between a current robust military waveform; namely, MIL-STD-188-110D, Waveform 0, and a filter bank multicarrier spread-spectrum (FBMC-SS) waveform proposed for communications through ionospheric/skywave HF channels. Waveform 0 is effectively a direct sequence spread spectrum waveform that uses Walsh multi-codes to enhance the information transmission rate. It may thus be referred to as Walsh-DSSS. FBMC-SS, on the other hand, makes use of filter banks to provide excellent performance when the received signal is subject to partial band interference. Successful application of FBMC-SS for communications across skywave HF channels has been previously demonstrated, both theoretically and through experimental work. However, very little has been done to contrast FBMC-SS against Walsh-DSSS. The goal of this paper is to first add new features to FBMC-SS to bring it on par with Walsh-DSSS. These features include: (i), introduction of multi-codes that achieve a comparable (or better) data rate to Walsh-DSSS; and (ii), addition of a scrambling step applied to the multi-codes to make the receiver detection robust against widely spread multipaths. With this established, in the second part of the paper, we examine the performance of the developed FBMC-SS against Walsh-DSSS when both are applied for communications across skywave HF channels. The two waveforms are compared both through a theoretical study and through experimental works across several skywave channels ranging from hundreds to thousands of kilometers. [ABSTRACT FROM AUTHOR]

This paper is devoted to software-defined radio (SDR) implementation of frequency modulated antipodal chaos shift keying (FM-ACSK) transceiver and presents results of prototype testing in real conditions. This novel and perspective class of spread-spectrum communication systems employs chaotic synchronization for the acquisition and tracking of the analog chaotic spreading code and does not need resource-demanding cross-correlation. The main motivation of the given work is to assess the performance of FM-ACSK in real conditions and demonstrate that chaotic synchronization can be considered an efficient spread-spectrum demodulation method. The work focuses on the real-time implementation aspects of the modulation-demodulation algorithms, forward error correction (FEC) and symbol timing synchronization approach in MATLAB Simulink. The performance of the presented prototype is assessed via extensive testing, which includes measurement of bit error ratio (BER) in single-user and multi-user scenarios, estimation of carrier frequency offset (CFO) impact and image transmission over-the-air between two independent sites and comparison with classical frequency hopping spread spectrum (FHSS). The paper shows that the presented class of the spread spectrum communication systems demonstrates good performance in low signal-to-noise ratio (SNR) conditions and in terms of BER significantly outperforms the classic spread-spectrum modulation schemes which employ correlation-based detection. [ABSTRACT FROM AUTHOR]

This paper proposes a multilevel cyclic shift index modulation aided differential chaotic shift keying (MCSI‐DCSK) system to improve data rate and energy efficiency. In the MCSI‐DCSK system, the bit stream is divided into blocks with N(M+1)$N(M+1)$ bits which are further divided into N groups equally. In each group, the first M bits are mapped into an index of cyclic shift in the chaotic reference sequence, while the last bit is used to modulate the shifted chaotic reference sequence. Finally, the all modulated shifted chaotic reference sequences are superimposed to form the information‐bearing signal. So the proposed system improves the data rate. The analytical bit‐error‐rate (BER) expressions of the MCSI‐DCSK system are derived over additive white Gaussian noise and multipath Rayleigh fading channels and validated via simulations. In addition, the BER performance of the proposed system is compared with other non‐coherent, chaotic communication systems. Simulation results indicate that the MCSI‐DCSK system has better performance in data rate and BER. [ABSTRACT FROM AUTHOR]

As Internet users interacting with their different friends in different social networks, the de-anonymization problem has been raising improving concern. Since the assailants may de-anonymize a social network by matching it with a correlated sanitized network and identifying anonymized user identities, multifarious arts study on the theoretical conditions or practical algorithms for correctly de-anonymizing a social network. Except for the structural information of these social networks, there has also been bounteous works taking advantage of some pre-identified seed nodes for reference in the anonymized network. In this paper, we systematically probe the theoretical conditions and algorithmic approaches for correctly matching two different-sized social networks by leveraging the multi-hop neighborhood relationships. A limited number of seeds are also taken into consideration as auxiliary information. To this end, we introduce the de-anonymization problem with the aid of the collectiveness and the collective adjacency disagreements, which are the collection of disagreements of different multi-hop adjacency matrices. We theoretically demonstrate that minimizing the collective adjacency disagreements can help match two social networks even in a very sparse circumstance, as it significantly enlarges the difference between the mismatched node pairs and the correctly matched pairs. Besides, the seeds is proved to bring positive influence in improving the de-anonymization accuracy. Algorithmically, we relax the domain of the matching function to continuum and adopt the conditional gradient descending method on the collective-form objective, to efficiently minimize the collective adjacency disagreements of two networks. We conduct tremendous experiments on different networks with or without seeds, the results of which return desirable de-anonymization accuracies and reveal the advantages of the collectiveness: the collectiveness manifests rich structural information, thereby most nodes can be correctly matched with their correspondences even in some sparse networks, where merely utilizing the 1-hop adjacency relationships might fail to work. [ABSTRACT FROM AUTHOR]

This paper presents techniques that are expected to improve the bit error rate (BER) performance of Unmanned Aerial Vehicles (UAVs) communication systems. The decode-and-forward (DF)-based cooperative multi-hop Rician network using space shift keying (SSK) modulation is employed for this purpose. The SSK modulation and cooperative communication are merged and used together. This enhances the BER performance for multiple-input multiple-output (MIMO) channels, thus accentuating its significance as an important technique for consistently reliable communication methodology while, at the same time, eliminating wastage of energy. The new technique is named as high performance (HP) due to not only BER performance improvement but also increase of the diversity of the communication system. This new model is further used for multi-hop networks and the resulting BER characteristics are assessed for possible enhanced performance in Rician channels. The paper also showcases the generalized-n-hop BER equation for various multi-hop DF-based cooperative communication systems in diverse UAV models. The Monte Carlo simulations further confirm the theoretical results that already exist for transmit-receive antennas. This work also underlines the fact that the number of hops in a communication system has no bearing whatsoever on the BER performance diversity value. [ABSTRACT FROM AUTHOR]

Infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communications are often combined to extend the connectivity and coverage in the Intelligent Transportation System (ITS) and its applications, e.g., augmented reality, real-time parking management and online shopping. Through multi-hop I2V and V2V communications, requesting vehicles are always connected to road side units (RSUs) even when they do not reside within the RSUs’ coverage range. However, there may be not adequate network resource for several I2V and V2V links when multiple vehicles request services simultaneously. In this paper, we propose a joint frequency scheduling and power control scheme to enhance connectivity in multi-hop I2V/V2V networks. We associate I2V and V2V links with tuple-links, then formulate an NP-hard problem in which a frequency scheduler and a power controller are jointly designed for the tuple-links. The NP-hard problem is decomposed into two separate subproblems by employing the delayed column generation technique. Then, we employ a method for linear programming and a greedy algorithm to address these subproblems. Through numerical experiments with practical parameter settings, we demonstrate the proposed scheme outperforms several existing ones in terms of connectivity enhancement, measured by the service resumption number and average achieved throughput. Furthermore, the efficiency of our scheme is further enhanced when the number of available channels is high, and buffer size equipped to the requesting vehicles is large. [ABSTRACT FROM AUTHOR]

Vehicular ad hoc networks (VANETs) have attracted increasing attention in cross-regional communication. The interconnection between VANETs and satellite networks expands their communication range. To improve the transmission performance of heterogeneous networks composed of VANETs and satellite networks, this paper proposes an end-to-end transmission control scheme for satellite network-assisted VANETs, analyzes the bandwidth delay product of multihop VANETs through heterogeneous networks, and establishes a transmission control model applicable to cross-regional environments. To address the long delay and high bit error rate in heterogeneous networks, the model designs the congestion window in the slow start and congestion avoidance of the transmission scheme. The data transmission volume is increased in the slow start, and various packet losses are distinguished in congestion avoidance. The experimental results show that the scheme can achieve good transmission performance in heterogeneous networks composed of VANETs and satellite networks. The results show that VANETs data can be effectively transmitted in heterogeneous networks. Compared with the traditional transmission scheme, this simple and practical end-to-end transmission control scheme can improve speed by 83.49 kbps and reduce transmission duration time of FTP server by $4.72\times 10^{3}$ s. The results of this study provide a reference for massive data transmission in heterogeneous networks of VANETs and satellite networks. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Signal Processing is the property of Journal of Signal Processing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Hop count distribution (HCD), generally formulated as a discrete probability distribution of the hop count, constitutes an attractive tool for performance analysis and algorithm design. This paper devotes to deriving an analytical HCD expression for a finite ad hoc network under the minimum hop-count routing protocols. Formulating the node distribution with binomial point process, the network is provided as a bounded area with all nodes randomly and uniformly distributed. Considering an arbitrary pair of source node (SN) and destination node, an innovative and straightforward definition is presented for HCD. In order to derive HCD out, an original mathematical framework, named as the equivalent area replacement method (EARM), is proposed and verified. Under the EARM, HCD is derived by first considering the special case where SN locates at the network center and then extending to the general case where SN is randomly distributed. For each case, the accuracy of our HCD model is evaluated by simulation comparison. Results show that our model matches well with the simulation results over a wide range of parameters. Particularly, the derived HCD outperforms the existing formulations in terms of the Kullback Leibler divergence, especially when SN is randomly distributed. [ABSTRACT FROM AUTHOR]

In non‐cooperative scenarios, the spreading sequences or waveforms of the direct sequence spread spectrum (DSSS) signals is unknown to the receiver. This paper focuses on addressing the problem of blind estimation of the spreading waveform under multipath channels. In the scenario of direct signal path transmission, the spreading sequences can be directly obtained based on the estimated spreading waveforms. However, in the presence of multipath channels, the spreading waveform becomes the convolution of the spreading sequence and channel response, thus deconvolution should also be performed after estimating the spreading waveforms. In order to perform blind despreading and deconvolution of asynchronous multiuser DSSS signals under multipath channels, the authors propose to exploit the finite symbol characteristics of information and spreading sequences and then the iterative least square with projection method is adopted. Besides, the Cramer‐Rao bound of spreading waveforms is derived in such a circumstance as a performance benchmark. The effectiveness of the proposed method is verified via simulation experiments. [ABSTRACT FROM AUTHOR]

The problem of disseminating continuous data flow from a given source node to all other network nodes is known as the dynamic broadcast problem, which is also a fundamental problem in multi-hop wireless networks (e.g., wireless ad hoc and sensor networks). Due to link unreliability and node mobility, the topology of a network typically changes with time. Little work has been conducted to address the dynamic broadcast problem in time-varying wireless multi-hop networks, especially under the popular Signal-to-Interference-plus-Noise-Ratio (SINR) interference model. In this paper, we study the dynamic broadcast problem in SINR-based time-varying directed acyclic multi-hop wireless networks formed by point-to-point wireless links. We consider the SINR-based link transmission rate model involved in the slot-based link scheduling. We first prove a tight upper bound for the broadcast capacity of the multi-hop wireless networks under study. We then propose an online max-weight Throughput-Optimal Dynamic Broadcast algorithm (TODB) which performs link weight allocation, link scheduling, and data forwarding for each time slot according to the current network connectivity and data reception rates of nodes. We derive the throughput-optimality of the TODB algorithm by proving that the broadcast throughput of TODB can achieve the aforementioned upper bound of the broadcast capacity. We evaluate the performance of TODB in terms of throughput and latency via simulations and the results validate its effectiveness. [ABSTRACT FROM AUTHOR]

This paper investigates schemes for multihop scheduling and power control for vehicle-to-vehicle (V2V) multicast communication, taking into account the effects of both co-channel interference and adjacent channel interference, such that requirements on latency or age of information (AoI) are satisfied. Optimal performance can be achieved by formulating and solving mixed Boolean linear programming (MBLP) optimization problems for various performance metrics, including network throughput and connectivity. Fairness among network nodes (vehicles) is addressed by considering formulations that maximizes the worst-case network node performance. Solving the optimization problem comes at the cost of significant computational complexity for large networks and requires that (slow) channel state information is gathered at a central point. To address these issues, a clustering method is proposed to partition the optimization problem into a set of smaller problems, which reduces the overall computational complexity, and a decentralized algorithm that does not need channel state information is provided. [ABSTRACT FROM AUTHOR]

In this paper, we consider the update bandwidth in distributed storage systems (DSSs). The update bandwidth, which measures the transmission efficiency of the update process in DSSs, is defined as the average amount of data symbols transferred in the network when the data symbols stored in a node are updated. This paper contains the following contributions. First, we establish the closed-form expression of the minimum update bandwidth attainable by irregular array codes. Second, after defining a class of irregular array codes, called Minimum Update Bandwidth (MUB) codes, which achieve the minimum update bandwidth of irregular array codes, we determine the smallest code redundancy attainable by MUB codes. Third, the code parameters, with which the minimum code redundancy of irregular array codes and the smallest code redundancy of MUB codes can be equal, are identified, which allows us to define MR-MUB codes as a class of irregular array codes that simultaneously achieve the minimum code redundancy and the minimum update bandwidth. Fourth, we introduce explicit code constructions of MR-MUB codes and MUB codes with the smallest code redundancy. Fifth, we establish a lower bound of the update complexity of MR-MUB codes, which can be used to prove that the minimum update complexity of irregular array codes may not be achieved by MR-MUB codes. Last, we construct a class of $(n = k + 2, k)$ vertical maximum-distance separable (MDS) array codes that can achieve all of the minimum code redundancy, the minimum update bandwidth and the optimal repair bandwidth of irregular array codes. [ABSTRACT FROM AUTHOR]

The objective of this study is to evaluate Grassmannian constellations combined with a spread spectrum multiple access scheme for underwater acoustic mobile multiple access communication systems. These communication systems enable the coordination of a fleet of Autonomous Underwater Vehicles (AUVs) from a surface or bottom control unit, e.g., a boat. Due to its robustness against phase rotation, the demodulator of Grassmannian constellations uses non-coherent detection, and the main advantage of such modulation lies in the spectrum efficiency gain with respect to conventional differential modulation. The communication system under study in this paper consists of (i), at the transmitter side, a Grassmannian modulation used in an orthogonal spread spectrum multiple access scheme called Multiuser Hyperbolic Frequency Modulation (MU-HFM) and (ii), at the receiver side, a non-coherent array decoder. The modulation and demodulation are presented as well as the considered spreading sequences. Finally, performances of the proposed transmission scheme are evaluated over replayed underwater acoustic channel responses collected at sea by a multi-sensor acoustic acquisition system. [ABSTRACT FROM AUTHOR]

In this paper, we aim to improve the connectivity, scalability, and energy efficiency of machine-type communication (MTC) networks with different types of MTC devices (MTCDs), namely Type-I and Type-II MTCDs, which have different communication purposes. To this end, we propose two transmission schemes called connectivity-oriented machine-type communication (CoM) and quality-oriented machine-type communication (QoM), which take into account the stochastic geometry-based deployment and the random active/inactive status of MTCDs. Specifically, in the proposed schemes, the active Type-I MTCDs operate using a novel Bernoulli random process-based simultaneous wireless information and power transfer (SWIPT) architecture. Next, utilizing multi-user power-domain non-orthogonal multiple access (PD-NOMA), each active Type-I MTCD can simultaneously communicate with another Type-I MTCD and a scalable number of Type-II MTCDs. In the performance analysis of the proposed schemes, we prove that the true distribution of the received power at a Type-II MTCD in the QoM scheme can be approximated by the Singh-Maddala distribution. Exploiting this unique statistical finding, we derive approximate closed-form expressions for the outage probability (OP) and sum-throughput of massive MTC (mMTC) networks. Through numerical results, we show that the proposed schemes provide a considerable sum-throughput gain over conventional mMTC networks. [ABSTRACT FROM AUTHOR]

Multihop relaying is a potential technique to mitigate channel impairments in optical wireless communications (OWC). In this paper, multiple fixed-gain amplify-and-forward (AF) relays are employed to enhance the OWC performance under the combined effect of atmospheric turbulence, pointing errors, and fog. We consider a long-range OWC link by modeling the atmospheric turbulence by the Fisher-Snedecor ${\mathcal {F}}$ distribution, pointing errors by the generalized non-zero boresight model, and random path loss due to fog. We also consider a short-range OWC system by ignoring the impact of atmospheric turbulence. We derive novel upper bounds on the probability density function (PDF) and cumulative distribution function (CDF) of the end-to-end signal-to-noise ratio (SNR) for both short and long-range multihop OWC systems by developing exact statistical results for a single-hop OWC system under the combined effect of ${\mathcal {F}}$ -turbulence channels, non-zero boresight pointing errors, and fog-induced fading. Based on these expressions, we present analytical expressions of outage probability (OP) and average bit-error-rate (ABER) performance for the considered OWC systems involving single-variate Fox's H and Meijer's G functions. Moreover, asymptotic expressions of the outage probability in high SNR region are developed using simpler Gamma functions to provide insights on the effect of channel and system parameters. The derived analytical expressions are validated through Monte-Carlo simulations, and the scaling of the OWC performance with the number of relay nodes is demonstrated with a comparison to the single-hop transmission. [ABSTRACT FROM AUTHOR]

In this paper, we consider a wireless multihop device-to-device (D2D) based mobile edge computing (MEC) system, where the destination wireless device (WD) is scheduled to compute nomographic functions. Under the MapReduce framework and motivated by reducing communication resource overhead, we propose a new multi-level over-the-air (OTA) aggregation scheme for the destination WD to collect the individual partially aggregated intermediate values (IVAs) for reduction from multiple source WDs in the data shuffling phase. For OTA aggregation per level, the source WDs employ a truncated channel-inverse structure multiplied by their individual transmit coefficients in transmission over the same time-frequency resource blocks, and the destination WD finally uses a receive filtering factor to construct the aggregated IVA. Under this setup, we develop a unified transceiver design framework that minimizes the mean squared error (MSE) of the aggregated IVA at the destination WD subject to the source WDs’ individual power constraints, by jointly optimizing the individual transmit coefficients of the source WDs and the receive filtering factor of the destination WD. The formulated power-constrained MSE minimization problem is non-convex. First, based on the primal decomposition method, we derive the closed-form solution under the special case of a common transmit coefficient. This shows that the common transmit coefficient of the source WDs is determined by the minimal transmit power budget among them. Next, for the general case, we transform the original problem into a quadratic fractional programming problem, and then develop a low-complexity algorithm to obtain the (near-) optimal solution by leveraging Dinkelbach’s algorithm along with the Gaussian randomization method. Numerical results are provided to demonstrate the significant performance gains achieved by the proposed multi-level OTA aggregation scheme over various existing schemes. [ABSTRACT FROM AUTHOR]

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The multi-hop unmanned aerial vehicle (UAV) network can serve as data relays where ground users (GUs) do not have reliable direct connections to the base station (BS). Existing works mainly focus on simple dual-hop system. In this paper, we investigate the packet routing problem in a multi-hop UAV relay network to minimize the data transmission time and enhance the network throughput. However, the dynamic network topology due to UAV mobility makes the packet routing challenging since the limited communication range of each UAV leads to volatile wireless connection. Moreover, the line-of-sight communication links may cause strong interference among UAVs. Towards this end, we propose a novel multi-agent deep reinforcement learning based algorithm, named as multi-agent QMIX (MAQMIX) to: 1) design proper UAVs’ trajectories to serve the moving GUs while maintaining the network connection; 2) allocate frequency resource properly among UAVs to alleviate the impact of interference; and 3) choose a proper next hop UAV for each data packet to reduce the transmission time and probability of network congestion. The proposed MAQMIX has two novel training mechanisms, i.e., intra-UAV and inter-UAV training mechanisms, which can tackle the large action space issue and coordinate the training among UAVs in the multi-hop UAV relay network. Simulation results demonstrate that the MAQMIX outperforms baseline schemes in terms of the network congestion avoidance, throughput, and transmission time. [ABSTRACT FROM AUTHOR]

Many applications operating in the Internet of Things (IoT) require timely and fair data collection from devices. This has motivated research into a new metric called Age of Information (AoI). This paper contributes to this effort by proposing to minimize the maximum average AoI (min-max AoI) in a multi-hop IoT network comprising of solar-powered Power Beacons (PBs). It outlines a Mixed Integer Linear Program (MILP) that jointly optimizes: (i) the beamforming vector used by PBs to charge devices, and (ii) routing, which determines how samples from devices are forwarded to a sink node, and (iii) the sampling time of sources. It also presents two protocols: Centralized Linear Relaxation (CLR) and Distributed Path Selection (DPS), respectively. CLR is run by the sink to determine the transmit power of PBs and the path of each source using two Linear Programs (LPs). On the other hand, DPS is a distributed approach whereby PBs and sources make their own decisions using local information. Our simulation results show that min-max AoI increases with the number of sources, but reduces with increasing number of PBs. The number of paths available to a source, the number of frames, and solar panel size have limited impact on performance. The min-max AoI of CLR and DPS is $1.60\times $ and $1.95\times $ higher than that of MILP. [ABSTRACT FROM AUTHOR]

Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption. [ABSTRACT FROM AUTHOR]

Until now, multi-hop device-to-device (MD2D) routing in mobile wireless networks has been designed to operate over a single-protocol routing framework. Consequently, to the best of our knowledge, no framework has been developed to enable the dynamic deployment and switching of multiple MD2D routing protocols under one framework. This paper proposes a multi-protocol framework to introduce the idea of clustering a cell and deploying different MD2D routing protocols for each cluster based on the cluster requirements. To this end, four clusters are developed with varying network conditions (i.e., node density, mobility rate, and the number of flows). Then, the performance of our two previously designed multi-hop routing protocols, namely hybrid SDN architecture for wireless distributed networks (HSAW) and source-based virtual ad hoc routing protocol (VARP-S), are investigated in each cluster in terms of energy consumption, end-to-end (E2E) delay, packet loss, and cellular-band overhead. Based on the achieved simulation results, a multiple-criteria decision-making (MCDM) approach based on the analytic hierarchy process (AHP) is developed to choose the most suitable protocol for each cluster to provide the best performance. The simulation results indicate that our proposed multi-protocol framework provides better performance compared to traditional single-protocol architectures. [ABSTRACT FROM AUTHOR]

Autonomous Vehicles (AVs) rely on a set of radar sensors operated on frequency modulated waveforms. Due to the large bandwidth requirement of frequency modulated radars, only a limited number of proximate vehicles can be allowed for a concurrent transmission within the available spectrum. However, with the explosive growth of AVs, the available spectrum may soon reach its capacity. As a results, the coexistence of multiple AVs working on same resource, may lead to the problem of Radar-to-Radar (R2R) interference, also known as radar blindness. In this paper, we propose the notion of coded waveforms to minimize the R2R interference among the vehicles operating on the same resource. Specifically, the spread spectrum codes have been used as another degree of freedom (i.e., along with time-frequency resources) to spread the inter-vehicular radar interference over the wider spectrum, which enable to orthogonalize more number of AVs over the available range of spectrum. In addition, we have formulated a Spread Spectrum-based Radar Transmission Scheme (SS-RTS), and described the transmission and reception through SS-RTS. Also, the SS-RTS has been compared with the existing Graph-based Resource Allocation (GRA) scheme. Further, simulation results verified that SS-RTS significantly reduces the inter-vehicular R2R interference and outperforms GRA in terms of blind probability. [ABSTRACT FROM AUTHOR]

In this paper, we study diffusive multi-hop mobile molecular communication (MMC) with drift in one-dimensional channel by adopting amplify-and-forward (AF) relay strategy. Multiple and single molecules type are used in each hop to transmit information, respectively. Under these two cases, the mathematical expressions of average bit error probability (BEP) of this system based on AF scheme are derived. We implement joint optimization problem whose objective is to minimize the average BEP with $(Q + 2)$ optimization variables including $(Q + 1)$ -hop distance ratios and decision threshold. ${Q}$ is the number of relay nodes. Furthermore, considering that more optimization variables result in higher computation complexity, we use efficient algorithm which is adaptive genetic algorithm (AGA) to solve the optimization problems to search the location of each relay node and the decision threshold at destination node simultaneously. Finally, the numerical results reveal that AGA has a faster convergence speed and it is more efficient with fewer iterations compared with Bisection algorithm. The performances of average BEP with optimal distance ratio of each hop and decision threshold are evaluated. These results can be used to design multi-hop MMC system with optimal optimization variables and lower average BEP. [ABSTRACT FROM AUTHOR]

Dual-function radar-communication (DFRC) based on frequency hopping (FH) MIMO radar (FH-MIMO DFRC) achieves symbol rate much higher than radar pulse repetition frequency. Such DFRC, however, is prone to eavesdropping due to the spatially uniform illumination of an FH-MIMO radar. In this paper, we reveal the potential of using permutations of hopping frequencies to achieve secure and high-speed FH-MIMO DFRC. Specifically, we identify the angle-dependent issue in detecting permutations and develop an element-wise phase compensation (EPC) to solve the issue for a legitimate user (Bob). EPC makes the demodulation at an eavesdropper (Eve) conditioned on knowing the angle-of-departure (AoD) of Bob. We also propose the random sign reversal (RSR) technique which randomly selects several antennas over hops and reverses their signs. Owing to EPC, there is a sign rule available for Bob. We employ the rule and develop a low-complexity algorithm for Bob to remove RSR. We further prove that, given the same signal-to-noise ratio, RSR plus EPC make the demodulation performance of Eve inferior to that of Bob in most angular regions. Confirmed by simulation, our design achieves substantially high physical layer security for FH-MIMO DFRC, improves demodulation performance compared with existing designs, and reduces mutual interference among radar targets. [ABSTRACT FROM AUTHOR]

Multipath propagation, frequency selective fading, low-propagation velocity, and narrow bandwidth are all characteristics of underwater acoustic channels. Doppler shifts and diffusions can occur as a result of the low transmission speed of an acoustic signal, which can be caused by the movement of ocean currents or the transceiver. Furthermore, frequency selective fading and excessive noise interference can disrupt underwater acoustic communication on a continual basis. Because of its high anti-interference ability and high confidentiality, spread spectrum technology is commonly adopted in underwater acoustic communications. Although the direct sequence spread spectrum method has a low data rate, it is advantageous in a multipath propagation channel environment or an environment with a low signal-to-noise ratio (SNR). This advantage is suitable for long-distance transmission or LPD (Low Probability of Detection) communication, and the direct sequence spread spectrum method is applied. In this paper, we propose a highly reliable M-ary cyclic spread spectrum technique by superimposing the M-ary spread spectrum, an extension of the direct sequence spread spectrum technique, and cyclic shift keying. Furthermore, by estimating the Doppler frequency using M-ary spread spectrum codes and performing synchronization correction of the ensuing symbol based on the estimation results, higher performance can be attained. Simulations and experiments showed that the M-ary cyclic spread spectrum method can reduce Doppler estimation and synchronization error accumulation while maintaining a high data rate. Furthermore, the MCSS method had a lower bit error rate than the standard spread spectrum method. [ABSTRACT FROM AUTHOR]

The performance of distributed computing is restricted by the slowest worker nodes, known as stragglers, in the system. Coded computation has emerged as an efficient technique to mitigate the straggler effects in distributed computing. Most existing works only considered the computation straggler for single-hop networks. However, in multi-hop networks, the straggler effects will occur not only on worker nodes but also on relay nodes. In this paper, we consider a heterogeneous multi-hop network. The nodes in the network are heterogeneous, i.e., their computation capacities and transmission capacities are different. We propose a hierarchical coding scheme for such a network. Firstly, we reorganize it into a hierarchical network containing multiple layers. Each layer in the network consists of several groups. Then, a new hierarchical coding scheme is proposed, where coding is applied to each group to mitigate the stragglers. By taking both the computation time and transmission time into consideration, the overall task completion time is derived. To improve the performance of the network, heterogeneous hierarchical coded computation (HHCC) algorithm is proposed to provide an asymptotically optimal task allocation strategy. Compared with existing uniform uncoded, load balanced uncoded, and heterogeneous coded matrix multiplication schemes, HHCC has significant improvement. [ABSTRACT FROM AUTHOR]

Communication limitation at the edge is widely recognized as a major bottleneck for federated learning (FL). Multi-hop wireless networking provides a cost-effective solution to enhance service coverage and spectrum efficiency at the edge, which could facilitate large-scale and efficient machine learning (ML) model aggregation. However, FL over multi-hop wireless networks has rarely been investigated. In this paper, we optimize FL over wireless mesh networks by taking into account the heterogeneity in communication and computing resources at mesh routers and clients. We present a framework that each intermediate router performs in-network model aggregation before sending the data to the next hop, so as to reduce the outgoing data traffic and hence aggregate more models under limited communication resources. To accelerate model training, we formulate our optimization problem by jointly considering model aggregation, routing, and spectrum allocation. Although the problem is a non-convex mixed-integer nonlinear programming, we transform it into a mixed-integer linear programming (MILP), and develop a coarse-grained fixing procedure to solve it efficiently. Simulation results demonstrate the effectiveness of the solution approach, and the superiority of the in-network aggregation scheme over the counterpart without in-network aggregation. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) content sharing holds great promise to alleviate the growing strain on cellular networks, as it offloads popular content data onto direct peer-to-peer links. However, it is still unexplored how content sharing could benefit from utilizing multihop rather than the conventional single-hop D2D communications. As a step towards this end, this paper proposes a game theoretic approach to enable D2D content sharing with multihop communication capabilities. Given a subset of participants, a Nash bargaining game is modeled to provide the routing and pricing graphs, where a novel incentive mechanism is adopted to stimulate cooperation. By iteratively evaluating the solution of the Nash bargaining subgame, participants that include content sources and transmission relays are determined, which ensures that all participants make contributions to the content sharing process. An additional procedure termed pricing plan is introduced to make sure that the final pricing graph is practical and feasible in terms of D2D communication. Experimental results are presented to demonstrate that the proposed game theoretic approach could not only jointly deal with the participants selection, routing, and pricing problems in multihop D2D content sharing, but also effectively restrict utilities and transmission resources to only contributive participants. [ABSTRACT FROM AUTHOR]

Space-air-ground integrated network (SAGIN), as an integration of interconnected space, air, and ground network segments, is expected to see prevalent usage as part of intelligent transportation systems (ITS), providing an enhanced service provision in terms of coverage, flexibility and reliability. However, restricted by the limited and unbalanced network resources, the efficiency and security of the underlying connectivities of SAGIN are of utmost concern for ITS applications. In this paper, a weighted fractional Fourier transform (WFRFT) based parallel complex spreading (PCS) approach is proposed to improve the communication efficiency and security of SAGIN at the physical (PHY-) layer. The concept of WFRFT along with the direct sequence spread spectrum technology establish the security kernel of the proposed scheme. The practicability of the complex-valued WFRFT-spreading architecture is verified by studying the correlation properties of the WFRFT-spreading signals. Taking advantages of the signal uniqueness of WFRFT, the proposed scheme is capable of providing more flexibility in signal characteristic control. Moreover, the complex-valued WFRFT-spreading processing makes the proposed scheme inherently robust against the large Doppler shift distortions in SAGIN. Simulation results demonstrate the superiority of the proposed WFRFT-PCS scheme in terms of communication efficiency and PHY-layer security. Finally, as a proof of concept, an all-digital FPGA prototype system is designed to show the practicability and the performance enhancement of the proposed scheme. [ABSTRACT FROM AUTHOR]

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In this paper, a cooperative protocol is investigated for a multi-hop network consisting of relays with buffers of finite size, which may operate in different communication modes. The protocol is based on the myopic decode-and-forward strategy, where each node of the network cooperates with a limited number of neighboring nodes for the transmission of the signals. Each relay stores in its buffer the messages that were successfully decoded, in order to forward them through the appropriate channel links, based on its supported communication modes. A complete theoretical framework is investigated that models the evolution of the buffers and the transitions at the operations of each relay as a state Markov chain (MC). We analyze the performance of the proposed protocol in terms of outage probability and derive an expression for the achieved diversity-multiplexing tradeoff, by using the state transition matrix and the related steady state of the MC. Our results show that the proposed protocol outperforms the conventional multi-hop relaying scheme and the system’s outage probability as well as the achieved diversity order depend on the degree of cooperation among neighboring nodes and the communication model that is considered for every relay of the network. [ABSTRACT FROM AUTHOR]

In frequency hopping (FH) communication systems, frequency hopping sequences (FHSs) are crucial in determining the system’s anti-jamming performance. If FHSs can ensure a wide-gap between two adjacent frequency points to avoid the frequency points with high interference probability, it will significantly improve the FH communication system’s anti-interference ability. Moreover, if each frequency point appears at the same number of times in a sequence period, the system’s anti-electromagnetic interference will be enhanced. Therefore, it is desirable to employ FHSs with low Hamming autocorrelation, wide frequency-hopping gap, and good uniformity in practical applications. However, to the best of our knowledge, no such infinite classes of FHSs have been reported in the literature to date. This paper aims to present two constructions of uniform wide-gap frequency-hopping sequences (WGFHSs) by concatenating two or three adequately designed sequences. For the first time, we obtain two infinite classes of WGFHSs, which are optimal with respect to the well-known Lempel-Greenberger bound. [ABSTRACT FROM AUTHOR]

While multi-hop multi-frequency mesh has been extensively studied in the past decades, only several deployable and relatively bulky systems have been developed to support small numbers of hops under stationary settings. This paper presents a new Software-Defined Networking (SDN)-based design of multi-hop multi-frequency mesh. A new lightweight hardware platform is developed to support adaptive routing and frequency selection, by modifying and integrating commercial-off-the-shelf WiFi modules. We also extend the celebrated Dijkstra's algorithm in support of the new multi-hop multi-frequency platform, where non-overlapping frequency bands are selected together with the routing paths by maintaining $N^2$ Dijkstra processes for $N$ frequency bands. These processes interact to recursively select the optimal upstream node and frequency for each downstream frequency of a node. Mininet-WiFi is used to evaluate the routing of the new system under dense network settings. The results indicate that our system improves the end-to-end throughput by taking background WiFi traffic into account and adaptively selecting the routes and frequencies, as compared to the shortest-path-based routing strategy. [ABSTRACT FROM AUTHOR]

In maritime wireless communications, unmanned surface vehicles (USVs) can improve coverage and transmission performance due to their agile maneuverability and flexible deployment. This paper considers a USV-enabled maritime wireless network, where a USV is employed to assist the communication between the terrestrial base station and ships. Considering the maritime environment characteristics and earth curvature, we establish the systematic USV kinetics and information transmission models. To guarantee fairness, we aim to maximize the minimum expected throughput overall ships by jointly optimizing the trajectory and communication resource allocation, subject to the constraints of the USV kinetics, safe sailing, breakpoint distances, line-of-sight links, resource allocation, and information-causality. Due to the complexity of the maritime two-ray signal propagation model, we propose a channel approximation method to find an upper bound of the throughput for the original problem. By the problem decomposition, two sub-problems are derived and solved iteratively using successive convex approximation and interior-point methods. Simulation results confirm the effectiveness of the proposed method and show that USV can significantly improve transmission performance in maritime wireless networks. [ABSTRACT FROM AUTHOR]

Operating beyond-5G networks at the millimeter wave (mmWave) band imposes technological challenges while offering great opportunities. The nature of millimeter waves renders the communication quality susceptible due to blockage caused by obstacles. Hence, multi-hop relaying is likely to play a significant role in improving the performance of mmWave networks. In this paper, we investigate the performance of two appropriate routing techniques for mmWave networks, namely minimum hop count (MHC) and nearest LoS relay to the destination with MHC (NLR-MHC). Analytical models are provided to evaluate the performance of the two routing techniques using tools from stochastic geometry. We model the distribution of hop count using phase-type distribution, and then we use this distribution to derive analytical results for the coverage probability and spectral efficiency. Results reveal the significant impact of densities of relays and blockages on the performance of the aforementioned routing techniques in-terms of spectral efficiency, connectivity probability, and average hop count. It is also demonstrated that NLR-MHC achieves a superior coverage probability and spectral efficiency compared to MHC. However, MHC provides better performance in-terms of connectivity probability and average hop count. [ABSTRACT FROM AUTHOR]

We consider a single-unicast networking scenario where a sender periodically sends a batch of data to a receiver over a multi-hop network, possibly using multiple paths. We study problems of minimizing peak/average Age-of-Information (AoI) subject to throughput requirements based on a stylized deterministic model in this scenario. The consideration of batch generation and multi-path communication differentiates our AoI study from existing ones. We first show that our AoI minimization problems are NP-hard, but only in the weak sense, as we develop an optimal algorithm with a pseudo-polynomial time complexity. We then prove that minimizing AoI and minimizing maximum delay are “roughly” equivalent, in the sense that any optimal solution of the latter is an approximate solution of the former with bounded optimality loss. We leverage this understanding to design a general approximation framework for our problems. It can build upon any $\alpha $ -approximation algorithm of the maximum delay minimization problem to construct an $(\alpha +\mathsf {c})$ -approximate solution for minimizing AoI. Here $\mathsf {c}$ is a constant depending on the throughput requirements. Furthermore, we show that our results can be extended to the multiple-unicast setting. Simulations over various network topologies validate the effectiveness of our approach. Our results make a major advance to optimizing AoI in multi-path communication, and hence can be of broad interest to the networking research community. [ABSTRACT FROM AUTHOR]

Spread spectrum technology has been widely employed for positioning and communicating with autonomous underwater vehicles (AUVs), but conventional spread spectrum sequences lack confidentiality and reliability in UWA channel. Considering the limitations of conventional sequences and the characteristics of underwater acoustic (UWA) channel, a composite chaotic orthogonal sequence (CCOS) based on the UWA channel is proposed. The confidentiality of the CCOS is superior to that of the m‐sequence, while the autocorrelation performance of the CCOS is superior to that of the orthogonal sequence. Moreover, the CCOS can compensate for the imbalance of logistic chaotic sequence when assigned certain initial values. Acquisition is a crucial component of accessing the spread spectrum signal; therefore, the acquisition performance indicates the applicability of the CCOS. The source–target model is established to simulate communication with an underwater moving target. To simulate the acquisition process, a parallel algorithm based on fast Fourier transform is adopted, and the entire simulation process is completed based on the BELLHOP ray acoustic model. Through data processing, the Doppler shift error is less than half of the frequency‐search element. Furthermore, the acquisition probabilities of the CCOS with different numbers of bits are over 90%, which demonstrates the reliability of the CCOS. [ABSTRACT FROM AUTHOR]

Satellite high-mobility communications can provide global communication services for mobile terminals, which plays a vital role in today's world of wireless communications. Different from traditional terrestrial-satellite communications, high-mobility terminals impose more challenges on the direct sequence spread spectrum (DSSS) signal acquisition in satellite communications. On the one hand, the spread spectrum sequence used in satellite communication systems is relatively long, which inevitably increases the computational complexity. On the other hand, high Doppler frequency offsets and time-varying Doppler rates caused by high-mobility terminals make satellite DSSS signal acquisition become the bottleneck. To solve such a problem in high-mobility satellite communications, we propose a new acquisition algorithm based on the new factor graph where time-varying Doppler rate is modeled by the random walk model, named the turbo iterative acquisition algorithm. It consists of the constraint-detection loop and the Doppler-estimation loop. By means of soft messages passed between these loops, the negative influence of time-varying Doppler frequency offsets can be eliminated effectively. Simulation results show that, compared with traditional algorithms, the proposed algorithm improves acquisition performance more than 1.3 dB with low computational complexity, which demonstrates the superiority of the proposed algorithm in terms of acquisition performance and complexity. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a multilevel cyclic shift index modulation aided differential chaotic shift keying (MCSI‐DCSK) system to improve data rate and energy efficiency. In the MCSI‐DCSK system, the bit stream is divided into blocks with N(M+1) bits which are further divided into N groups equally. In each group, the first M bits are mapped into an index of cyclic shift in the chaotic reference sequence, while the last bit is used to modulate the shifted chaotic reference sequence. Finally, the all modulated shifted chaotic reference sequences are superimposed to form the information‐bearing signal. So the proposed system improves the data rate. The analytical bit‐error‐rate (BER) expressions of the MCSI‐DCSK system are derived over additive white Gaussian noise and multipath Rayleigh fading channels and validated via simulations. In addition, the BER performance of the proposed system is compared with other non‐coherent, chaotic communication systems. Simulation results indicate that the MCSI‐DCSK system has better performance in data rate and BER.

Digital chaotic sequence spread spectrum (CSSS) communication systems provide a number of advantages for secure communications due to the apparent bandlimited Gaussian noise-like signal characteristics and the non-repeating nature of the underlying chipping sequence. The Rayleigh magnitude distribution of the signal represents a challenge, however, for transmission through linear high-power amplifiers (HPA), both due to the high peak-to-average power ratio (PAPR) and the impacts of selective signal compression on the tails of the time-domain Gaussian signals, which becomes observable by cyclostationary low probability of detection (LPD) metrics. This paper first provides an analysis of HPA compression effects on a single-carrier CSSS signal to understand the HPA-induced artifacts when pushed into compression. This work also defines and evaluates time-domain pre-distortion techniques for memoryless HPAs, validating those formulations through Matlab simulations and live measurements of predistorted CSSS signals transmitted through physical HPAs. Unlike computationally expensive statistical models used to predistort multi-carrier waveforms, this technique is shown to be a computationally efficient method to minimize the increased likelihood of adversarial detection of single-carrier waveforms. The proposed pre-distortion techniques are measured as achieving an average of 3.35-dB in improvements for linear operating range, enabling transmission of CSSS waveforms at an HPA backoff of 4.80-dB without adversely affecting kurtosis-based signal detectability.

This paper proposes and analyzes a modification to the standard matched filtering operation utilized in filter-bank multicarrier spread spectrum (FB-MC-SS) communications. This modification suppresses the impact of partial-band interferers without a priori knowledge of their location within the band of transmission and/or their power characteristics. A performance analysis of the proposed matched filter, which indicates its usefulness in environments where interference is likely to be experienced, is presented. It is shown that whereas the standard matched filter proves to be ineffective for packet detection and timing acquisition in such harsh environments, the modified matched filter successfully removes the harmful effects of interferers. This is found to be a unique feature of FB-MC-SS which is non-existent in other alternative spread spectrum methods.

The transmission of huge amounts of data generated from various sensors is the basis and prerequisite for the analysis and prediction of the marine ecosystem. The special geographical conditions of the ocean determine that its data transmission is different from the common terrestrial data transmission. In this study, a marine environmental monitoring network architecture is proposed to collect environmental data from marine ecosystems using a heterogeneous network constructed by a multi-hop network and a satellite network. Considering the characteristics of satellite networks, such as high bandwidth delay product (BDP), long latency and high bit error rate, this work proposes a transmission scheme that improves the transmission performance of Transmission Control Protocol/Internet Protocol (TCP/IP)-based Internet networks over satellite networks. The improved scheme increases the monitoring data transmission rate, distinguishes between random data loss and congested data loss, rationalizes the threshold in fast recovery, and improves the overall transmission performance of the marine environmental monitoring network. The experimental results show that the proposed scheme can greatly improve the transmission performance of the monitoring network compared with traditional transmission protocols. The network model proposed in this study makes full use of current advanced network technologies, including multi-hop networks, wireless sensor networks, and satellite networks to expand the monitoring area at sea. This study provides a useful reference for the network model and data transmission for ocean monitoring. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a promising 6G technology that can improve wireless communication capacity in a cost-effective and energy-efficient manner, by adjusting a large number of passive reflectors to appropriately change the signal propagation. In this study, we identified the achievable rate region of a two-hop interference channel with distributed multiple IRS relays. To do so, we formulated a non-convex problem that characterizes the rate-profile, and found its solution using successive convex approximation (SCA). We then proposed an alternating direction method of multipliers (ADMM) and alternating optimization (AO) based distributed and low-complex IRS control that maximizes the achievable sum-rate, and proved its convergence and optimality. We then compared the proposed IRS control with semi-definite relaxation (SDR)-, random phase-, deep reinforcement learning (DRL)- based IRS controls, and optimal amplify-and-forward (AF)-, interference neutralization (IN)-, and decode-and-forward (DF) based relaying schemes. We demonstrated that the proposed control with multiple IRS elements outperforms the benchmark controls in terms of the achievable rate region, achievable sum-rate, and energy efficiency under same power budget. We also confirmed that the discrete phase approximation of the proposed control provides near-optimal performance with fewer bits, and the proposed control is robust under imperfect CSI condition. The proposed controls can be efficiently applied to large-scale multi-pair multihop device-to-device and machine-type device communications in the interference-limited or low-powered dense networks of 5G and 6G environments. [ABSTRACT FROM AUTHOR]

We consider the problem of private polynomial computation (PPC) from a distributed storage system (DSS). In such setting a user wishes to compute a multivariate polynomial of degree at most $g$ over $f$ variables (or messages) stored in $n$ noncolluding coded databases, i.e., databases storing data encoded with an $[n,k]$ linear storage code, while revealing no information about the desired polynomial evaluation to the databases. For a DSS setup where data is stored using linear storage codes, we derive an outer bound on the PPC rate, which is defined as the ratio of the (minimum) desired amount of information and the total amount of downloaded information, and construct two novel PPC schemes. In the first scheme, we consider Reed-Solomon coded databases with Lagrange encoding, which leverages ideas from recently proposed star-product private information retrieval and Lagrange coded computation. The second scheme considers the special case of coded databases with systematic Lagrange encoding. Both schemes yield improved rates, while asymptotically, as $f\rightarrow \infty $ , the systematic scheme gives a significantly better computation retrieval rate compared to all known schemes up to some storage code rate that depends on the maximum degree of the candidate polynomials. [ABSTRACT FROM AUTHOR]

We study a heterogeneous wireless sensor network (WSN) where $N$ heterogeneous access points (APs) gather data from densely deployed sensors and transmit their sensed information to $M$ heterogeneous fusion centers (FCs) via multi-hop wireless communication. The heterogeneous optimal deployment of APs and FCs is modeled as an optimization problem with total wireless communication power consumption of the network as its objective function. We consider both static WSNs, where APs and FCs retain their deployed position, and mobile WSNs where APs and FCs can move from their initial deployment to their optimal locations. Based on the derived necessary conditions for the optimal deployment in static WSNs, we propose an iterative algorithm to deploy APs and FCs. In addition, we study the necessary conditions of the optimal movement-efficient deployment in mobile WSNs with constrained movement energy and present iterative algorithms to find such deployments, accordingly. Simulation results show that our proposed deployment algorithms outperform the existing methods in the literature, and achieve a lower total wireless communication power in both static and mobile WSNs. [ABSTRACT FROM AUTHOR]

Aligned-Images Sum-set Inequalities are used in this work to study the Generalized Degrees of Freedom (GDoF) of the symmetric layered multi-hop interference channel under the robust assumption that the channel state information at the transmitters (CSIT) is limited to finite precision. First, the sum-GDoF value is characterized for the $2\times 2\times 2$ setting that is comprised of 2 sources, 2 relays, and 2 destinations. It is shown that the sum-GDoF does not improve even if perfect CSIT is allowed in the first hop, as long as the CSIT in the second hop is limited to finite precision. The sum GDoF characterization is then generalized to the $2\times 2\times \cdots \times 2$ setting that is comprised of $L$ hops. Remarkably, for large $L$ , the sum-GDoF value approaches that of the one-hop broadcast channel that is obtained by full cooperation among the two transmitters of the last hop, with finite precision CSIT. Previous studies of multi-hop interference networks either identified sophisticated GDoF optimal schemes under perfect CSIT, such as aligned interference neutralization and network diagonalization, that are powerful in theory but too fragile to be practical, or studied robust achievable schemes like classical amplify/decode/compress-and-forward without claims of information-theoretic optimality. In contrast, under finite precision CSIT, we show that the benefits of fragile schemes are lost, while a combination of classical random coding schemes that are simpler and much more robust, namely a rate-splitting between decode-and-forward and amplify-and-forward, is shown to be GDoF optimal. As such, this work represents another step towards bridging the gap between theory (optimality) and practice (robustness) with the aid of Aligned-Images Sum-set Inequalities. [ABSTRACT FROM AUTHOR]

This work investigates multi-hop serial relaying half-duplex (HD) networks comprising one source, one destination and $K$ decode-and-forward (DF) relays. Buffer-aided (BA) relays are considered where finite size buffers are added to relays. For this setup, we propose a novel BA relaying strategy that selects the node that must transmit over one epoch in a block fading environment. Selecting a node depends on the buffer state information of all relays and on the availability of the hops. Moreover, the proposed relaying scheme is controlled by an adjustable parameter that allows the system to achieve multiple levels of tradeoff between the average packet delay (APD) and the outage probability (OP). A Markov chain model is adopted to evaluate the system’s performance and simple closed-form expressions were derived for the APD and OP based on an asymptotic analysis. The performance analysis proves the ability of the suggested relaying scheme to achieve significant OP and APD gains with small buffer sizes. Two variants of the proposed relaying scheme are particularly appealing. The APD-prioritizing variant achieves the smallest APD of $2K$ without improving the diversity order. The second OP-prioritizing variant reaches the full diversity order of $K+1$ while increasing the asymptotic APD to $K(K+3)$. [ABSTRACT FROM AUTHOR]

The relay is harvesting energy for data transmission and eavesdropping attacks will occur. Considering carried energy and security of relay, this letter studies relay selection in energy harvesting multi-hop D2D networks with an eavesdropper. To improve the secure connectivity performance of the relay, the higher bound of source-to-destination secrecy connectivity probability (SCP) is derived. Then, we derive the factor directly related to the largest SCP. Then, a relay selection algorithm is proposed to find a higher security connectivity relay path. Our theoretical derivation and the proposed algorithm are verified by Monte Carlo simulation results. The simulation results show that the proposed algorithm exhibit significantly higher SCP than the direct transmission method and conventional relay selection algorithms. [ABSTRACT FROM AUTHOR]

In this article, recursive filtering is investigated for time-varying discrete sequential systems (DSSs) under weighted try-once-discard (WTOD) protocols, which are employed to govern the access authorization of a shared network in order to remit the communication burden. A transmission model, dependent on a Bernoulli distributed white sequence, is developed to describe the phenomenon of deception attacks. In light of the adopted protocol and the attack model, a recursive algorithm with the form of Riccati-like difference equations is developed to optimize the filtering performance in the mean square sense. Furthermore, by resorting to the mathematical induction, the convergence of the proposed recursive algorithm is discussed profoundly. Finally, a simulation example is presented to verify the availability of the designed recursive filter. [ABSTRACT FROM AUTHOR]