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Horizontal antenna sectorization has been used within all generations of cellular radio networks to improve both the coverage and capacity of such networks. This paper evaluates the potential coverage and capacity gains of sectorization through extensive simulation and real-world trials of deployments of higher order horizontal sectorization (three, six, nine, 12, and 15 sectors) when applied to a Third-Generation (3G) Evolved High-Speed Packet Access (\mbox3\mboxG/\mboxHSPA+) network. Simulation results are presented for idealized homogeneous networks based upon a standardized 3G Partnership Project HSPA/Long-Term Evolution (LTE) network model to find the theoretical downlink capacity gains and the optimum horizontal antenna beamwidth to maximize capacity without significantly reducing coverage and other cellular-network key performance indicators (KPIs). Further simulations have also been performed to assess the potential gain seen within Telefonica UK's central London \mbox3\mboxG/\mboxHSPA+ network, and these results have also been verified using live network field results from the deployment of six-sector sites into Telefonica UK's network. Finally, trial results from the deployment of what is believed to be the industry's first 15-sector 3G site are presented, showing further gains are possible well beyond the six sectors per site. [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]

The end-to-end throughput of multi-hop communication in wireless ad hoc networks is affected by the conflict between forwarding nodes. It has been shown that sending more packets than maximum achievable end-to-end throughput not only fails to increase throughput but also decreases throughput owing to high contention and collision. Accordingly, it is of crucial importance for a source node to know the maximum end-to-end throughput. The end-to-end throughput depends on multiple factors, such as physical layer limitations, medium access control (MAC) protocol properties, routing policy, and nodes’ distribution. There have been many studies on analytical modeling of end-to-end throughput but none of them has taken routing policy and nodes’ distribution as well as MAC layer altogether into account. In this paper, the end-to-end throughput with perfect MAC layer is obtained based on routing policy and nodes’ distribution in 1-D and 2-D networks. Then, imperfections of IEEE 802.11 protocol are added to the model to obtain precise value. An exhaustive simulation is also made to validate the proposed models using ns-2 simulator. Results show that if the distribution to the next hop for a particular routing policy is known, our methodology can obtain the maximum end-to-end throughput precisely. [ABSTRACT FROM AUTHOR]

We present a distributed stable protocol for local broadcast in multi-hop wireless networks, where packets are injected to the nodes continuously, and each node needs to quickly disseminate the injected packets to all its neighbors within a given communication range $R$. We investigate the maximum packet injection rate and the minimum packet latency that can be achieved in a stable protocol. This paper assumes the signal-to-interference-plus-noise-ratio (SINR) interference model, which reflects more accurately the physical characteristics of the wireless interference, such as fading and signal accumulation, than conventional local interference models, e.g., graph-based models. More specifically, we present a stable protocol that can handle both stochastic and adversarial injection patterns. The protocol is asymptotically optimal in terms of both injection rate and packet latency. To the best of our knowledge, this paper is the first one studying the properties of stable protocols for the basic primitive of local broadcast in a multi-hop setting under SINR. Our proposed protocol utilizes a static local broadcast algorithm as a subroutine. This static algorithm is of independent interest, and it closes the $O(\log n)$ gap between the upper and lower bounds for static local broadcast. Simulation results indicate that our proposed algorithms can perform well in realistic environments. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to assess the performance in terms of end-to-end throughput of an ad hoc multi-hop wireless network, where each link is affected by interference coming from other multi-hop paths nearby. The approach captures the mutual impact of each path on all others. It can be applied to both, contention-based and scheduled, medium access control (MAC) protocols. Sources have data to send to destination nodes through $n$ relays. Nodes are assumed to be uniformly and randomly distributed in the 2-D infinite plane. The model shows the impact on the end-to-end throughput of $n$ ; it also captures the influence of node density, traffic generated, number of retransmissions, and other MAC parameters. Finally, the model provides the throughput-delay tradeoff. Unlike most previous approaches, the mathematical tool proposed appears to be scalable, allowing easy extension to any number of hops. Comparison with simulation results is provided to prove that the impact of the approximations introduced in the analysis is almost negligible. [ABSTRACT FROM PUBLISHER]

There have been some rapid advances on the design of full duplex (FD) transceivers in recent years. Although the benefits of FD have been studied for single-hop wireless communications, its potential on throughput performance in a multi-hop wireless network remains unclear. As for multi-hop networks, a fundamental problem is to compute the achievable end-to-end throughput for one or multiple communication sessions. The goal of this paper is to offer some fundamental understanding on end-to-end throughput performance limits of FD in a multi-hop wireless network. We show that through a rigorous mathematical formulation, we can cast the multi-hop throughput performance problem into a formal optimization problem. Through numerical results, we show that in many cases, the end-to-end session throughput in a FD network can exceed $2 \times$ of that in a half duplex (HD) network. Our finding can be explained by the much larger design space for scheduling that is offered by removing HD constraints in throughput maximization problem. The results in this paper offer some new understandings on the potential benefits of FD for end-to-end session throughput in a multi-hop wireless network. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the age minimization problem for a two-hop relay system, under a resource constraint on the average number of forwarding operations at the relay. We first design an optimal policy by modelling the considered scheduling problem as a constrained Markov decision process (CMDP) problem. Based on the observed multi-threshold structure of the optimal policy, we then devise a low-complexity double threshold relaying (DTR) policy with only two thresholds, one for relay’s AoI and the other one for the age gain between destination and relay. We derive approximate closed-form expressions of the average AoI at the destination, and the average number of forwarding operations at the relay for the DTR policy, by modelling the tangled evolution of age at relay and destination as a Markov chain (MC). Numerical results validate all the theoretical analysis, and show that the low-complexity DTR policy can achieve near optimal performance compared with the optimal CMDP-based policy. Moreover, the relay should always consider the threshold for its local age to maintain a low age at the destination. When the resource constraint is relatively tight, it further needs to consider the threshold on the age gain to ensure that only those packets that can decrease destination’s age dramatically will be forwarded. [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]

Recently, multiple concurrent transmission techniques have been proposed for smartly exploiting interference to improve network throughput. This paper considers zero-forcing (ZF) precoding that allows two interfering links to concurrently transmit under certain situations. This paper focuses on identifying appropriate schedule schemes that efficiently utilize the ZF precoding opportunities to improve network throughput. With this motivation, we define novel link models to formulate our concerned problem. We also develop a distributed scheduling algorithm by using belief propagation. Finally, we conduct extensive simulation experiments to evaluate the efficiency of ZF in improving network throughput in multihop wireless networks. Our simulations confirm that intelligently utilizing ZF in multihop networks is very effective in improving throughput. [ABSTRACT FROM PUBLISHER]

Millimeter Wave (mmWave) communications are evolving as a potential and promising technology to address the ever increasing mobile data rate requirements. This paper addresses fair scheduling in directional antenna based mmWave wireless personal and local area networks with non-uniform traffic demand. Due to their small wavelength, mmWave signals are susceptible to blockage. The proposed fair schedulers handle the link blockage problem through relaying, and are capable of providing end-to-end fair bandwidth allocation to relay flows. To achieve differentiated and fair service allocation to various regions of the network while using only limited flow related information, a service tag based scheduler is proposed in this paper. Then, the performance bounds on the minimum throughput and unfairness of this scheduler are obtained. To approximate the performance of the service tag based scheduler while minimizing the control overhead, a heuristic fair scheduler is also proposed. Results from extensive simulations conducted in a mmWave WPAN deployed to support high data rate applications show the performance advantages of the proposed schedulers, compared to existing fair schedulers, in terms of throughput and fairness. [ABSTRACT FROM AUTHOR]

Wireless radio frequency energy harvesting has been adopted in wireless networks as a method to supply energy to wireless nodes. In this paper, we analyze a wireless energy harvesting network based on a Boolean-Poisson model. This model assumes that energy sources are distributed according to a Poisson point process and have disc-shaped coverage regions with random radii. We introduce a distribution for the coverage radii, which takes aggregated harvested power into account. The union of the coverage regions of the energy sources forms the energy harvesting zone. We derive the transmission success probability of single-hop networks characterized by the probability that two sensor nodes are located in the energy harvesting zone. Then, we analyze the performance of multi-hop networks in the cases, where the locations of the sensor nodes are either fixed or randomly distributed. Moreover, we consider a star-shaped topology, which reflects the scenario wherein some sensor nodes simultaneously transmit data to a data collector. In this setting, we derive an approximation of the average throughput at the data collector. Numerical results validate the accuracy of our analysis in the single-hop and multi-hop networks and confirm the tightness of our approximation in the case of the star-shaped topology. [ABSTRACT FROM PUBLISHER]

This paper presents an analytical study of the stable throughput for multiple broadcast sessions in a multi-hop wireless tandem network with random access. Intermediate nodes leverage on the broadcast nature of wireless medium access to perform inter-session network coding among different flows. This problem is challenging due to the interaction among nodes, and has been addressed so far only in the saturated mode where all nodes always have packet to send, which results in infinite packet delay. In this paper, we provide a novel model based on multi-class queueing networks to investigate the problem in unsaturated mode. We devise a theoretical framework for computing maximum stable throughput of network coding for a slotted ALOHA-based random access system. Using our formulation, we compare the performance of network coding and traditional routing. Our results show that network coding leads to high throughput gain over traditional routing. We also define a new metric, network unbalance ratio (NUR), that indicates the unbalance status of the utilization factors at different nodes. We show that although the throughput gain of the network coding compared to the traditional routing decreases when the number of nodes tends to infinity, NUR of the former outperforms the latter. We carry out simulations to confirm our theoretical analysis. [ABSTRACT FROM PUBLISHER]

There are two fundamentally different fronthaul techniques in the downlink communication of cloud radio access network (C-RAN): the data-sharing strategy and the compression-based strategy. Under the former strategy, each user's message is multicast from the central processor (CP) to all the serving remote radio heads (RRHs) over the fronthaul network, which then cooperatively serve the users through joint beamforming; while under the latter strategy, the user messages are first beamformed then quantized at the CP, and the compressed signal is unicast to the corresponding RRH, which then decompresses its received signal for wireless transmission. Previous works show that in general the compression-based strategy outperforms the data-sharing strategy. This paper, on the other hand, points out that in a C-RAN model where the RRHs are connected to the CP via multihop routers, data-sharing can be superior to compression if the network coding technique is adopted for multicasting user messages to the cooperating RRHs, and the RRH's beamforming vectors, the user-RRH association, and the network coding design over the fronthaul network are jointly optimized based on the techniques of sparse optimization and successive convex approximation. This is in comparison to the compression-based strategy, where information is unicast over the fronthaul network by simple routing, and the RRH's compression noise covariance and beamforming vectors, as well as the routing strategy over the fronthaul network are jointly optimized based on the successive convex approximation technique. The observed gain in overall network throughput is due to that information multicast is more efficient than information unicast over the multihop fronthaul of a C-RAN. [ABSTRACT FROM PUBLISHER]

Unmanned aerial vehicles (UAVs) recently enabled a myriad of new applications spanning domains from personal entertainment to surveillance and monitoring. In this paper, we focus on using several small UAVs collaboratively to provide extended reach to an online video monitoring system for inspection of industrial installations. We make use of 802.11 radios on low-cost commercial-off-the-shelf UAVs, set up a time-division multiple access overlay protocol to avoid mutual interference, and enable high channel utilization in multihop networks. In particular, we provide a model for the quality of the UAV-to-UAV link, in terms of packet delivery ratio as a function of distance, packet size, and orientation, based on an extensive measurement campaign. We show that this platform is not omnidirectional in the horizontal plane and that UAV-to-UAV communication ceases around 75 m. Concerning the operation in a multihop mode to allow extending the network, the paper derives the optimal number of hops that maximize the end-to-end throughput, as well as the corresponding hop lengths. We validate our mathematical model with extensive experimental measurements transmitting payloads up to 200 m (over 802.11 g at 54 MBps). [ABSTRACT FROM PUBLISHER]

Underwater acoustic (UWA) networks are a key form of communications for human exploration and activities in the oceanographic space of the earth. A fundamental issue of UWA communications is large propagation delays due to water medium, which has posed a grand challenge in UWA network protocol design. Conventional wisdom of addressing this issue is to live with this disadvantage by inserting a guard interval to introduce immunity to propagation delays. Recent advances in interference alignment (IA) open up a new direction to address this issue and promise a great potential to improve network throughput by exploiting large propagation delays. In this paper, we investigate propagation delay-based IA (PD-IA) in multi-hop UWA networks. We first develop a set of simple constraints to characterize PD-IA feasible region at the physical layer. Based on the set of PD-IA constraints, we develop a distributed PD-IA scheduling algorithm to greedily maximize interference overlapping possibilities in a multi-hop UWA network. Simulation results show that the proposed PD-IA algorithm yields higher throughput than an idealized benchmark algorithm without propagation delays, indicating that large propagation delays are not adversarial but beneficial for network throughput performance. [ABSTRACT FROM AUTHOR]

Decentralized coded content caching for next generation cellular networks is studied. The contents are linearly combined and cached in under-utilized caches of user terminals and its throughput capacity is compared with decentralized uncoded content caching. In both scenarios, we consider multihop device-to-device communications and the use of femtocaches in the network. It is shown that decentralized coded content caching can increase the network throughput capacity compared to decentralized uncoded caching by reducing the number of hops needed to deliver the desired content. Furthermore, the throughput capacity for Zipfian content request distribution is computed and it is shown that the decentralized coded content cache placement can increase the throughput capacity of cellular networks by a factor of (\log (n))^2 where $n$ is the number of nodes served by a femtocache. [ABSTRACT FROM PUBLISHER]

In this paper, we consider random-access wireless multihop networks, with multipacket reception capabilities, where multiple flows are forwarded to the gateways through node disjoint paths. We explore the issue of allocating flow on multiple paths, exhibiting both intra- and interpath interference, in order to maximize average aggregate flow throughput (AAT) and provide bounded packet delay. A distributed flow allocation scheme is proposed where allocation of flow on paths is formulated as an optimization problem. Through an illustrative topology, it is shown that the corresponding problem is nonconvex. Furthermore, a simple but accurate model is employed for the AAT achieved by all flows, which captures both intra- and interpath interference through the signal-to-interference-plus-noise ratio (SINR) model. The proposed scheme is evaluated through Ns2 simulations of several random wireless scenarios. Simulation results reveal that the model employed accurately captures the AAT observed in the simulated scenarios, even when the assumption of saturated queues is removed. Simulation results also show that the proposed scheme achieves significantly higher AAT for the vast majority of the wireless scenarios explored than for the following flow allocation schemes: one that assigns flows on paths on a round-robin fashion, one that optimally utilizes the best path (BP) only, and another one that assigns the maximum possible flow on each path. Finally, a variant of the proposed scheme is explored, where interference for each link is approximated by considering its dominant interfering nodes only. [ABSTRACT FROM PUBLISHER]

Batched sparse (BATS) codes are a promising technique for reliable data transmission in multihop wireless networks. A BATS code consists of an outer code and an inner code, the design of which can be separated. In this paper, we investigate the design of the inner code and focus on maximizing the expected batch transfer matrix rank normalized by the total number of packets transmitted by both the source and intermediate nodes. By allowing different recoding decisions at different nodes, the problem is formulated as a nonlinear integer programming (NLIP) problem, which is non-deterministic polynomial (NP)-hard in general. We derive a noniterative formula to simplify the evaluation of the expected batch transfer matrix rank. By considering large finite fields and relaxing the integer constraints, we obtain an upper bound on the optimal value of the original maximization NLIP problem. We also derive a centralized and a decentralized algorithm to find suboptimal solutions of the NLIP problem, with different tradeoffs between complexity and performance. Numerical results show that our proposed inner codes outperform the standard BATS, and achieve very close to the upper bound, which verifies the near optimality of our algorithms. [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]

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]

Denial-of-service attacks launched by malicious jammers can pose significant threats to infrastructure-less wireless networks without a centralized controller. While significant recent research efforts have dealt with such attacks and several possible countermeasures have been proposed, little attention has been paid to the idea of cooperative anti-jamming. Inspired by this observation, this paper proposes and studies a cooperative anti-jamming scheme designed to enhance the quality of links degraded by jammers. To achieve this objective, users are allowed to cooperate at two levels. First, they cooperate to optimally regulate their channel access probabilities, so that jammed users gain a higher share of channel utilization. Second, users leverage multiple-input single-output cooperative communication techniques to enhance the throughput of jammed links. The problem of optimal cooperative anti-jamming is formulated as a distributed pricing-based optimization problem, and a best-response algorithm is proposed to solve it in a distributed way. Simulations demonstrate that the proposed algorithm achieves considerable gains (compared with traditional non-cooperative anti-jamming) especially under heavy traffic or high jamming power. Furthermore, the proposed distributed algorithm is shown to achieve close-to-global optimality with moderate traffic load. [ABSTRACT FROM PUBLISHER]

This paper studies the coexistence of heterogeneous multi-hop networks, which use different physical-layer technologies. We propose a new paradigm, called cooperative interference mitigation (CIM), which exploits recent advancement in interference cancellation (IC), such as technology-independent multiple output. CIM makes it possible for disparate networks to cooperatively mitigate the interference to/from each other to enhance everyone’s performance. We first show the feasibility of CIM among heterogeneous multi-hop networks by exploiting only channel-ratio information. Then, we establish two tractable models to characterize the CIM behaviors of both networks by using full IC and receiver-side IC only. We propose two bi-criteria optimization problems aiming at maximizing both networks’ throughput, while cooperatively canceling the interference between them based on our two models. Several simulations are carried out to compare the Pareto-optimal throughput curves by using our CIM paradigms and traditional interference-avoidance (IAV) paradigm. By comparing the results from CIM and IAV, we show that CIM could remarkably improve the coexisting networks’ throughput in different network settings. [ABSTRACT FROM PUBLISHER]

Recently, degree-of-freedom (DoF)-based models have been widely used to study MIMO network performance. Existing DoF-based models differ in their interference cancellation (IC) behavior and many of them suffer from either loss of solution space or possible infeasible solutions. To overcome these limitations, a new DoF-based model, which employs an IC scheme based on node-ordering was proposed. In this paper, we apply this new DoF IC model to study a throughput maximization problem in a multihop MIMO network. The problem formulation involves joint consideration of flow routing and DoF allocation and falls in the form of a mixed-integer linear program (MILP). Our main contribution is an efficient polynomial time algorithm that offers a competitive solution to the MILP through a series of linear programs (LPs). The algorithm employs a sequential fixing framework to obtain an initial feasible solution and then improves the solution by exploiting: 1) the impact of node ordering on DoF consumption for IC at a node and 2) route diversity in the network. Simulation results show that the solutions obtained by our proposed algorithm are competitive and feasible. [ABSTRACT FROM PUBLISHER]

In covert communication, Alice tries to communicate with Bob without being detected by a warden Willie. When the distance between Alice and Bob becomes large compared with the distance between Alice and Willie(s), the performance of covert communication will be degraded. In this case, multi-hop message transmission via intermediate relays can help to improve the performance. Hence, in this paper, multi-hop covert communication over a moderate size network and in the presence of multiple collaborating Willies is considered. The relays can transmit covertly using either a single key for all relays or different independent keys at the relays. For each case, we develop efficient algorithms to find optimal paths with maximum throughput and minimum end-to-end delay between Alice and Bob. As expected, employing multiple hops significantly improves the ability to communicate covertly versus the case of a single-hop transmission. Furthermore, at the expense of more shared key bits, analytical results and numerical simulations demonstrate that the multi-hop covert communication with different independent keys at the relays has better performance than the multi-hop covert communication with a single key. [ABSTRACT FROM AUTHOR]

The optimum designs of multihop networks operating in an interference-limited environment are studied in this paper. The objective is to identify the optimum operation parameters that can maximize the end-to-end throughput of a multihop link in the network. The optimum designs are performed with respect to two parameters, the number of hops, and the signal-to-interference ratio (SIR) threshold for successful transmission. Under a fixed total transmission power, more hops means shorter distance for each hop, but also less power per hop and longer delays. A higher SIR threshold can achieve a higher throughput by employing high-order modulations, but at the cost of a higher outage probability. We capture these tradeoff relationships by deriving the throughput, which is expressed as an explicit function of a number of system parameters. It is shown through theoretical analysis that the throughput is quasi-concave in the number of hops or the SIR threshold, and the optimum design parameters that can maximize the throughput are obtained analytically and verified through simulations. [ABSTRACT FROM AUTHOR]

In this paper, we study the achievable throughput of batched temporal network coding in multi-hop erasure channels, where network coding is applied only within small coding blocks and each communication hop is modeled as a Gilbert–Elliott (GE) packet erasure channel. The GE channel is a 2-state Markov model that is commonly used for channels with memory. While channel memory does not affect the end-to-end capacity of multi-hop erasure channels, we show that it degrades the end-to-end throughput, when batched network coding with finite batch size is applied, due to the higher variance in erasures within one coding block. On the other hand, if the initial channel state information is available, the channel variance can be significantly reduced. We show that this fact can be utilized for improving the efficiency of the recoding operations at the intermediate nodes, and hence improve the end-to-end throughput of batched network coding schemes. Specifically, we propose adaptive recoding operations, where the network coded packets are adaptively generated based on the number of received packets and the initial channel state for each coding block. The simulation results show that the proposed adaptive recoding scheme significantly enhances the end-to-end throughput of batched network coding over multi-hop GE channels. [ABSTRACT FROM PUBLISHER]

Interference neutralization (IN) is regarded as a promising interference management techniques for multi-hop wireless networks. Yet most existing results of IN are limited to two-hop networks such as the relay-aided cellular network. Little progress has been made so far in the exploration of IN in generic multi-hop (more than two hops) networks. This paper aims to bridge this gap by developing an optimization framework for IN in a generic multi-hop network with the objective of maximizing the end-to-end throughput of multiple coexisting communication sessions. We first derive a mathematical model for IN in a special one-hop network to characterize the capability of IN, and then generalize this model to a multi-hop network. Based on the IN model, we develop a cross-layer optimization framework for a multi-hop network with the objective of fully translating the benefits of IN to the end-to-end throughput of the multi-hop sessions. To evaluate the performance of IN in multi-hop networks, we compare its performance against the case where IN is not employed. Simulation results show that the use of IN can significantly (more than 50%) increase the session throughput and, more notably, the throughput gain of IN increases with the node density and traffic intensity in the network. [ABSTRACT FROM PUBLISHER]

This paper studies the design and secrecy performance of linear multihop networks, in the presence of randomly distributed eavesdroppers in a large-scale 2-D space. Depending on whether there is feedback from the receiver to the transmitter, we study two transmission schemes: an ON–OFF transmission (OFT) and a non-ON–OFF transmission (NOFT). In the OFT scheme, transmission is suspended if the instantaneous received signal-to-noise ratio (SNR) falls below a given threshold, whereas, there is no suspension of transmission in the NOFT scheme. We investigate the optimal design of the linear multiple network in terms of the optimal rate parameters of the wiretap code as well as the optimal number of hops. These design parameters are highly interrelated, since more hops reduce the distance of per-hop communication, which completely changes the optimal design of the wiretap coding rates. Despite the analytical difficulty, we are able to characterize the optimal designs and the resulting secure transmission throughput in mathematically tractable forms in the high SNR regime. Our numerical results demonstrate that our analytical results obtained in the high SNR regime are accurate at practical SNR values. Hence, these results provide useful guidelines for designing linear multihop networks with targeted physical layer security performance. [ABSTRACT FROM PUBLISHER]

Efficient communication through a multi-hop network with packet loss requires random linear network coding schemes with low computation cost and high throughput. In this paper, we propose a low-density parity-check (LDPC)-based framework for constructing chunked code, a variation of random linear network code with low encoding/decoding computational cost and small coefficient vector overhead. Two classes of chunked codes with LDPC structures, named uniform LDPC-chunked codes and overlapped LDPC-chunked (OLC) codes, are studied under a general chunk transfer matrix model. ULC codes achieve rates close to the optimum and perform better than existing chunked codes that employ parity-check constraints. OLC codes are overlapped chunked codes, where it is not necessary to generate new packets for encoding, and demonstrate much higher rates in certain scenarios than the state-of-the-art designs of overlapped chunked codes. These results justifies the feasibility of this LDPC approach for communication through multi-hop networks with packet loss. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new caching scheme for a random wireless device-to-device (D2D) network of $n$ nodes with local caches, where each node intends to download files from a prefixed library via D2D links. Our proposed caching delivery includes two stages, employing distributed MIMO and hierarchical cooperations, respectively. The distributed MIMO is applied to the first stage between source nodes and neighbors of the destination node. The induced multiplexing gain and diversity gain increase the number of simultaneous transmissions, improving the throughput of the network. The hierarchical cooperations are applied to the second stage to facilitate the transmissions between the destination node and its neighbors. The two stages together exploit spatial degrees of freedom as well as spatial reuse. We develop an uncoded random caching placement strategy to serve this cooperative caching delivery. Analytical results show that the average aggregate throughput of the network scales almost linearly with $n$ , with a vanishing outage probability. Furthermore, we derive an explicit expression of the optimal throughput as a function of system parameters, such as pathloss factor under a target outage probability. Analytical and numerical results demonstrate that our proposed scheme outperforms existing ones when the local cache size is limited. [ABSTRACT FROM PUBLISHER]

While considerable work has addressed the optimal AoI under different circumstances in single-hop networks, the exploration of AoI in multi-hop wireless networks is rarely attempted. More importantly, the inherent relationships between AoI and throughput are yet to be explored, especially in multi-hop networks. This paper studies AoI in multi-hop wireless networks and explores its potential relationships with throughput for the very first time, particularly focusing on the impacts of flexible routes on the two metrics, i.e., AoI and throughput. By developing a rigorous mathematical model with interference, channel allocation, link scheduling, and routing path selection taken into consideration, we build the interrelation between AoI and throughput in multi-hop networks. A multi-criteria optimization problem is formulated with the goal of simultaneously minimizing AoI and maximizing network throughput. By qualitatively analyzing their relationships, we exhibit that the two metrics may conflict with each other, implying the optimal solutions for the multi-criteria problem will include a set of Pareto-optimal points rather than a single point existing in the traditional optimization problem. We resort to a novel approach by transforming the multi-criteria problem into a single objective one so as to find the weakly Pareto-optimal points iteratively, thereby allowing us to screen all Pareto-optimal points for the solution. Through formal proof, our solution is demonstrated to be able to identify all Pareto-optimal points and terminate in a finite number of iterations. We conduct the simulation evaluation to identify the optimal tradeoff points of AoI and throughput, demonstrating that one performance metric may improve at the expense of degrading the other, with the routing path found as one of the key factors in determining such a tradeoff. [ABSTRACT FROM AUTHOR]

For improving the throughput while simultaneously enhancing the security in aeronautical ad-hoc networking (AANET), a channel quality indicator (CQI)-mapped spatially modulated sparse code multiple access (SM-SCMA) scheme is proposed in this paper. On one hand, we exploit the joint benefits of spatial modulation and SCMA for boosting the data rate. On the other hand, a physical-layer secret key is generated by varying the SM-SCMA mapping patterns based on the instantaneous CQI in the desired link. This guarantees the security of AANETs, since this secret key is not exchanged between the source aeroplane and its destination. Due to the line-of-sight (LoS) propagation in the AANET, other aeroplanes or eavesdroppers may detect the signals delivered in the desired link. However, they are unable to translate the detected signals into the original confidential information, even if multiple copies of the signals are recoined over multiple hops of the AANET, because they have no knowledge of the CQI-based SM-SCMA mapping pattern. The performance of the CQI-mapped SM-SCMA is evaluated in terms of both its bit error rate and its ergodic secrecy rate, which substantiates that the proposed scheme secures the confidential information exchange in the multi-hop AANET. [ABSTRACT FROM AUTHOR]

Hybrid wireless network is composed of both ad hoc transmissions and cellular transmissions. Under the $L$ -maximum-hop routing policy, flow is transmitted in the ad hoc mode if its source and destination are within $L$ hops away; otherwise, it is transmitted in the cellular mode. Existing works study the hybrid wireless network capacity as a function of $L$ so as to find the optimal $L$ to maximize the network capacity. In this paper, we consider two more factors: traffic model and base station access mode. Different from existing works, which only consider the uniform traffic model, we consider a traffic model with social behavior. We study the impact of traffic model on the optimal routing policy. Moreover, we consider two different access modes: one-hop access (each node directly communicates with base station) and multi-hop access (node may access base station through multiple hops due to power constraint). We study the impact of access mode on the optimal routing policy. Our results show that: 1) the optimal $L$ does not only depend on traffic pattern, but also the access mode; 2) one-hop access provides higher network capacity than multi-hop access at the cost of increasing transmitting power; and 3) under the one-hop access mode, network capacity grows linearly with the number of base stations; however, it does not hold with the multi-hop access mode, and the number of base stations has different effects on network capacity for different traffic models. [ABSTRACT FROM AUTHOR]

Being readily available in most of 802.11 radios, multirate capability appears to be useful as WiFi networks are getting more prevalent and crowded. More specifically, it would be helpful in high-density scenarios because internode distance is short enough to employ high data rates. However, communication at high data rates mandates a large number of hops for a given node pair in a multihop network and thus, can easily be depreciated as per-hop overhead at several layers of network protocol is aggregated over the increased number of hops. This paper presents a novel multihop, multirate adaptation mechanism, called multihop transmission opportunity (MTOP), that allows a frame to be forwarded a number of hops consecutively to minimize the MAC-layer overhead between hops. This seemingly collision-prone nonstop forwarding is proved to be safe via analysis and USRP/GNU Radio-based experiment in this paper. The idea of MTOP is in clear contrast to the conventional opportunistic transmission mechanism, known as TXOP, where a node transmits multiple frames back-to-back when it gets an opportunity in a single-hop WLAN. We conducted an extensive simulation study via OPNET, demonstrating the performance advantage of MTOP under a wide range of network scenarios. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of link scheduling in multihop wireless networks under general interference constraints. Our goal is to design scheduling schemes that do not use per-flow or per-destination information, maintain a single data queue for each link, and exploit only local information, while guaranteeing throughput optimality. Although the celebrated back-pressure algorithm maximizes throughput, it requires per-flow or per-destination information. It is usually difficult to obtain and maintain this type of information, especially in large networks, where there are numerous flows. Also, the back-pressure algorithm maintains a complex data structure at each node, keeps exchanging queue-length information among neighboring nodes, and commonly results in poor delay performance. In this paper, we propose scheduling schemes that can circumvent these drawbacks and guarantee throughput optimality. These schemes use either the readily available hop-count information or only the local information for each link. We rigorously analyze the performance of the proposed schemes using fluid limit techniques via an inductive argument and show that they are throughput-optimal. We also conduct simulations to validate our theoretical results in various settings and show that the proposed schemes can substantially improve the delay performance in most scenarios. [ABSTRACT FROM PUBLISHER]

The cost of energy consumption is an important concern for network operators. In this paper, we study an energy-related problem that focuses on network-wide energy consumption. In the first part of this work, we study how to maximize throughput under a network-wide energy constraint. We formulate this problem as a mixed-integer nonlinear program (MINLP). This formulation differs from prior efforts as it considers a non-zero device power, which complicates the problem. We propose a novel piece-wise linear approximation to transform the nonlinear constraints into linear constraints. We prove that the solution developed under this approach is near-optimal with a guaranteed performance bound. In the second part, we generalize the problem in the first part via a multicriteria optimization framework, which simultaneously optimizes throughput and total network energy. We show how weakly Pareto-optimal solutions can characterize an optimal throughput-energy curve. We offer some interesting properties of the optimal throughput-energy curves, which are useful to both network operators and end-users. Our results fill in some important gaps in the current understanding on optimizing total network energy. [ABSTRACT FROM PUBLISHER]

Multipath routing can offer various advantages for wireless multihop networks. Among those advantages, in this paper, we focus on an advantage of multipath routing for security using the notion of information-theoretic security. We formulate an optimization problem that maximizes the transmission rate from a source node to a destination node with information-theoretic security constraints to avoid eavesdropping that can be carried out at some nodes within a wireless multihop network. Binary erasure channel (BEC) modeling is employed to model wireless links that suffer from fading and interference. It is shown that the proposed throughput maximization problem is a linear optimization problem and the optimal rate allocation can be found by standard optimization techniques. We also study performance analysis including an asymptotic analysis to see whether or not multipath routing (with equal rate allocation) could be secure in terms of an information-theoretic security point of view. Through performance analysis, we can show that multipath routing can provide not only more secure routing against eavesdropping, but also a higher throughput as more multipaths are available. [ABSTRACT FROM PUBLISHER]

This paper considers the problem of throughput optimal routing/scheduling in a multi-hop constrained queueing network with random connectivity whose special cases include opportunistic multi-hop wireless networks and input-queued switch fabrics. The main challenge in the design of throughput optimal routing policies is closely related to identifying appropriate and universal Lyapunov functions with negative expected drift. The few well-known throughput optimal policies in the literature are constructed using simple quadratic or exponential Lyapunov functions of the queue backlogs and as such they seek to balance the queue backlogs across network independent of the topology. By considering a class of continuous, differentiable, and piece-wise quadratic Lyapunov functions, this paper provides a large class of throughput optimal routing policies. The proposed class of Lyapunov functions allow for the routing policy to control the traffic along short paths for a large portion of state-space while ensuring a negative expected drift. This structure enables the design of a large class of routing policies. In particular, and in addition to recovering the throughput optimality of the well-known backpressure routing policy, an opportunistic routing policy with congestion diversity is proved to be throughput optimal. [ABSTRACT FROM AUTHOR]

This paper investigates the speed limit of information propagation in large-scale multihop wireless networks, which provides fundamental understanding of the fastest information transportation and delivery that a wireless network is able to accommodate. We show that there exists a unified speed upper bound for broadcast and unicast communications in large-scale wireless networks. When network connectivity is considered, this speed bound is a function of node density. If the network noise is constant, the bound is a constant when node density exceeds a threshold; if the network noise is an increasing function of node density, the bound decreases to zero when node density approaches infinity. As achieving the speed bound places strict requirements on node locations, we also quantify the gap between the actual achieved speed and the desired bound in random networks in which the relay nodes are not located as desired. We find that the gap converges to zero exponentially as node density increases to infinity. [ABSTRACT FROM PUBLISHER]

5G mobile networks are expected to provide pervasive high speed wireless connectivity and support increasingly resource intensive user applications. Network hyper-densification therefore becomes necessary, though connecting to the Internet tens of thousands of base stations is non-trivial, especially in urban scenarios where optical fibre is difficult and costly to deploy. The millimetre wave (mm-wave) spectrum is a promising candidate for inexpensive multi-Gbps wireless backhauling, but exploiting this band for effective multi-hop data communications is challenging. In particular, resource allocation and scheduling of very narrow transmission/ reception beams require to overcome terminal deafness and link blockage problems, while managing fairness issues that arise when flows encounter dissimilar competition and traverse different numbers of links with heterogeneous quality. In this paper, we propose WiHaul, an airtime allocation and scheduling mechanism that overcomes these challenges specific to multi-hop mm-wave networks, guarantees max-min fairness among traffic flows, and ensures the overall available backhaul resources are fully utilised. We evaluate the proposed WiHaul scheme over a broad range of practical network conditions, and demonstrate up to 5× individual throughput gains and a five-fold improvement in terms of measurable fairness, over recent mm-wave scheduling solutions. [ABSTRACT FROM AUTHOR]

D2D communications are considered as effective means to achieve vehicle-to-vehicle (V2V) communications, which can be used to improve the performance in vehicular ad hoc networks (VANETs). In this paper, we investigate the resource allocation and interference management based on clustering mechanism in the D2D communications under-laying VANETs aiming to optimize resource utilization efficiency. Firstly, given the transmission resources of intra-cluster for D2D communications, we design a vehicle clustering algorithm to improve intra-cluster resource efficiency and nullify the intra-cluster interference. Secondly, by analyzing the wireless service in VANETs, a cooperative communication scheme with optimized resource utilization is proposed to maximize intra-cluster spectral efficiency. Thirdly, when uplink spectrums are shared, an interference neutralization (IN) model is developed to manage inter-cluster interference, while each vehicle is equipped with one antenna and there is no extra antenna for interference cancellation. In accordance with the IN model, a cross-layer optimization frame for multi-hop VANETs is proposed to maximize the end-to-end throughput of multiple coexisting communication sessions. To evaluate the performance, we select the method without cooperative communication and IN as a benchmark and compare it against the method with cooperative communication only and the method with both cooperative communication and IN. The simulation results show that the method that uses cooperative communication and IN can dramatically increase the throughput. Furthermore, the throughput gains increase along with vehicle density growing in VANETs. [ABSTRACT FROM AUTHOR]

The deployment of unmanned aerial vehicle (UAV) for surveillance and monitoring gives rise to the confidential information leakage challenge in both civilian and military environments. The security and covert communication problems for a pair of terrestrial nodes against UAV surveillance are considered in this paper. To overcome the information leakage and increase the transmission reliability, a multi-hop relaying strategy is deployed. We aim to optimize the throughput by carefully designing the parameters of the multi-hop network, including the coding rates, transmit power, and required number of hops. In the secure transmission scenario, the expressions of the connection probability and secrecy outage probability of an end-to-end path are derived and the closed-form expressions of the optimal transmit power, transmission and secrecy rates under a fixed number of hops are obtained. In the covert communication problem, under the constraints of the detection error rate and aggregate power, the sub-problem of transmit power allocation is a convex problem and can be solved numerically. Simulation shows the impact of network settings on the transmission performance. The trade-off between secrecy/covertness and efficiency of the multi-hop transmission is discussed which leads to the existence of the optimal number of hops. [ABSTRACT FROM AUTHOR]

Cooperation has become an essential element in spectrum sharing between the primary and secondary networks. A new trend in cooperation is to allow the primary and secondary networks to cooperate on the node level for data forwarding. This new paradigm allows to pool network resources from both the primary and secondary networks and allows users in each network to access a much richer network infrastructure in a combined network. This paper offers an in-depth study of such node-level cooperation by explaining its optimal throughput curve—the maximum achievable throughput for both the primary and secondary users. We formulate the problem as a multicriteria optimization problem with the goal of maximizing the throughput of both the primary and secondary users. Through a novel approach based on weighted Chebyshev norm, we transform the multicriteria optimization problem into a single criteria optimization problem and find a sequence of Pareto-optimal points iteratively. Based on the Pareto-optimal points, we construct the throughput curve and show that it provides an $\varepsilon $ -approximation to the optimal curve. We prove some important properties of the optimal throughput curve. Through a case study, we show that the throughput region (the area under the throughput curve) under node-level cooperation is substantially larger than that when there is no node-level cooperation. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel buffer-aided link selection scheme based on network coding in the multiple-hop relay network. The proposed scheme significantly increases transmission throughput by applying data buffers at the relays to decrease the outage probability and using network coding to increase the data rate. The closed-form expressions of both average throughput and packet delay are successfully derived. The proposed scheme not only has significantly higher throughput than both the traditional and existing buffer-aided max-link schemes but smaller average packet delay than the max-link scheme as well, making it an attractive scheme in practice. [ABSTRACT FROM PUBLISHER]

To improve the efficiency of wireless data communications, new physical-layer transmission methods based on known-interference cancelation (KIC) have been developed. These methods share the common idea that interference can be canceled when its content is known. Existing work on KIC mainly focuses on single-hop or two-hop networks, with physical-layer network coding and full-duplex communications as typical examples. This paper extends the idea of KIC to general multihop networks and proposes an end-to-end KIC (E2E-KIC) transmission method, together with its medium access control (MAC) design. With E2E-KIC, multiple nodes in a flow passing through a few nodes in an arbitrary topology can simultaneously transmit and receive on the same channel. We first present a theoretical analysis on the effectiveness of E2E-KIC in an idealized case. Then, to support E2E-KIC in multihop networks with an arbitrary topology, we propose an E2E-KIC-supported MAC protocol (E2E-KIC MAC), which is based on an extension of the Request-to-Send/Clear-to-Send mechanism in the IEEE 802.11 MAC. We also analytically analyze the performance of the proposed E2E-KIC MAC in the presence of hidden terminals. Simulation results illustrate that the proposed E2E-KIC MAC can improve network throughput and reduce end-to-end delay. [ABSTRACT FROM PUBLISHER]

Previous works on multicast capacity mainly focus on deriving asymptotic order results in large-scale wireless networks. While they can explore the general scaling laws of throughput capacity, it is also of great interest for practical concern to predict the exact achievable throughput in networks with an arbitrary finite number of nodes. In this paper, we investigate the nonasymptotic throughput and delay of multihop wireless networks for multicast applications wherein for each source node, $k$ nodes are randomly selected as receivers. It is challenging for the exact performance analysis since multicast transmission has a dynamic nature due to the following factors: 1) random distribution of nodes; 2) bursty traffic arrivals; and 3) different timescales for transient analysis. To tackle the problem, we propose an explicit analytical model and develop a multicast routing scheme, which accounts for these aspects. With our proposed model, we derive lower bound (LB) and upper bound (UB) on nonasymptotic multicast throughput and delay using stochastic network calculus. We show that the performance results hold for all timescales and network sizes and are strongly correlated to data burstiness and the number of receivers. While we investigate from a nonasymptotic point of view, our results can also cover the asymptotic scaling laws. Simulations are conducted to further verify the accuracy of the analytical bounds. [ABSTRACT FROM AUTHOR]

In this paper, we extend the information theoretic framework that was developed in earlier works to multi-hop network settings. For a given network, we construct a novel deterministic model that quantifies the ability of the network in transmitting private and common messages across users. Based on this model, we formulate a linear optimization problem that explores the throughput of a multi-layer network, thereby offering the optimal strategy as to what kind of common messages should be generated in the network to maximize the throughput. With this deterministic model, we also investigate the role of feedback for multi-layer networks, from which we identify a variety of scenarios in which feedback can improve transmission efficiency. Our results provide fundamental guidelines as to how to coordinate cooperation between users to enable efficient information exchanges across them. [ABSTRACT FROM AUTHOR]

ZigBee is a widely used wireless technology in low-power and short-range scenarios such as the Internet of Things, sensor networks, and industrial wireless networks. However, the traditional ZigBee supports only one data rate, 250 Kbps, which thoroughly limits ZigBee’s efficiency in dynamic wireless channels. In this paper, we propose Mrs. Z, a novel physical layer design to enable multi-rate selection in ZigBee with lightweight modification on the legacy ZigBee modules. The key idea is to change the single spectrum spreading length to multiple ones. Correspondingly, to support the rate adaptation to the channel variations, we propose a bit-error-based rate selection scheme, which predicts BER by leveraging the physical properties of ZigBee to calculate the confidence for each symbol in transmission. Then, the receiver selects the rate based on the negative impact on throughput incurred by bit errors and gives feedback to the transceiver. We implement Mrs. Z on USRPs and evaluate its performance in different scenarios. Experiment results demonstrate that Mrs. Z achieves about 1.15, 1.2, and 1.8 $\times$ average throughput compared to the classic smart pilot, softrate, and the traditional ZigBee. [ABSTRACT FROM AUTHOR]

Multihop underwater acoustic sensor networks (UASNs) suffer from low throughput caused by low channel utilization and unreasonable bandwidth allocation. The existing media access control (MAC) protocols for UASNs mainly aim to improve channel utilization but neglect to optimize bandwidth, so that they cannot achieve high throughput in miltihop networks. We propose the idea of joint bandwidth optimization and MAC in this paper. We first present a system model to optimize bandwidth for miltihop UASNs. Both the complicated interference relations between links and the different transmission demands of nodes are modeled. Thus, it can accurately reflect the characteristics of miltihop UASNs. By analyzing a 1-D linear miltihop network, we find and formulate a maximum hop number which is determined by nodes’ traffic load and channel capacity. The other finding is that an optimal scheduling needs to allocate the bandwidth based on traffic load, and the nodes with more traffic load should be allocated more bandwidth. This finding inspire us to develop a distributed traffic-based scheduling MAC protocol. This protocol can optimize bandwidth allocation by letting the older packet to be transmitted preferentially. To improve channel utilization, multiple packets are allowed to be transmitted in each data transmission round. Simulation results have confirmed that our protocol can achieve excellent performance owing to its core idea of joint bandwidth optimization and MAC. [ABSTRACT FROM PUBLISHER]