With the advent of 5G, the internet has entered a new video-centric era. From short-video platforms like TikTok to long-video platforms like Bilibili, online video services are reshaping user consumption habits. Adaptive Bitrate (ABR) control is widely recognized as a critical factor influencing Quality of Experience (QoE). Recent learning-based ABR methods have attracted increasing attention. However, most of them rely on limited network trace sets during training and overlook the wide-distribution characteristics of real-world network conditions, resulting in poor generalization in out-of-distribution (OOD) scenarios. To address this limitation, we propose SABR, a training framework that combines behavior cloning (BC) pretraining with reinforcement learning (RL) fine-tuning. We also introduce benchmarks, ABRBench-3G and ABRBench-4G+, which provide wide-coverage training traces and dedicated OOD test sets for assessing robustness to unseen network conditions. Experimental results demonstrate that SABR achieves the best average rank compared with Pensieve, Comyco, and NetLLM across the proposed benchmarks. These results indicate that SABR enables more stable learning across wide distributions and improves generalization to unseen network conditions.

This paper investigates a multi-user multiple-input single-output (MU-MISO) symbiotic radio (SR) system empowered by multiple reconfigurable intelligent surfaces (RISs). In this system, each RIS adopts a multi-functional reflection modulation scheme to simultaneously transmit data from Internet of Things (IoT) sensors and enhance the primary transmission. However, allocating all reflected power exclusively to IoT data transmission could compromise the capability of RISs to enhance the primary transmission. To address this issue, we propose a flexible power allocation scheme that partitions the power reflected from the RISs into two components: one for enhancing the primary transmission and the other for supporting IoT communication, fully exploiting the multi-functional potential of RISs. Subsequently, we formulate a joint optimization problem aimed at minimizing the transmit power subject to the rate requirements for both primary and RIS transmissions, involving the joint optimization of the beamforming at the base station (BS) and the reflection modulation design at the RISs. Given the non-convex constraints and the coupled variables within the problem, we develop an alternating optimization algorithm combined with difference-of-convex programming to efficiently solve the problem and determine the power allocation scheme. Furthermore, to reduce computational complexity, we consider uniform power allocation across all reflecting elements and introduce weighted parameters to flexibly balance between assisting primary transmission and supporting IoT communication. Simulation results demonstrate that our proposed power allocation scheme effectively balances the demands of the primary and RIS transmission, significantly reducing the required transmit power.

LiDAR-based object detection plays a crucial role in autonomous driving, yet remains vulnerable to ghost object attacks, where adversarially crafted point clouds trigger false detections. Traditional attack methods often require a large number of points and substantial computational resources, making them inapplicable in real-world scenarios. Although prior research has explored reducing the number of required attack points, real-world feasibility remains a challenge due to the high computational cost and attack generation time. While LiDAR object detection can be compromised given enough adversarially crafted points, we believe there are some critical points, which we call reduced attack budget, which are sufficient to attack the detector. Motivated by this consideration, we propose a novel geometric- and heuristic-based approach capable of generating effective ghost object attacks by leveraging the target’s contour characteristics. By strategically selecting a minimal set of adversarial points, as few as 20 points, our approach maintains high detection confidence, reduces attack execution time and attack budget by up to 4 and 73 times, respectively, in this paper. Our method has been verified on both simulated and real-world datasets (KITTI). The experimental results demonstrate that our optimized attack significantly reduces computational overhead and consequently improves the attack’s real-time feasibility.

This paper proposes a partition-based reconfigurable intelligent surface (RIS)-assisted multi-user multiple-input single-output (MU-MISO) symbiotic radio (SR) system. Unlike conventional RIS designs in SR systems that utilize all elements for secondary transmissions, which restricts its ability to support the primary transmission, the RIS is divided into two subsurfaces: one enhances primary transmissions while the other transmits IoT information via spectrum sharing. We formulate a joint optimization problem to minimize transmit power under rate constraints for both primary and IoT transmissions through active beamforming and passive RIS phase-shift design. To tackle the non-convex constraints and variable coupling in the formulated problem, we propose efficient optimization techniques, including alternating optimization and difference-of-convex methods. Furthermore, we propose a low-complexity interference-free scheme leveraging partitioned RIS to eliminate inter-user interference, which is unachievable with conventional RIS design. Simulation results reveal that compared to the conventional scheme, which can be viewed as a special case of partition-based RIS where all the reflecting elements are used to transmit IoT information, partition-based RIS demonstrates superior performance, thereby validating the advantages of RIS partitioning in SR systems.

LIDAR-based 3D object detection aims to enhance the situational awareness of autonomous vehicles. Despite recent advancements in this technology, there has been evidence that the susceptibility of 3D object detectors to signal spoofing is high, leading to the erroneous detection of "ghost objects" or the failure to detect genuine ones. While prior work has investigated the design of these new attacks and new defenses, the effect of weather conditions, which is a hot topic in autonomous vehicle research, on both attacks and defenses has never been studied. Inspired by this observation, in this paper, we present a novel genetic algorithm-based attack, entitled Rain-Reaper, that leverages on the effect of rain and identifies critical detection points used by 3D detectors. We show that adverse weather conditions not only diminish detection distance and accuracy but also expose the limitations of existing defenses. We have found that the unique characteristics of wet roads lead to underperforming defenses, thus, leading to a false sense of confidence in them. The effectiveness and efficiency of the attack and the robustness of the defenses have been evaluated with both simulated and real data. Our Rain-Reaper demonstrates a high attack success rate while successfully evading existing defenses with an adversarial point budget of up to 8.8 times smaller than previously demonstrated state-of-the-art attacks.

In next-generation Internet services, such as Metaverse, the mixed reality (MR) technique plays a vital role. Yet the limited computing capacity of the user-side MR headset-mounted device (HMD) prevents its further application, especially in scenarios that require a lot of computation. One way out of this dilemma is to design an efficient information sharing scheme among users to replace the heavy and repetitive computation. In this paper, we propose a free-space information sharing mechanism based on full-duplex device-to-device (D2D) semantic communications. Specifically, the view images of MR users in the same real-world scenario may be analogous. Therefore, when one user (i.e., a device) completes some computation tasks, the user can send his own calculation results and the semantic features extracted from the user's own view image to nearby users (i.e., other devices). On this basis, other users can use the received semantic features to obtain the spatial matching of the computational results under their own view images without repeating the computation. Using generalized small-scale fading models, we analyze the key performance indicators of full-duplex D2D communications, including channel capacity and bit error probability, which directly affect the transmission of semantic information. Finally, the numerical analysis experiment proves the effectiveness of our proposed methods.

The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect users' behaviour. Achieving real-time synchronization between the virtual bilocation and the user is complex, placing high demands on the Metaverse Service Provider (MSP)'s rendering resource allocation scheme. To tackle this issue, we propose a semantic communication framework that leverages contest theory to model the interactions between users and MSPs and determine optimal resource allocation for each user. To reduce the consumption of network resources in wireless transmission, we use the semantic communication technique to reduce the amount of data to be transmitted. Under our simulation settings, the encoded semantic data only contains 51 bytes of skeleton coordinates instead of the image size of 8.243 megabytes. Moreover, we implement Deep Q-Network to optimize reward settings for maximum performance and efficient resource allocation. With the optimal reward setting, users are incentivized to select their respective suitable uploading frequency, reducing down-sampling loss due to rendering resource constraints by 66.076% compared with the traditional average distribution method. The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

In order to enhance the diagnosis of turn-to-turn short circuit (TTSC) fault based on machine learning (ML), a novel method to decouple the demagnetization characteristics due to TTSC fault effect on magnet to improve the data integrity is presented in this article. The updated knee point of the magnet based on magnet temperature is obtained in real-time and a fault indicator indicative of the initialization of irreversible demagnetization is used to decouple the influence of rotor MMF from the magnetic field energy stored in the air-gap. An extensive set of data is obtained from analytical modelling of permanent magnet synchronous machine (PMSM) with TTSC fault based on winding function approach. The model fidelity is increased by incorporating the TTSC fault effect on magnet as a look-up-table obtained from finite element analysis. In addition to the simulation data, experimental data of PMSM with TTSC fault are used to train the machine learning algorithms. The results confirm that data integrity is improved and time-domain signal analysis are sufficient for training and diagnosis of TTSC fault based on ML algorithms.

The lane detection systems in ADAS and self-driving applications need to be resilient to adverse weather like rain, to minimize the chance of serious accidents. However, it is still challenging to maintain high precision in these conditions. State-of-the-art segmentation-based detectors use a naive post-processing method to quickly extract lane points from the segmented output based on the local maxima, but it is prone to failure when the segmentation contains errors. In this paper, we present an Adaptive Lane point EXtractor (ALEX) which overcomes this limitation by harnessing statistical properties from local regions of the segmentation to implicitly identify and compensate for errors. ALEX merges both local maximum and local mean statistics with CNN attributes to build a holistic hybrid feature set. Lane points are predicted from this representation by estimating their location on a reduced-size confidence map. A lateral offset is predicted to compute the precise location on the full-sized scene, while a class label prediction denotes which lane class the point belongs to. Besides the segmentation output and lane point ground truth, no additional information is required by ALEX, making it effectively agnostic to weather conditions and segmentation methods. Evaluation on two publicly available clear-weather databases and one rain-translated database verified that our approach consistently improved accuracy while reducing false positive and false negative rates, regardless of weather or segmentation method.

The drive for more electric aircraft (MEA) architecture has resulted in the introduction of high power density electric machines for aircraft propulsion applications. The reliability of the electrical machines in such harsh environments is a challenge that is seldom addressed. The paper proposes, through simulation, the use of aging model to accurately estimate the lifetime of a machine with turn-to-turn short-circuit (TTSC) condition. The proposed aging model considers all the aging factors due to electrical, mechanical and thermal phenomena. The paper also puts forth a cumulative stress curve for various loading & environmental constraints and uses the stress curve with winding temperature to create an aging model to accurately predict and estimate the lifetime of the machine. A bottom-up approach through the developed model can be used to estimate the lifetime of the machine in real-time.

In condition monitoring of electrical machines, wireless sensors enables access to internal signals that are relatively unexplored compared to the conventional external measurements. This paper demonstrates the application of wireless sensor to measure the rotor field winding current in a Brushless Synchronous Generator and compare the fault detection capability with the stator exciter field current. The faults considered are the stator armature and rotor field winding inter-turn short circuit fault. From the experimental investigation, the rotor field current measurements obtained through a wireless sensor is found to be more effective in tracking the evolution of a fault.

Energy harvesting has emerged to be a promising technique to promote sustainable operation of data gathering wireless sensor networks (WSNs). However, energy half-duplex constraints of the energy storage device and the hotspot problem of the tree-based topology lead to long delay for sustainable data gathering WSNs. In this paper, we aim to build a delay-efficient sustainable data gathering network through joint design of hybrid tree construction and priority based scheduling. Mixed integer nonlinear programming(MINLP) model is used to characterize the optimization problem to minimize sustainable data gathering delay. Since the original problem is NP-hard, it is decomposed into a tree construction sub-problem and a link scheduling sub-problem. Two approximation algorithms are proposed to solve them respectively. Simulation results show that our proposed algorithm outperforms the benchmark algorithms.

In wireless sensor networks (WSNs), to efficiently make the maximum value and the identity of corresponding sensor nodes available at the sink node is an important problem. In this paper, we develop a timer-based max function computation scheme over multiple access channels (TMCoMAC) in which timer scheme is combined with code division multiple access (CDMA) scheme to achieve fast max function computation with satisfying computation success probability. CDMA code is introduced to mitigate the influence of collision that limits the computation success probability of traditional timer-based computation schemes. An optimization problem to maximize the computation success probability is formulated and solved by using an iterative method. Numerical results are provided to show that our proposed algorithm can improve computation success probability with less delay overhead when CDMA sequence is sufficiently long. More specifically, our proposed scheme improves the computation success probability by about 16% - 24% compared to benchmark algorithm.

Licensed-assisted access (LAA), which conveys control signal via licensed anchor carrier and data information via both licensed and unlicensed bands, is a promising solution to enhance the throughput of wireless communications. In view of the potential impact on the incumbent services in the unlicensed band, how to design the medium access control (MAC) protocol for LAA system to make fair and friendly coexistence with its neighboring incumbent users is one of the most critical and challenging issues. In this paper, a LAA using LTE (LAA-LTE) system in the WiFi unlicensed spectrum is investigated. The listen-before-talk (LBT) protocol is designed for the LAA-LTE system. By quantifying the WiFi throughput in the coexisting system, allowable LTE transmission time is determined by considering different targets of WiFi service protection. Then, the LTE transmission time is optimized for maximizing the overall normalized channel rate contributed by both LAA-LTE and WiFi system, with the protection to the WiFi system. Our work offers guidelines of designing the LAA-LTE system, paving the way to a controllable, not only harmonious, coexistence of LAA-LTE and WiFi systems in the unlicensed spectrum.

In recent years, to efficiently deliver a specific function value is of great importance in sensing and monitoring wireless sensor networks. In this study, a priority‐aware hybrid scheduling scheme is proposed to achieve fast decentralised energy‐efficient max function computation in a single‐hop network. In the authors’ proposed scheme, priority‐aware time division multiple access (TDMA) scheme is used to first schedule the transmission. In contrast to traditional TDMA, where all the nodes in a network take turns to transmit, in the authors’ proposed scheme, the node with the maximum value is given the priority to transmit. However, the problem of collision exists and this still limits the performance of TDMA‐based scheme. Therefore, in order to improve the performance with the influence of collision, code division multiple access (CDMA) is introduced to recover information whenever collision occurs. To solve this, an optimisation problem is formulated to minimise average computation time subjected to the constraints on failure probability. The synergy of CDMA and TDMA contributes to reduction of computation failure probability as well as average computation delay. Moreover, when compared with the traditional round‐robin TDMA transmission, the scheduling rule in the proposed scheme helps to reduce number of transmissions for a single computation. Therefore, a reduction in energy consumption occurs as well. Numerical results show that our algorithm reduces average computation time and energy consumption for one‐shot max function computation, and with the advantage of better scalability.

Licensed-assisted access (LAA), which conveys data information via both licensed and unlicensed bands through spectrum aggregation, becomes a promising solution to enhance the capacity of wireless systems. In view of the potential impact on the incumbent system operating in unlicensed bands, the medium access control (MAC) protocol design for LAA system to harmonically coexist with its neighboring incumbent users is one of the most critical and challenging issues. In this paper, we consider a long-term evolution-based LAA (LAA-LTE) system operating in the WiFi unlicensed spectrum, for which the listen-before-talk-based MAC protocol is carefully designed. By quantifying the WiFi throughput and packet delay in the coexisting system, we formulate the constraints of LAA-LTE transmission time to fairly maintain WiFi services. The conditions of known and unknown network size of incumbent WiFi system are each considered separately. Then, the feasible region of LAA-LTE transmission time is determined, and the LAA-LTE protocol is optimized for maximizing the LAA-LTE throughput or the overall throughput contributed by both LAA-LTE and WiFi system. The theoretical analysis is validated via simulation, which also illustrates important observations when LAA-LTE and WiFi systems coexist. This paper offers guidelines to design the LAA-LTE system, paving the way to a controllable, not only harmonious, coexistence of LAA-LTE and WiFi systems in the unlicensed spectrum.

In this paper, we investigate a spectrum refarming system where an OFDMA system shares the licensed band of a CDMA system. Both systems share the same cell site, but each has different base station (BS) antennas. Joint resource allocation problem is formulated to optimize the CDMA receive power, OFDMA transmit power, and subcarrier assignment. Conventional interference control to protect the primary CDMA system relies on the availability of cross-channel gains (CCGs) from each secondary OFDMA transmitter to the CDMA BS receiver. However, the CCGs are difficult to be obtained due to lack of intersystem cooperation. To address this problem, we first decouple the original problem into higher and lower-level problems via primal decomposition. Then, a robust lower-level resource allocation (R-LRA) scheme, which controls interference without using CCGs is proposed, with which CDMA users can be sufficiently protected. Thereafter, an enhanced R-LRA (ER-LRA) scheme is proposed to decrease the conservation of R-LRA scheme. Assisted by the CDMA inner power control and based on the ER-LRA, efficient algorithm is designed to solve the higher-level problem. Extensions of the ER-LRA for other scenarios are also studied. Simulation results are provided to validate the proposed schemes in facilitating and improving the spectrum sharing performance.

Conventional spectrum refarming (SR) techniques assemble the legacy services to partial licensed spectrum, and free up the remained spectrum for operating other communication systems. In this paper, we propose a new broadband SR framework in which the orthogonal-frequency division multiple access (OFDMA) system dynamically shares the code division multiple access (CDMA) spectrum, which contains multiple bands in a concurrent manner. The interference margin provided by the downlink isometric random precoded CDMA system is first derived. To protect all the CDMA users, interference constraints that regulate the OFDMA transmission are then formulated. We formulate the joint CDMA load planning and OFDMA resource allocation problem for the SR system. By applying primal decomposition, it is shown that the higher-level problem is non-convex in general. We first propose an efficient algorithm to find the myopic optimal solution by investigating the derivative property of the higher-level problem. Through enhancing the original constrains, the higher-level problem is shown to be convex and solved with another efficient algorithm. Simulation results are provided to evaluate the SR performance, illustrating the significance of the CDMA load planning on the OFDMA throughput, the advantage of the proposed SR model over conventional SR, and the protection to the CDMA system.

Conventional spectrum refarming (SR) techniques assemble the legacy services to partial licensed spectrum, and free up the remained spectrum for operating other systems. In this paper, we propose a new broadband SR framework in which the OFDMA system can concurrently share partial or all the CDMA spectrum that contains multiple bands. The interference temperature provided by the downlink isometric random precoded CDMA system is derived, and the in-band and cross-band interferences introduced by the OFDMA system to CDMA system are quantified. With the derived interference temperature and interference power, resource allocation problems of the OFDMA system under full-concurrent and partial-concurrent broadband SR are formulated and solved. Numerical results are provided to evaluate the SR performance, illustrate the advantage of the full-concurrent broadband SR, and show the significance of the CDMA system load planning on the SR performance.

Spectrum refarming (SR) refers to a radio resource management technique which supports different generations of cellular networks to operate in the same radio spectrum. In this paper, an underlay SR model is proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) system to share the spectrum of a Code Division Multiple Access (CDMA) system through intelligently exploiting the interference margin provided by the CDMA system when operating with a low system load. The asymptotic signal-to-interference-plus-noise ratio (SINR) of the CDMA system is used to quantify the interference margin, which interestingly does not depend on the instantaneous information (spreading codes and channel state information) of the CDMA system, thanks to its internal power control. By using the transmit power constraints together with the derived interference margin, the uplink resource allocation problem for OFDMA system is formulated and solved through dual decomposition method. The proposed SR system only requires high level system parameters from the CDMA system, hence, the upgrading of legacy CDMA system is not needed. Simulation results have verified our theoretical analysis, and validated the effectiveness of the proposed resource allocation algorithm and its capability to protect the legacy CDMA users.

Distributed Energy Resources (DER) are one of the distinguished features of Smart Grid. A combination of small-scale energy generator and storage unit can produce energy to serve the associated load, while at the same time store or sell excessive energy. Assuming there is an energy surplus, the system can choose to sell a portion of its available energy to the market. In this work, an oligopoly model is developed in order to study dynamic pricing in such a scenario. The problem can be characterized as a dynamic N-player differential game, where the optimal solutions correspond to the equilibria of the game. We provide a mathematical analysis for the solution of the game, where a complete characterization of the steady-state price and optimal strategies of the players can be obtained in the symmetric case. Extensive numerical studies are provided to demonstrate the behaviors of the proposed market model and to analyze the impacts of various market parameters on the system.

Spectrum refarming (SR) is a promising radio resource management technique which allows different generations of cellular networks to operate in the same radio spectrum. In this paper, an underlay SR model is proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) system to refarm the spectrum assigned to a Code Division Multiple Access (CDMA) system through intelligently exploiting the interference margin provided by the CDMA system. We investigate the mutual effect of the two systems by evaluating the asymptotic signal-to-interference-plus-noise ratio (SINR) of CDMA users, based on which the interference margin tolerable by CDMA system is determined. With the interference margin together the transmit power constraints, the resource allocation problem of OFDMA system is formulated and solved through dual decomposition method. Simulation results have verified our theoretical analysis and validated the effectiveness of our proposed OFDMA resource allocation solution, as well as its protection to CDMA services.

As a novel fundamental platform for providing real time access to wireless network, vehicular communication is drawing more and more attentions in recent years. IEEE 802.11p is a main radio access technology which supports communication for high mobility terminals. Due to the limited coverage, it is usually deployed coupling with cellular network to achieve seamless mobility. In cellular/802.11p heterogeneous network, vehicular communication has the characteristics of short span of time associating with Road Side Unit (RSU). Moreover, the media access control (MAC) scheme of IEEE 802.11p decides that packet collision probability increasing followed by the increasing of user quantity, which leads to the decreasing of network throughput. In response to these compelling problems, we propose a fuzzy Q-learning based vertical handoff (FQVH) control strategy for supporting the mobility management. FQVH has online learning ability and can give optimal handoff decisions adaptively with no need for prior knowledge on handoff behavior. Simulation results verify that it can adjust handoff strategies to different traffic conditions, and keep users always connected to the best network.

Multi‐user multiple‐input–multiple‐output (MU‐MIMO) systems are a promising technology for increasing spectral efficiency and diversity gain in the up‐link channel. Space‐time block coding (STBC) or the spatial‐multiplexing (SM) scheme may selectively be used by each user. The simple techniques, zero‐forcing (ZF), STBC and successive interference cancellation are jointly applied to separate and detect all streams at the ZF‐STBC MIMO receiver. Unfortunately the channel estimation error (CEE) and error propagation (EP) are usually presented in practical multi‐layers detection. In this study, the author investigates the effect of CEE and EP on the bit error rate (BER) performance of the ZF‐STBC MIMO receiver over Rayleigh flat fading channels. They derive a nearly exact closed‐form BER for general phase shift keying/quadrature‐amplitude modulation with CEE and EP for arbitrary number of users. Finally, simulation results demonstrate the validity of the author's analysis.

In this paper, a non-coherent base station cooperation (NC-BSC) scheme is examined for the downlink OFDMA wireless cellular networks. We formulate the resource allocation in the scheme as a subcarrier allocation optimization problem with equal power allocated on each subcarrier. To balance the tradeoff between system throughput and fairness, a multi-cell scenario controllable fairness is extended from single-cell scenario mentioned in [1], based on which the controllable global fairness (GF) scheme in the NC-BSC system is proposed. Two heuristic iterative algorithms are proposed to realize the subcarrier allocation in the NC-BSC system with and without the controllable fairness in a distributed manner. The performance is compared with traditional dynamic subcarrier allocation in noncooperative multi-cell networks. Simulation results show the performance enhancement through implementation of NC-BSC and the effectiveness of multi-cell controllable fairness in the NC-BSC system.

Fair and efficient subcarrier assignment for an infrastructure-based cellular OFDMA network is a challenging problem due to interferences from neighboring cells. In this paper, we investigate this problem using potential game theory, where the utility function adopted is meant for minimizing the co-channel interferences among different players. Each of these players is considered to be a cell with a central base station (BS) and its multiple mobile stations (MS) in a downlink scenario. Under such formulation, we establish the potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game, which can be achieved via certain strategy dynamics such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and present numerical results to evaluate the performance of our game. Improvement in efficiency and fairness is observed in this study.

This paper investigates the subcarrier allocation problem for a downlink multi-cell multiuser OFDMA network using potential game theory. Each player is considered to be a central base station together with all the mobiles distributed within its coverage area. In such a system, co-channel interferences (CCI), if left uncontrolled, could hinder the transmissions and limit the throughputs of the users, especially those near the cell-edge area. Certain remedies, including power control with pricing, did not seem to solve the problem completely. We specifically address this issue from an interference-minimizing approach, where the utility function adopted is meant to minimize the total CCI among players. Under such formulation, we show that the formulated game can be mathematically described by a potential game. Hence, a Nash equilibrium (NE) will be guaranteed for the proposed game and stable solutions can be achieved via myopic gameplays such as the best/better responses. We propose our iterative algorithm for obtaining the NEs and address several performance issues such as fairness for edge-users and the price of anarchy. Numerical results show the improvement in efficiency and fairness using this approach.

We present a human centric cyber physical framework architecture of our in-pipe water monitoring and feedback system. This system comprises of the physical water distribution infrastructure, together with the hardware and software supported intelligent agents for water allotment, leak detection and contamination spread control. An agent-based approach for connecting the cyber and physical layers is selected, where the agents get information from sensors monitoring the physical components and provide this information to the cyber system. The Hidden Markov Models (HMM) are briefly discussed to determine water consumption patterns and make decisions for cyber and physical systems.

In this paper, the design of wireless inductive charger for portable electronic devices is present. There are two main parts have been included. The first part is the exciting circuit in which to provide sufficient input power to the primary charging platform. The exciting circuit is comprised by oscillator circuit and power amplifier circuit. Both of the two circuits have been simulated in software and verified by measurements. The second part is a two layer near uniform field planar inductive platform (primary coil). The design of the charging platform consists of two layers of square spirals overlapping each other using the principle of superposition. The strong areas (peaks) of one layer are superposition onto the weak areas (troughs) of the other layer. In this manner, a near uniform magnetic field suitable for power and signal transfer is created.

In this paper, we consider a scenario where distributed users in an OFDM-based system share the spectrum for transmission. Each network user (player) comprises a pair of transmit and receive nodes and will be allocated a given number of subcarriers. We propose a utility function that aims at efficiently allocating subcarriers to all players by minimizing the amount of interference generated. We first show that for the utility function used in the subcarrier assignment problem, it is possible to find a network potential function for the game. This guarantees the existence of at least one pure Nash equilibrium if each player is assigned with a predetermined number of subcarriers for transmission. Hence, convergence to Nash equilibrium can be achieved by iteratively playing the best-response game (also known as myopic game) among the players. Our simulation results show that distributing power over a number of subcarriers can achieve better per user capacity compared to the case where transmission is made through only a single subcarrier.

Based on the technology of Mobile Ad-hoc Network (MANET), we design and implement an Audio Conferencing Testbed (ACT) that is used for a group of people to set up virtual audio conferencing room to complete certain mission in places where network infrastructure is unavailable. ACT is built on popular Windows operating system with off-the-shelf IEEE802.lt (a.k.a. Wi-Fi) adapters as the enabling technology. Little assumption is made during the development process in order to minimize the gap between a laboratory testbed and a fully-operational system. Some notable features of ACT include: 1) it makes use of distributed TDMA scheme to provide "circuit- switched" type of Quality-of-Service (QoS) guarantee for audio traffic; 2) its broadcast tree building algorithm is able to minimize the latency of message dissemination to the whole network; 3) the protocol running in ACT is able to predict radio link break due to mobility so that service interruption is reduced; 4) and relative position information is available at each node in the network. Our work is focused on the system aspect, and a series of experiments are conducted in real environment to verify the system design and evaluate its performance.

The spokesmen election (SE) problem was first proposed in the wave expansion broadcast (WEB) protocol for minimizing broadcast latency in wireless multihop networks. It refers to how to select a set of transmitters from all informed nodes so that the number of uninformed nodes having correct reception is maximal. In this paper, the authors formulate the SE problem into posiform maximization problem, which is a special case of pseudo-Boolean optimization problems. Since maximizing posiform f is equivalent to finding the stability number of f's conflict graph, existing approximate algorithms for computing stability number could be utilized to find a near- optimal solution of SE problem; and new lower bound of the number of uninformed nodes with correct receptions is derived. Numerical results show that our proposed solution outperforms previous spokesmen election algorithm (SEA) in terms of both broadcast latency and broadcast redundancy.

In this paper, we develop kappa-connectivity in wireless multi-hop networks in the presence of both the log-normal shadowing and Nakagami-m fading. The formula are generally applicable in a variety of realistic physical situations. Based on the results, we are able to find the critical node density to satisfy node kappa-connectivity almost with probability 1. In addition, kappa-connectivity shows significant difference with distinct channel conditions, which necessitates a generic result. The result is useful for the design of a wireless multi-hop network in practice.

Resource allocation is a fundamental problem in connection-oriented networks. A preemption mechanism would provide available and reliable services to new connections with higher priority by tearing down existing connections of lower priority. However, end users of the existing connections that are preempted will suffer service disruptions. The duration spent and the work done for these connections are wasted, leading to lower useful utilization of the overall network resources. Soft preemption can alleviate this by rerouting a connection that is about to be preempted before actually tearing it down so that the interruption of ongoing service can be avoided. In this paper, we focus on minimizing the service disruptions caused as a result of preemption by proposing algorithms that incorporate the soft preemption feature. A centralized algorithm is developed to select the network links that have a high number of reroutable connections in order to minimize service disruptions. For feasible deployment, a decentralized preemption algorithm that uses local information is subsequently proposed. Simulation results indicate that these approaches not only reduce the service disruption but also lead to higher network throughput than what can be achieved by existing preemption algorithms.

This letter analytically examines the achievable energy efficiency of channel aware geographic-informed forwarding (CAGIF) algorithm, which chooses the next hop relay node by taking into consideration the underlying channel conditions, rather than purely maximizing the forwarding progress. The theoretical analysis in terms of the average forward distance is developed and the upper bound and lower bound of the average energy consumption are provided by referring to the retransmission techniques. Numerical results show that CAGIF significantly improves the energy efficiency over the previous geographic information based routing algorithms that ignore the channel conditions.

This paper proposes a new energy-efficient local metric, termed as efficient advancement metric (EAM), for channel aware geographic-informed forwarding (CAGIF) algorithm, which studies the optimal selection of the relay nodes by taking into account the underlying channel conditions. The proposed metric considers not only the forward distance but also the packet successful probability under a certain channel condition, rather than purely maximizing the forward distance, to choose the most energy-efficient relay node in the geographic- informed routing protocol in a CDMA-based wireless sensor network. The proposed algorithm only requires that nodes have the knowledge of their own location information and the location information of the source and destination nodes. The protocol assumes that nodes could vary transmission range to search for the optimal relay nodes according to this metric. An analytical framework is provided and numerical results show that there exists an optimum distance of a relay node under a certain channel condition to maximize the EAM for any fading conditions.

In wireless sensor network, it is always important to obtain accurate relative positions of each sensor node, especially when there is no anchor node in the network to provide an absolute coordinate system. In this paper, this problem was first addressed by building a local coordinate system to express relative locations. Then the Cramer-Rao lower bound (CRLB) in an anchor-free network is analyzed, and used to find the optimal path for locating a remote node through vector addition. Some geometric problems in the path setup process are also addressed. Through simulation, the authors showed that the proposed method could give better accuracy than previous similar approach, and even in certain case could outperform some other approach which has higher computational cost.

In classical code division multiple access (CDMA) based multi-channel medium access control (MAC) protocols for mobile ad hoc networks (MANETs), numerous exchanges of neighborhood information are required for code assignment such that nodes within a two-hop separation will adopt different transmission codes and therefore avoid the hidden terminal problem (HTP). However, such expensive communication overhead for code assignment is not desirable since it will cause an under-utilization of bandwidth, energy inefficiency and longer delays, which can significantly degrade the network performance. In this paper, a novel location-aware multi-channel MAC protocol is presented for a large-scale dense MANETs based on a scalable two-phase coding scheme, where the first-phase code is used for differentiating adjacent cells and the second-phase code is employed for distinguishing nodes in one specific cell. A node knows its first-phase code from its location information and requests its second-phase code from its cell leaden. This protocol eliminates the HTP during data transmission without the periodical exchange of neighborhood information. Furthermore, the mechanism of collision resolution in the control channel is described. The performance of the proposed protocol is analyzed in terms of the control overhead and delay. The theoretical results are confirmed by extensive simulations and it is shown that the new protocol significantly outperforms the classical CDMA-based multi-channel MAC protocols

This paper proposes a novel joint clustering and multi-channel medium access control (MAC) protocol for mobile ad hoc networks, based on a scalable two-phase coding scheme. It employs the first-phase codes for differentiating the clusters and the second-phase codes for distinguishing the nodes in a specific cluster. The proposed protocol effectively integrates the procedure of code assignment with dynamic clustering and henceforth substantially reduces the control overhead of code assignment in a code division multiple access (CDMA) based multi-channel MAC protocol while simultaneously combating the hidden terminal problem. Furthermore, the confliction detection and resolution mechanism for the allocation of the first-phase codes as well as the collision avoidance mechanism for the allocation of the second-phase codes in the control channel are also introduced. Analytical framework and extensive simulation results, in terms of control overhead and delay, are provided and compared to the traditional distributed CDMA based multichannel MAC algorithms with or without clustering.

In this paper, we study the network performance of a wireless multi-hop network in terms of the successful link probability and k-connectivity probability by taking into account shadowing. We provide the closed-form analytic results of the successful link probability, and henceforth k-connectivity, in the context of shadowing multi-hop networks. Given a certain number of nodes spatially distributed according to a Poisson point process, we examine the critical density to keep the probability that a node is k-connected close to 1. The impacts of the shadowing on the k-connectivity are illustrated and discussed. The results can be practically used for the design of a wireless multi-hop network.

New closed-form formulas for the call complete probability and the probability density function (pdf) of the completed call holding time (CCHT) are developed under the concurrent impacts of the resource insufficiency as well as the wireless link unreliability in the wireless mobile networks performance evaluation. The results are obtained with the general scenario, i.e. general call holding time, general cell residence time and the generalized wireless channel model. The analysis result is validated by the simulation model under typical call holding time and cell residence time distributions, Gilbert-Elliott or Fritchman wireless channel model. The comparison indicates that the wireless networks performance will be greatly overestimated without taking into account the unreliable wireless link effect.

In the hierarchical cellular system, the take-back procedure usually takes place when the overflowed slow or fast call crosses the microcell boundary. In this paper, three new take-back schemes, micro-macro, macro-micro and macro-macro, based on cell boundary crossing are proposed. In terms of call blocking probability and call dropping probability, the comparison shows that micro-macro outperforms the other schemes.

This paper introduces a novel joint clustering and multi-channel medium access control (MAC) protocol for mobile ad hoc networks (MANETs) based on a scalable two-phase coding scheme, where the first-phase code is used for differentiating the clusters and the second-phase code is employed to distinguish the nodes in a specific cluster. It mitigates the hidden terminal problem (HTP) during data transmission and efficiently incorporates the procedure of code assignment with adaptive clustering. We also introduce the connection detection and confliction resolution mechanisms for the allocation of the first-phase code in the control channel. Simulation results show that substantial improvement in terms of control overhead can be achieved by the proposed protocol over the traditional distributed code division multiple access (CDMA) based multi-channel MAC algorithms with clustering or without clustering

In this paper, we derive the distribution of multiple access interference (MAI) power for wireless code division multiple access (CDMA) ad hoc networks operating in a general Nakagami-m fading channel model. Furthermore, we propose a multi-code multi-packet transmission (MCMPT) scheme for it to increase the performance, in terms of the expected forward progress. Based on the instantaneous good channel conditions in a Nakagami-m fading channel, a node can initiate flexible number of parallel transmission of multiple packets on multiple codes. Numerical results show that adaptive MCMPT considering varying channel conditions not only outperforms the nonadaptive conventional packet transmission (CPT), but also achieves better progress improvement with the increasing values of parameter m in a slowly-varying Nakagami-m fading channel

In this paper, we propose a model to study the call performance in mobile network taking into account the inherent time varying wireless channel. The performance metrics call complete probability and call complete ratio are introduced and further derived with the general call holding time. The impacts of the wireless channel error characteristics and the system parameters on the call performance are illustrated and discussed. The sensitivity problem with respect to the call holding time distribution is investigated. The result indicates that both call complete probability and call complete ratio exhibit a significantly different variation under different call holding time. The analytical model is verified by simulation result.

We present a novel location-aware multi-channel medium access control (MAC) protocol for large-scale dense mobile ad hoc networks (MANETs) based on a scalable two-phase coding scheme, where the first-phase code is used to differentiate adjacent cells and the second-phase code is employed to distinguish nodes in one specific cell. It eliminates the hidden terminal problem (HTP) during data transmission without requiring periodical exchange of neighborhood information. Furthermore, we introduce a collision resolution mechanism in the control channel. We analyze the performance of the proposed protocol in terms of control overhead. Its theoretical results are confirmed by simulations and it is demonstrated that the new protocol significantly outperforms the classical code division multiple access (CDMA) based multi-channel MAC protocols.

In this letter, we propose a new logarithmic rate distortion model for DCT-based video encoders. The proposed model can fit into the actual rate curve by combining several logarithmic functions, where the boundary of each function is adaptive to the statistics of video sequence. Experimental results demonstrate that the new rate distortion model provides a more accurate estimation of the bit rate than existing models.

The channel assignment problem (CAP) in cellular systems has the task of planning the reuse of the limited available frequencies in a spectrum-efficient and interference-minimal way. We adopt an integer programming representation of the static channel assignment (SCA) formulated by Smith and Palaniswami. The tabu search (TS) algorithm is implemented to solve this problem. Ten benchmark problems are tested, and we show that the TS approach significantly outperforms other optimization techniques.

In this paper, we study a fixed wireless access (FWA) system supporting both fixed and mobile users. A multi-dimensional Markov chain is developed which captures the mobility and call arrival pattern of the users. Three different policies including complete sharing, guard channel and reserved trunk are evaluated. Analytical results are provided to demonstrate the effects of various parameters on the system performance.

A study on the effect of genetic parameters is carried out in order to find the optimum value of the parameters in genetic algorithms for solving personal communication service network planning problems. As for any genetic algorithm, one of the problems is its convergence behavior which is affected by many factors including the genetic parameters. The selection of these genetic parameters is generally quite ad hoc. However, we find in this study that proper parameter selection is critical because they significantly affect the convergence and optimality of the solution obtained.

This paper deals with the optimization of the design and radio network resource planning for cellular mobile communication systems. The key element to be considered for mobile network planning is cost. A hierarchical optimization planning method (HOP) is utilized since there are so many factors like system performance, terrain features, base station parameters, and cost factors which are involved in the large-scale system design. We present a three-level optimization approach for designing a cellular mobile system. It determines the cell number, cell site allocation, and the specific base station parameters in order to minimize the total system cost and to comply with the required system performance. The problem is formulated as a large combinatorial optimization model which can determine the optimal number of cells and select the best base stations' locations. The simulated annealing approach is developed to solve the hard combinatorial problem. Simulation results demonstrate the feasibility and effectiveness of the HOP approach for radio network planning.

With the trend towards higher performance in cellular networks, traffic control methods that assign available channel to cells dynamically provide more benefits than the conventional fixed assignment in generating better capacity and lesser forced termination. Previous studies of dynamic methods are based mainly on event driven simulation. A theoretical model for a cellular mobile communication system is presented in the paper. The comparison techniques are illustrated by examining a channel borrowing scheme. The characteristics obtained from the dynamic model and from event driven simulation are in agreement.>