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LoRaWAN forms a one-hop star topology where LoRa nodes send data via one-hop uplink transmission to a LoRa gateway. If the LoRa gateway can be jammed by attackers, it may not be able to receive any data from any nodes in the network. Our empirical study shows that although the LoRa physical layer (PHY) is robust and resilient by design, it is still vulnerable to synchronized jamming chirps. Potential protection solutions (e.g., collision recovery, parallel decoding) may fail to extract LoRa packets if an attacker transmits synchronized jamming chirps at higher power. To protect the LoRa PHY from such attacks, we propose a new protection method that can separate LoRa chirps from jamming chirps by leveraging their difference in power domain. We note that the new protection solution is orthogonal to existing solutions that leverage the chirp misalignment in the time domain or the frequency disparity in the frequency domain. We conduct experiments with COTS LoRa nodes and software-defined radios with varied experiment settings such as different spreading factors, bandwidths, and code rates. Results show that synchronized jamming chirps at high power can jam all previous solutions, whereas our protection solution can effectively protect LoRa gateways from the jamming attacks.

IEEE 802.11ax is the standard for the new generation WiFi networks. In this paper, we formulate the problem of joint access point (AP) placement and power-channel-resource unit assignment for 802.11ax-based dense WiFi. The objective is to minimize the number of APs. Two quality-of-service (QoS) requirements are to be fulfilled: (1) a two-tier throughput requirement which ensures that the throughput of each station is good enough, and (2) a fault tolerance requirement which ensures that the stations could still use WiFi even when some APs fail. We prove that this problem is NP-hard. To tackle this problem, we first develop an analytic model to derive the throughput of each station under the OFDMA mechanism and a widely used interference model. We then design a heuristic algorithm to find high-quality solutions with polynomial time complexity. Simulation results under both fixed-user and mobile-user cases show that: (1) when the area is small (50 x 50 m2), our algorithm gives the optimal solutions; when the area is larger (80 x 60 m2), our algorithm can reduce the number of APs by 34.9-87.7% as compared to the Random and Greedy algorithms. (2) Our algorithm can always get feasible solutions that fulfill the QoS requirements.

Due to their flexibility and low cost deployment, unmanned aerial vehicles (UAV) will most likely act as base stations and backhaul relays in the next generation of wireless communication systems. However, these UAVs---in the untethered mode---can only operate for a finite time due to limited energy they carry in their batteries. In free-space optical communications, one solution is to transport both the data and the energy from the source to the UAV through the laser beam---a concept known as simultaneous lightwave information and power transfer (SLIPT). In this study, we have analyzed the SLIPT scheme for laser-powered decode-and-forward UAV relays in an optical wireless backhaul. The major goal of this study is to optimally allocate the received beam energy between the decoding circuit, the transmitting circuit and the rotor block of the relay in order to maximize a quality-of-service metric such as maximum achievable rate, outage or error probabilities. As expected, we note that the optimal power allocation depends heavily on the source-relay and relay-destination channel conditions. In the final part of this study, we have maximized the operational time of the UAV relay given that the maximum achievable rate stays above a certain threshold in order to meet a minimum quality-of-service requirement.

As a low-power and low-cost wireless protocol, the promising ZigBee has been widely used in sensor networks and cyber-physical systems. Since ZigBee based networks usually adopt tree or cluster topology, the convergecast scenarios are common in which multiple transmitters send packets to one receiver, leading to the severe collision problem. The conventional ZigBee adopts carrier sense multiple access with collisions avoidance to avoid collisions, which introduces additional time/energy overhead. The state-of-the-art methods resolve collisions instead of avoidance, in which mZig decomposes a collision by the collision itself and reZig decodes a collision by comparing with reference waveforms. However, mZig falls into high decoding errors only exploiting the signal amplitudes while reZig incurs high computational complexity for waveform comparison. In this paper, we propose CmZig to embrace channel estimation in multiple-packet reception (MPR) of ZigBee, which effectively improves MPR via lightweight computing used for channel estimation and collision decomposition. First, CmZig enables accurate collision decomposition with low computation complexity, which uses the estimated channel parameters modeling both signal amplitude and phase. Second, CmZig adopts reference waveform comparison only for collisions without chip-level time offsets, instead of the complex machine learning based method. We implement CmZig on USRP-N210 and establish a six-node testbed.

CAC for trees is the statement asserting that any infinite subtree of $\mathbb{N}^{, 28 pages

In VANETs, it is important to support fast and reliable multi-hop broadcast for safety-related applications. The performance of multi-hop broadcast schemes is greatly affected by relay selection strategies. However, the relationship between the relay selection strategies and the expected broadcast performance has not been fully characterized yet. Furthermore, conventional broadcast schemes usually attempt to minimize the waiting time difference between adjacent relay candidates to reduce the waiting time overhead, which makes the relay selection process vulnerable to internal interference, occurring due to retransmissions from previous forwarders and transmissions from redundant relays. In this paper, we jointly take both of the relay selection and the internal interference mitigation into account and propose a fast, reliable, opportunistic multi-hop broadcast scheme, in which we utilize a novel metric called the expected broadcast speed in relay selection and propose a delayed retransmission mechanism to mitigate the adverse effect of retransmissions from previous forwarders and an expected redundancy probability based mechanism to mitigate the adverse effect of redundant relays. The performance evaluation results show that the proposed scheme yields the best broadcast performance among the four schemes in terms of the broadcast coverage ratio and the end-to-end delivery latency.

In this paper, we compute the expected number of vehicles with at least one two-hop path to a fixed roadside unit (RSU) in a multi-hop, one-dimensional vehicular ad hoc network (VANET) where other cars can act as relays. The pairwise channels experience Rayleigh fading in the random connection model, and so exist, with a probability given by a function of the mutual distance between the cars, or between the cars and the RSU. We derive exact expressions for the expected number of cars with a two-hop connection to the RSU when the car density $\rho$ tends to zero and infinity, and determine its behaviour using an infinite oscillating power series in $\rho$, which is accurate for all regimes of traffic density. We also corroborate those findings with a realistic scenario, using snapshots of actual traffic data. Finally, a normal approximation is discussed for the probability mass function of the number of cars with a two-hop connection to the RSU., Comment: 5 pages, 5 figures

Free space optics (FSO) has been demonstrated as a secure and high-speed solution for long distance and line-of-sight wireless communications. Applying FSO as fronthaul/backhaul communications between base stations (BSs) and the gateway can significantly increase the fronthaul/backhaul link capacity. Traditionally, the gateway has to be equipped with multiple FSO transceivers, each of which is used to communicate with a BS by establishing a dedicated FSO. In this paper, we propose to use a steerable FSO system, where the gateway is equipped with a steerable FSO transceiver to communicate with multiple FSO transceivers at different BSs in a time division multiplexing manner. Applying the steerable FSO system can reduce the number of FSO transceivers at the gateway, and thus reduce the capital cost of implementing an FSO based fronthaul/backhaul network. We formulate the transmission scheduling problem in the steerable FSO system to optimize the active time for each FSO link associated with the steerable FSO transceiver such that the overall delay of transmitting a packet from geo-distributed BSs to the steerable FSO transceiver at the gateway is minimized, while the latency requirements of the BSs are met. We propose the laTency aWare transmIssion Scheduling for sTeerable FSO (TWIST) algorithm to efficiently solve the proposed problem.

Consider n nodes communicating over an unreliable broadcast channel. Each node has a single packet that needs to be communicated to all other nodes. Time is slotted, and a time slot is long enough for each node to broadcast one packet. Each broadcast reaches a random subset of nodes. The objective is to minimise the time until all nodes have received all packets. We study two schemes, (i) random relaying, and (ii) random linear network coding, and analyse their performance in an asymptotic regime in which n tends to infinity. Simulation results for a wide range of n are also presented., Submitted to IEEE Transactions on Information Theory

With the growing demand for network connectivity and diversity of network applications, one primary challenge that network service providers are facing is managing the commitments for Service Level Agreements~(SLAs). Service providers typically monitor SLAs for management tasks such as improving their service quality, customer billing and future network planning. Network service customers, on their side, monitor SLAs to optimize network usage and apply, when required, penalties related to service failures. In future 6G networks, critical network applications such as remote surgery and connected vehicles will require these SLAs to be more dynamic, flexible, and automated to match their diverse requirements on network services. Moreover, these SLAs should be transparent to all stakeholders to address the trustworthiness on network services and service providers required by critical applications. Currently, there is no standardised method to immutably record and audit SLAs, leading to challenges in aspects such as SLA enforcement and accountability -- traits essential for future network applications. This work explores new requirements for future service contracts, that is, on the evolution of SLAs. Based on those new requirements, we propose an end to end layered SLA architecture leveraging Distributed Ledger Technology (DLT) and smart contracts. Our architecture is inheritable by an existing telco-application layered architectural frameworks to support future SLAs. We also discuss some limitations of DLT and smart contracts and provide several directions of future studies.

Welcome to a further installment of "New Products" in IEEE Microwave Magazine. In this issue, we present seven new items that may be of interest to the RF/microwave and wireless communities.

Cooperating radios can extend their communication range by adjusting their signals to ensure coherent combining at a destination radio. This technique is called distributed transmit beamforming. Beamforming (BF) relies on the BF radios having frequency synchronized carriers and phases adjusted for coherent combining. Both requirements are typically met by exchanging preambles with the destination. However, since BF aims to increase the communication range, the individually transmitted preambles are typically at low SNR and their lengths are constrained by the channel coherence time. These noisy preambles lead to errors in frequency and phase estimation, which result in randomly changing BF gains. To build reliable distributed BF systems, the impact of estimation errors on the BF gains need to be considered in the design. In this work, assuming a destination-led BF protocol and Kalman filter for frequency tracking, we optimize the number of BF radios and the preamble lengths to achieve reliable BF gain. To do that, we characterize the relations between the BF gains distribution, the channel coherence time, and design parameters like the SNR, preamble lengths, and the number of radios. The proposed relations are verified using simulations and via experiments using software-defined radios in a lab and on UAVs.

Jamming attacks on wireless networked control systems are investigated for the scenarios where the system dynamics face exogenous disturbance. In particular, the control input packets are assumed to be transmitted from a controller to a remotely located linear plant over an insecure wireless communication channel that is subject to jamming attacks. The time-varying likelihood of transmission failures on this channel depends on the power of the jamming interference signal emitted by an attacker. We show that jamming attacks can prevent stability when the system faces disturbance, even if the attacked system without disturbance is stable. We also show that stability under jamming and disturbance can be achieved if the average jamming interference power is restricted in a certain way that we characterize in the paper. We illustrate our results on an example networked control system with a fading wireless channel, where the outage probability is affected by jamming attacks., Comment: Improve wording; Correct typos

Index modulation (IM) reduces the power consumption and hardware cost of the multiple-input multiple-output (MIMO) system by activating part of the antennas for data transmission. However, IM significantly increases the complexity of the receiver and needs accurate channel estimation to guarantee its performance. To tackle these challenges, in this paper, we design a deep learning (DL) based detector for the IM aided MIMO (IM-MIMO) systems. We first formulate the detection process as a sparse reconstruction problem by utilizing the inherent attributes of IM. Then, based on greedy strategy, we design a DL based detector, called IMRecoNet, to realize this sparse reconstruction process. Different from the general neural networks, we introduce complex value operations to adapt the complex signals in communication systems. To the best of our knowledge, this is the first attempt that introduce complex valued neural network to the design of detector for the IM-MIMO systems. Finally, to verify the adaptability and robustness of the proposed detector, simulations are carried out with consideration of inaccurate channel state information (CSI) and correlated MIMO channels. The simulation results demonstrate that the proposed detector outperforms existing algorithms in terms of antenna recognition accuracy and bit error rate under various scenarios.

The proposed approach is designed to boost the IEEE 802.15.4 / ZigBee-based WSN streaming efficiency by introducing multipurpose routing. We investigate how those networks can be designed in order to achieve optimum throughput using computational models to explain intra-track and inter-track interference in multipath routing networks. One mode of action in particular – Spatial-TDMA (S-TDMA), Zig Bee dependent WSNs, will greatly reduce the amount of interference, both in one- and multi-track environments. It is also seen that two-way networks can be stronger than their one-way counterparts by means of deliberately selected implementation parameters. Finally, a greater degree of spatial isolation between the routes used indicates improved average efficiency in multi-path scenarios. The simulation is one of our results.

The role of this work gives out the execution outline of a stable Wireless Sensor Network (WSN) using IEEE802.15.4 (ZigBee) for gradient surveillance. The main aim of this analysis is to construct a WSN system that can sense and monitor the distortion of the ground caused by calamities in massive regions with sensor and radio equipment. Both environmental and electrical issues must be resolved in order for statistics to be accessed regularly. This analysis describes approaches enabling transient social interaction mode switching depending based rechargeable density a framework for preserving router terminals mostly from illumination, as well as an upgraded antenna definition instead for WSN. The specification of an evolving wireless network is illustrated in the test response using each absolute evaluation specialty. The acquired information from the developed system can be used to predict the field's rank.

According to the latest news, the 3rd Generation cooperation Project has been taken the inventiveness of creating an interworking architecture involving cellular and WLAN as an additional feature to the cellular network requirements of 3GPP. This article provides an overview of an interworking infrastructure that allows mobile operators to provide the public WLAN dependent entrance service to various 3GPP network subscribers. The enabling features include 3GPP membership reuse, network availability, authentications relying on 3GPP systems, security keys agreement, USIM /SIM card authorization, user data service access and routing, as well as end-user paying. The function of interworking is accomplished without setting any particular 3GPP specifications for the new WLAN entrance networks, but instead by depend on existing features available in the traditional WLAN entrance networks centered on the IEEE 802.11 principles. In this paper, authors have focused on two key aspects of MTC devices, as currently discussed in 3GPP-Release 10. These are named as “the control of subscriptions” and the “congestion/overload control of the network”. A new solution is proposed for the latter one based on the handling of the bulk signals.

With the exponential increase of the number of devices in the communication ecosystem toward the upcoming sixth generation (6G) of wireless networks, more enabling technologies and potential wireless architectures are necessary to fulfill the networking requirements of high throughput, massive connectivity, ultra reliability, and heterogeneous quality of service (QoS). In this work, we consider an uplink network consisting of a primary user (PU) and a secondary user (SU) and, by integrating the concept of cognitive radio and multiple access, two protocols based on rate-splitting multiple access and non-orthogonal multiple access with successive interference cancellation are investigated in terms of ergodic rate. The considered protocols aim to serve the SU in a resource block which is originally allocated solely for the PU without negatively affecting the QoS of the PU. We extract the ergodic rate of the SU considering a specific QoS for the PU for the two protocols. In the numerical results, we validate the theoretical analysis and illustrate the superiority of the considered protocols over two benchmark schemes., Comment: 5 pages, 3 figures

The necessitate for a worldwide monitoring method for Internet worm detection is obvious. Similarly local reply and exposure inspection also understandable. Generally large set of data is used to supervise worm activity, but found tricky to relate at local network. We observe “victim number based approaches” are not stable for related networks. So what work is suitable for local network? To solve this issue, we recommend Destination Source Correlation algorithm which monitors local networks and looks into the infection rate & tracks real infected hosts to offer a precise reply. Although “HoneyStat” strategy is already been used to trace temporary infection cycle of worm.

Millimeter-wave self-backhauled small cells are a key component of next-generation wireless networks. Their dense deployment will increase data rates, reduce latency, and enable efficient data transport between the access and backhaul networks, providing greater flexibility not previously possible with optical fiber. Despite their high potential, operating dense self-backhauled networks optimally is an open challenge, particularly for radio resource management (RRM). This paper presents, RadiOrchestra, a holistic RRM framework that models and optimizes beamforming, rate selection as well as user association and admission control for self-backhauled networks. The framework is designed to account for practical challenges such as hardware limitations of base stations (e.g., computational capacity, discrete rates), the need for adaptability of backhaul links, and the presence of interference. Our framework is formulated as a nonconvex mixed-integer nonlinear program, which is challenging to solve. To approach this problem, we propose three algorithms that provide a trade-off between complexity and optimality. Furthermore, we derive upper and lower bounds to characterize the performance limits of the system. We evaluate the developed strategies in various scenarios, showing the feasibility of deploying practical self-backhauling in future networks., Comment: 19 pages

Mobile Ad-hoc Network (MANET) is a multitude of self-organizing, self-configuring and infrastructure-less network of mobile devices. In MANET, the node will be act as a router. Routing is a main challenge to perpetuate connectivity and verify the successive rate of Quality of Service (QoS). In order to provide the accurate data delivery with improved QoS the modified Lumer and Faieta algorithm with modified Ad hoc On-Demand Distance Vector Routing (AODV), Dynamic Source Routing (DSR) reactive protocols are used in the proposed work. The routing process is controlled depending on traffic protocols to minimize the network latency. In addition, QoS provision based on delay requirement to ensure guaranteed performance level to the delay sensitive applications. Three performance parameters such as End-to-end Average Delay, Packet Delivery Ratio (PDR) and Control Overhead are contemplated in different mobility scenarios to compare the performance of the proposed protocol by using NS2 simulator with the original AODV, DSR and the MAC layer information can be used to construct the neighbor table which will enhance the performance in terms of delay and PDR as well as minimizing the control overhead.

A key component for preserving a WSN’s integrity is designing an intrusion detection system (IDS). This article covers several sorts of security threats that may occur in a WSN. It proposes a detection of malicious nodes in a WSN. This system identifies four common assaults (i.e., black hole, wormhole, gray hole, and DDoS attacks) and is based on a Base Station machine learning (ML) algorithm (BS). The suggested ML algorithm continually analyzes data patterns from each node. Based on this technique, BS recognizes the network’s harmful behavior and provides notifications to neighbor nodes to prevent attacker. First, the various assaults are examined and their characteristics are derived in terms of network parameters. Furthermore, the gathered pattern trains an ML algorithm. Then, the attacker node is effectively and properly classified within the BS. The NS2 simulator simulated the needed secure WSN. The experimental findings revealed excellent accuracy of the suggested method for attack detection. This precision can enhance network performance in terms of energy usage and packet delivery (PDR).

Traffic congestion is a major problem in developing and developed countries vehicle traffic management systems. Traffic control system works based on the idea of removing instabilities and avoid accidents in order to minimize the traffic and maximize the vehicle flow. To control the congestion need to predict the upcoming traffic flow and it will be useful for Advanced Traffic Information Systems (ATIS), Advanced Traffic Management Systems (ATMS) and traffic analytics. Non–linear historical data and uncertain factors influence the vehicle congestion at peak hours which cannot be considered in existing algorithms. This study proposes hybrid neural network algorithms such as Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) network for short term traffic flow prediction based on multivariate analysis. Widely referred datasets Performance Measurement Systems (PEMS) and Mesowest have been used to evaluate this model. Experiment results shows that CNN-LSTM Hybrid prediction model achieves high accuracy compared with other models.

In this paper, we investigate the energy-efficient multi-access mobile edge computing with secrecy provisioning. Specifically, we first investigate the scenario of one wireless device's (WD's) multi-access offloading subject to a malicious node's eavesdropping. By characterizing the WD's secrecy based throughput in its offloading transmission, we formulate a joint optimization of the WD's multi-access computation offloading, secrecy provisioning, and offloading-transmission duration, with the objective of minimizing the WD's total energy consumption, while providing a guaranteed secrecy-outage during offloading and a guaranteed overall-latency in completing the WD's workload. Despite the non-convexity of this joint optimization problem, we exploit its layered structure and propose an efficient algorithm for solving it. Based on the study on the single-WD scenario, we further investigate the scenario of multiple WDs, in which a group of WDs sequentially execute the multi-access computation offloading, while subject to a malicious node's eavesdropping. Taking the coupling effect among different WDs into account, we propose a swapping-heuristic based algorithm (that uses our proposed single-WD algorithm as a subroutine) for finding the ordering of the WDs to execute the multi-access computation offloading, with the objective of minimizing all WDs' total energy consumption. Extensive numerical results are provided to validate the effectiveness and efficiency of our proposed algorithms.

The advancement in the communication and services demand for better QoS, but in parallel the increase in network traffic demands for an effective and significant traffic controlling model to manage high network traffic and also reduce congestion. In case of MANET circumstances it is further difficult to control and manage due to high mobilizing nodes and limited resource restrictions. Even MANET’s dynamic mobility creates high maintenance overhead for effective communication. In the past most of the designed routing protocols utilize reactive routing mechanism, which are primary source driven. In case of a link failure and data failure it has to update the source node and source node only have to decide next course of action. This will generates an additional overhead in the network and may reduce throughput of the protocols. This paper aims to propose a novel Traffic Controlling Model (TCM) to efficiently manage the routing overhead in MANET. The TCM will handle heavy traffic, which is the main cause of network congestion and overhead. It first determines the network traffic and evaluates the probable Node Link Life (NLL) to recommend the TCM process. The analysis of the results generated through the experiment evaluation shows that the data routing has improved and substantiates the effectiveness of the proposal in compared to the existing routing approaches.

Massive MIMO opens up attractive possibilities for next generation wireless systems with its large number of antennas offering spatial diversity and multiplexing gain. However, the fronthaul link that connects a massive MIMO Remote Radio Head (RRH) and carries IQ samples to the Baseband Unit (BBU) of the base station can throttle the network capacity/speed if appropriate data compression techniques are not applied. In this paper, we propose an iterative technique for fronthaul load reduction in the uplink for massive MIMO systems that utilizes the convolution structure of the received signals. We use an alternating minimisation algorithm for blind deconvolution of the received data matrix that provides compression ratios of 30-50. In addition, the technique presented here can be used for blind decoding of OFDM signals in massive MIMO systems., Comment: 7 pages, 3 figures

In Mobile Ad Hoc Networks (MANET), during routing, there may be possibility of route recovery delay and overhead. Also there may be issues due to reduced lifetime of link and node. In order to overcome these issues, in this paper, an optimization technique for fault recovery and fast data transmission in MANET is proposed. In order to avoid the faults due to frequent disconnections and node failures, the path with least mobility and high residual energy is selected for transmission. During data transmission, if majority of the neighbours are changed or if the residual energy is low, then the source will choose any shorter alternate route by applying the optimized recovery mechanism. By simulation results, we show that the proposed technique enhances packet delivery ratio and throughput and minimizes end-to-end delay, energy consumption and control overhead.

Mobile Ad-hoc networks (MANET) is a collection of nodes of wireless connectivity. In Mobile Ad hoc Network (MANET) all the mobile nodes are requiring restricted battery capacity. Because of the changing nature of network the sudden communication link breakage happens. Hence the possibility of data loss is more. Efficient utilization of energy and lossless transmission are the important issues in MANET. This paper proposes a new Trust based Efficient Energy Balanced Less Loss Routing (TER) Protocol for MANETS. This protocol improves the network performance by properly choosing the intermediate forwarding nodes. The Source Node picks only single of its neighbors as its next hop node by using Efficient Parameter (EP). The EP is calculated from the residual energy, distance, Occupied Queue space, the velocity of that node. The node using maximum EP is nominated as the succeeding node. This protocol reduces the number of channeling messages and hence reduces the path-finding Overhead of the network. It lessens the chance of data loss and hence improves throughput and Packet Delivery Ratio. This protocol adds trust to the selected node. In this paper, we do the simulation in ns-2 simulator and the performance is measured by with performance parameters like Routing Overhead, Packet Delivery Ratio, Throughput, End to End Delay and Average energy consumption.

This article focuses on the development of integrated sensing and communications (ISAC) from a multiple access (MA) perspective, where the idea of non-orthogonal multiple access (NOMA) is exploited for harmoniously accommodating the sensing and communication functionalities. We first reveal that the developing trend of ISAC is from \emph{orthogonality} to \emph{non-orthogonality}, and introduce the fundamental models of the downlink and uplink ISAC while identifying the design challenges from the MA perspective. (1) For the downlink ISAC, we propose two novel designs, namely \emph{NOMA-empowered} downlink ISAC and \emph{NOMA-inspired} downlink ISAC to effectively coordinate the inter-user interference and the sensing-to-communication interference, respectively. (2) For the uplink ISAC, we first propose a \emph{pure-NOMA-based} uplink ISAC design, where a fixed communication-to-sensing successive interference cancellation order is employed for distinguishing the mixed sensing-communication signal received over the fully shared radio resources. Then, we propose a general \emph{semi-NOMA-based} uplink ISAC design, which includes the conventional orthogonal multiple access-based and pure-NOMA-based uplink ISAC as special cases, thus being capable of providing flexible resource allocation strategies between sensing and communication. Along each proposed NOMA-ISAC design, numerical results are provided for showing the superiority over conventional ISAC designs., 7 pages, 5 figures

Switches in cloud data centers support multiple service queues per port to provide differentiated network performance among different traffic classes. To isolate service queues, recent solutions leverage the power of Explicit Congestion Notification (ECN). However, this causes a fundamental dependency on ECN-based transport protocols, making it hard to use generic transport protocols. To this end, we design DynaQ, a protocol-independent multi-queue management solution that enables service queue isolation with generic transport protocols. The key idea of DynaQ is to adjust the packet dropping threshold of service queues dynamically. Specifically, DynaQ allows a service queue to occupy free buffer space but prevents the queue from hurting other active queues. Our solution requires only a few additional clock cycles to implement on hardware. To evaluate DynaQ comprehensively, we conduct a series of testbed experiments and large-scale simulations. Our evaluation results show that, compared to alternative schemes, DynaQ is the only solution that achieves work-conserving weighted fair sharing and low latency without protocol dependency.

Distributed Denial of service (DDoS) attacks is an enormous threat to today’s cyber world, cyber networks are compromised by the attackers to distribute attacks in a large volume by denying the service to legitimate users. The toughest and challenging task in today’s network and network security engineers is to identify compromised traffic (attacked) and legitimate (normal) traffic. The main goal of the paper is to detect DDos attacks using classification algorithms. To achieve the goal the proposed system uses attacking tool to initiate attacks using Loic attacking tool with the data set extracted from open source tool Wireshark and transferring the dataset to apache Spark for detection analysis. The system also uses Apache spark machine learning algorithms (MLib), classification algorithms to classify the dataset. We use Naive Bayes, KNN and Random forest classification algorithms to classify normal traffic and attacked traffic. Our system is capable of detecting attacks with respect to any traffic protocols ICMP, TCP, or UDP. The accuracy of detection is compared on three classification algorithms and noted that random forest gives the accuracy of 96.75%.

This paper presents the implementation and experimental evaluation of a short-packet physical-layer network coding (PNC) system. Implementation of short-packet PNC systems is challenging. First, short packets may have only a few pilot symbols for synchronization and channel estimation purposes. Increasing the number of pilots increases the overhead; decreasing the number of pilots, on the other hand, degrades the packet error rate performance. Second, many short-packet systems are meant for applications with very stringent delay requirements. Employing advanced but complex PNC channel decoding may result in unacceptable delay due to the processing delay. This work presents a low-complexity and low-overhead physical-layer design of OFDM-based short-packet PNC systems, implemented over the software-defined radio platform. Our design makes use of only a small number of pilots (without separate OFDM preamble symbols) to address issues such as slot synchronization, packet detection, carrier frequency offsets, and mismatched channel state information. Our design employs reduced-complexity XOR channel decoding based code-aided parameter estimation (that includes synchronization and channel estimation) to compensate for the limitations imposed by having a small number of pilots. This is the first demonstration that provides a practical framework for applying PNC to short-packet communications.

The potential of adaptive antennas to optimize the wireless network performance make it one of the promising technologies that can face the increased demand for wireless communications services with the limited available bandwidth. Adaptive antennas have the ability to steer their main lobe in the direction of interest and placing nulls in the direction of interference. This can result in co-channel interference minimization, maximizing Signal to Interference Ratio (SIR) and then improve the receiver sensitivity. In this paper, the base-station sensitivity improvement and its effect on the mobile transmit power were investigated at different scenarios. Results show that using adaptive antenna yields in RF pollution reduction.

The domain name system (DNS) that maps alphabetic names to numeric Internet Protocol (IP) addresses plays a foundational role for Internet communications. By default, DNS queries and responses are exchanged in unencrypted plaintext, and hence, can be read and/or hijacked by third parties. To protect user privacy, the networking community has proposed standard encryption technologies such as DNS over TLS (DoT), DNS over HTTPS (DoH), and DNS over QUIC (DoQ) for DNS communications, enabling clients to perform secure and private domain name lookups. We survey the DNS encryption literature published since 2016, focusing on its current landscape and how it is misused by malware, and highlighting the existing techniques developed to make inferences from encrypted DNS traffic. First, we provide an overview of various standards developed in the space of DNS encryption and their adoption status, performance, benefits, and security issues. Second, we highlight ways that various malware families can exploit DNS encryption to their advantage for botnet communications and/or data exfiltration. Third, we discuss existing inference methods for profiling normal patterns and/or detecting malicious encrypted DNS traffic. Several directions are presented to motivate future research in enhancing the performance and security of DNS encryption., to be Published in ACM Computing Surveys (2022)

In a time-varying massive multiple-input multipleoutput (MIMO) system, the acquisition of the downlink channel state information at the base station (BS) is a very challenging task due to the prohibitively high overheads associated with downlink training and uplink feedback. In this paper, we consider the hybrid precoding structure at BS and examine the antennatime domain channel extrapolation. We design a latent ordinary differential equation (ODE)-based network under the variational auto-encoder (VAE) framework to learn the mapping function from the partial uplink channels to the full downlink ones at the BS side. Specifically, the gated recurrent unit is adopted for the encoder and the fully-connected neural network is used for the decoder. The end-to-end learning is utilized to optimize the network parameters. Simulation results show that the designed network can efficiently infer the full downlink channels from the partial uplink ones, which can significantly reduce the channel training overhead., Comment: 5 pages, 5 figures

A number of companies and standards development organizations have, since 2000, been producing products and standards for "time-sensitive networks" to support real-time applications that require a) zero packet loss due to buffer congestion, b) extremely low packet loss due to equipment failure, and c) guaranteed upper bounds on end-to-end latency. Often, a robust capability for time synchronization to less than 1 μs is also required. These networks consist of specially-featured bridges that are interconnected using standard Ethernet links with standard MAC/PHY layers. Since 2012, this technology has advanced to the use of routers, as well as bridges, and features of interest to time-sensitive networks have been added to both Ethernet and wireless standards.

We propose a novel interference alignment (IA) technique with receive antenna partitioning (RAP) for simultaneous wireless information and power transfer (SWIPT)-enabled downlink fog radio access networks (F-RANs). The basic idea of the proposed scheme is to apply a generalized downlink IA for each access point (AP) and to divide receive antennas at each user into two groups for information decoding (ID) and energy harvesting (EH), respectively. With the proposed scheme, an optimal receive antenna configuration at each user is obtained to maximize the weighted sum of achievable rate and the sum of harvested energy of the network. Also we develop an antenna configuration selection algorithm to obtain near-optimal performance with low computational complexity. Through extensive computer simulations, it is shown that the proposed scheme significantly improves a rate-energy region compared with existing techniques.

Intelligent reflecting surface (IRS) has received widespread attention because it can significantly improve the performance of wireless networks. The X-duplex is a more flexible duplex mode, which can decrease a small sum rate in exchange for a higher quality-of-service performance. In this article, an IRS transmission scheme based on X-duplex is investigated to enhance the flexibility and freedom of communication design. We present the X-duplex IRS with the simultaneous wireless information and power transfer, and establish a power consumption model based on real application scenarios. An alternating optimization algorithm is proposed to maximize the energy efficiency (EE) of a multi-input single-output (MIMO) network assisted by the X-duplex IRS. As for the X-duplex relay, we explore an algorithm based on the golden section to optimize the EE. Simulation results comprehensively evaluate the performance of the two auxiliary transmission methods. The X-duplex IRS has higher EE and weighted sum rate (WSR) than the X-duplex relay when sufficient transmission power is available. However, the IRS cannot entirely replace the traditional relay. The X-duplex relay with self-interference energy harvesting achieves a higher WSR and EE when the access point energy is limited or the transmission distance is short.

The channel state information (CSI) is essential for the base station (BS) to schedule user equipments (UEs) and efficiently manage the radio resources. Hence, the BS requests UEs to regularly feed back the CSI. However, frequent CSI reporting causes large signaling overhead. To reduce the feedback overhead, we propose two machine learning-based approaches to adjust the CSI feedback interval. We use a deep neural network and reinforcement learning (RL) to decide whether an UE feeds back the CSI. Simulation results show that the RL-based approach achieves the lowest mean squared error while reducing the number of CSI feedback transmissions.

This article deals with the problem of decentralized resilient observer-based output-feedback control design for networked control systems (NCSs). The proposed scheme considers both network imperfections and security issues. It is assumed that the NCS is suffering from time-varying network-induced delays and time-varying transmission intervals. Moreover, data transmission is performed over a nonsecure network that suffers from a denial-of-service (DoS) attack. The DoS jamming attack has affected the network by the occurrence of consecutive packet dropouts, which result in attack-induced packet dropouts. Based on the fact that packet dropouts caused by DoS attacks naturally do not follow a specific statistical pattern, the attack-induced packet dropouts are modeled as an extension of time-varying intervals with no probability distribution. Sufficient conditions are provided to guarantee the uniformly globally exponential stability of the NCS in the form of linear matrix inequalities. Finally, the effectiveness and applicability of the proposed method are demonstrated by simulation results.

This article presents the design and implementation of PCube, a phase-based parallel packet decoder for concurrent transmissions of LoRa nodes. The key enabling technology behind PCube is a novel air-channel phase measurement technique that is able to extract phase differences of air-channels between LoRa nodes and multiple antennas of a gateway. PCube leverages the reception diversities of multiple receiving antennas of a gateway and scales the concurrent transmissions of a large number of LoRa nodes, even exceeding the number of receiving antennas at a gateway. As a phase-based parallel decoder, PCube provides a new dimension to resolve collisions and supports more concurrent transmissions by complementing time and frequency-based parallel decoders. PCube is implemented and evaluated with synchronized software defined radios and off-the-shelf LoRa nodes in both indoors and outdoors. Results demonstrate that PCube can substantially outperform state-of-the-art works in terms of aggregated throughput by 4.9× and the number of concurrent nodes by up to 5×. More importantly, PCube scales well with the number of receiving antennas of a gateway, which is promising to break the barrier of concurrent transmissions.

In this paper, we propose a wideband Full Duplex (FD) Multiple-Input Multiple-Output (MIMO) communication system comprising of an FD MIMO node simultaneously communicating with two multi-antenna UpLink (UL) and DownLink (DL) nodes utilizing the same time and frequency resources. To suppress the strong Self-Interference (SI) signal due to simultaneous transmission and reception in FD MIMO systems, we propose a joint design of Analog and Digital (A/D) cancellation as well as transmit and receive beamforming capitalizing on baseband Orthogonal Frequency-Division Multiplexing (OFDM) signal modeling. Considering practical transmitter impairments, we present a multi-tap wideband analog canceller architecture whose number of taps does not scale with the number of transceiver antennas and multipath SI components. We also propose a novel adaptive digital cancellation based on truncated singular value decomposition that reduces the residual SI signal estimation parameters. To maximize the FD sum rate, a joint optimization framework is presented for A/D cancellation and digital beamforming. Finally, our extensive waveform simulation results demonstrate that the proposed wideband FD MIMO design exhibits higher SI cancellation capability with reduced complexity compared to existing cancellation techniques, resulting in improved achievable rate performance., 32 pages, 10 figures, Under Review for Publication in the IEEE Transactions on Wireless Communications

Internet of Vehicles (IoV) is considered to be a backbone of smart transportation system where vehicles are expected to exchange traffic information and other data using vehicle-to-vehicle (V2V) communications. Furthermore, V2V communications is regarded as a medium to send upcoming traffic information to vehicles/drivers or passengers using wireless technology in a timely manner. This will help reduce traffic accidents, traffic jams, fuel consumption caused by traffic jams, loss of hours caused by delayed commuting and carbon emission caused by vehicles. Because of the critical nature of IoV for smart transportation systems, secure wireless communication is one of the critical and essential components to offer trustworthy services through IoV. Like in other wireless systems, wireless communication is open in air, which makes attackers' job easy to launch the malicious actions in IoV. In this paper, we investigate the impact of mobility of vehicles for secure communications in IoV with joint jamming and eavesdropping attacks. We investigate different scenarios, when vehicles (legitimate ones and attackers) travel in same and opposite directions with low speed (school zone speed) limit to highway speed limit. Furthermore, we study the impact of association time and encryption time not only for establishing the connection between vehicles for V2V communications but also for exchanging messages for vehicles after successful association between vehicles and encryption of the message. In addition, we also study the joint impact of jamming and eavesdropping attacks in IoV for different speed limits, transmission ranges and wireless bandwidths. We investigate the extra cost in terms of transmit power and bandwidth incurred by jamming and eavesdropping attacks while maintaining the same secrecy rate as it could have been without those attacks. Numerical results are used to support the analysis.

Link-flooding attacks (LFAs) are a new type of distributed denial-of-service (DDoS) attacks that can substantially damage network connectivity. LFAs flows are seemingly legitimate at the origin. But their cumulative volume at critical links causes congestion. We propose RL-Shield, a reinforcement learning based defense system against LFAs. It mitigates LFAs and, at the same time, effectively forwards data traffic in the network. RL-Shield introduces a new detection algorithm for monitoring IP behaviors using the Dirichlet distribution and Bayesian statistics. It monitors the interplay of LFAs and traffic engineering and identifies source IPs that persistently react to rerouting events. The detection algorithm controls two reinforcement learning based routing algorithms that use a hop-by-hop technique to connect related node pairs. We evaluate RL-Shield on various network topologies by simulating several attack strategies. The simulation results demonstrate the effectiveness and high-accuracy of RL-Shield.

Wireless networks are considered the best utilized network and in particular Mobile Ad-hoc NETworks (MANETs) have found many applications for its data transmission in real time applications. The accompanying challenges restrict the current protocols for the routing being specifically used in MANETs. The design issues in this network are to restrict the usage of energy while transmitting information and provide security to the nodes. In the existing routing protocols, route comes from a source where the source node seeks a way to the target node, by transmitting messages to its adjacent nodes, and the nodes use energy to do this. Mobile Ad-hoc network faces challenges in improving the energy efficiency and providing security for the routing protocol. This research work proposes the Enhanced Energy Efficient-Secure Routing (EEE-SR) protocol as a novel security algorithm to access secure data in hostile environment. In the proposed work, to secure data transmission in the network, the nodes associates with security policy. Under this policy, both the nodes have a common enforcing policy, and then they communicate with each other. The selection of the nodes for the transmission has to prove its authentication and then selection of the routing path built on the available energy threshold at the nodes in the set-up for forwarding packets in the network. The routing protocol implements the best shortest path in network and also checks for the nodes trustworthiness by evaluating the trust policies enforcement on it. The protocol enables a node to autonomously decide whether to select the neighboring node or based on the available energy threshold and security policy enforced. The algorithm evaluates increase network lifetime and low in the energy consumption, packet loss and end-to-end delay.

Today, the rapid growth of vehicles connected to the Internet enables provides various services to consumers, including traffic management, traffic safety, and entertainment. Vehicular Ad-Hoc Network (VANET) is one of the most prominent and emerging technologies on the Internet of Vehicular Things (IoVT). This technology offers to fulfill requirements such as robust information exchange, and infotainment among vehicles for the smart city environment. Still, it has some challenges such as centralization, storage, security, and privacy because all city vehicular networks send vehicles and road-related information data directly to the cloud. This article proposes BIIoVT: Blockchain-based Secure Storage Architecture for Intelligent Internet of Vehicular Things (IIVoT) to mitigate the above-mention issues. Blockchain provides security and privacy at each city's vehicular networks and decentralized storage at the cloud layer with a Distributed Hash Table (DHT). It also examines how the vehicular network offers a secure platform. The validation results of the proposed architecture show an outstanding balance of secure storage and efficiency for the IoVT compared to existing methods.

Gateways in the Internet of Things (IoT) play a decisive role in routing the preprocessed filtered data to cloud platforms. While investigating gateways, the need for a comprehensive systematic literature review that can elaborate the working and functionalities of IoT gateways was felt. This paper presents a systematic literature review of IoT gateways in general and smart gateways in particular. It considered papers published over the last 10 years, i.e., from 2011 till July 2021. A methodical literature analysis technique is used in this review; out of 2347 papers, 67 articles are selected for complete analysis based on well-defined criteria. The survey starts with the broad categorization of gateways in IoT as basic and smart gateways. Further, smart gateways are sub-divided into three categories as passive gateways, semi-automated and fully-automated gateways. The survey is performed based on well-defined criteria, which include: the type of gateways, their requirements, tools/platforms, the approach adopted, evaluation and their application domain. This paper demonstrates further bifurcation of functional requirements of IoT gateways. Research gaps and open issues have been identified in the area. Future prospects have accordingly being suggested to help academicians embark on advanced research.

The existing relay-assisted terahertz (THz) wireless system is limited to dual-hop transmission with pointing errors and short-term fading without considering the shadowing effect. This paper analyzes the performance of a multihop-assisted backhaul communication mixed with an access link under the shadowed fading with antenna misalignment errors. We derive statistical results of the signal-to-noise ratio (SNR) of the multihop link by considering independent but not identically distributed (i.ni.d) $\alpha$-$\mu$ fading channel with pointing errors employing channel-assisted (CA) and fixed-gain (FG) amplify-and-forward (AF) relaying for each hop. We analyze the outage probability, average BER, and ergodic capacity performance of the mixed system considering the generalized-$K$ shadowed fading model with AF and decode-and-forward (DF) protocols employed for the access link. We derive exact expressions of the performance metrics for the CA-multihop system with the DF relaying for the last hop and upper bound of the performance for the FG-multihop system using FG and DF relaying at the last relay. We also develop asymptotic analysis in the high SNR to derive the diversity order of the system and use computer simulations to provide design and deployment aspects of multiple relays in the backhaul link to extend the communication range for THz wireless transmissions., Comment: This work has been submitted to the IEEE for possible publication

The non-intrusive human activity recognition has been envisioned as a key enabler for many emerging applications requiring interactions between humans and computing systems. To accurately recognize different human behaviors, ubiquitous wireless signals are widely adopted, e.g., Wi-Fi signals, whose Channel State Information can precisely reflect human movements. Unfortunately, nearly all Wi-Fi-based recognition systems assume a clean wireless environment, i.e., no interference will compromise the developed algorithms, which, apparently, is not feasible in practice. Even worse, for systems using Wi-Fi 2.4GHz signals, the widely existing interference from coexisting protocols, such as ZigBee, Bluetooth, and LTE-Unlicensed, can easily compromise the recognition process, posing a hard limit on further enhancing the accuracy. Therefore, this work uncovers a new wireless adversarial attack against Wi-Fi-based human activity recognition systems, by intentionally injecting interference using coexisting protocol signals. The contaminated Wi-Fi signal will distort CSI estimation and finally output a false recognition result. Different from traditional jamming attacks, this new adversarial attack is intelligent and stealthy in terms of avoiding being detected from traffic analysis. Along with both theoretical analysis and extensive real-world experiments, we have shown this newly-identified attack can easily compromise many existing Wi-Fi-based human recognition systems while still bypassing malicious signal detection schemes.

Cell-free massive MIMO systems have promising data rate and uniform coverage gains. These systems, however, typically rely on optical fiber based fronthaul for the communication between the central processing unit (CPU) and the distributed access points (APs), which increases the infrastructure cost, leads to high installation time, and limits the deployment flexibility and adaptability. To address these challenges, this paper proposes two architectures for cell-free massive MIMO systems based on wireless fronthaul that is operating at a \textit{higher-band} compared to the access links: (i) A wireless-only fronthaul architecture where the CPU has a wireless fronthaul link to each AP, and (ii) a mixed-fronthaul architecture where the CPU has a wireless link to each cluster of APs that are connected together via optical fibers. These dual-band architectures ensure high-data rate fronthaul and provide high capability to synchronize the distributed APs. Further, the wireless fronthaul reduces the infrastructure cost and installation time, and enhances the flexibility, adaptability, and scalability of the network deployment. To investigate the achievable data rates with the proposed architectures, we formulate the end-to-end data rate optimization problem accounting for the various practical aspects of the fronthaul and access links. Then, we develop a low-complexity yet efficient joint beamforming and resource allocation solution for the proposed architectures based on user-centric AP grouping. With this solution, we show that the proposed architectures can achieve comparable data rates to those obtained with optical fiber-based fronthaul under realistic assumptions on the fronthaul bandwidth, hardware constraints, and deployment scenarios. This highlights a promising path for realizing the cell-free massive MIMO gains in practice while reducing the infrastructure and deployment overhead., Comment: This paper is accepted in IEEE Transactions on Wireless Communications