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The multimode power-split architecture for hybrid electric vehicle (HEV) powertrains is generally known for the complexity of its operation. This paper first addresses the challenge of developing an automated on-line near-optimal control strategy for these systems. Particularly, a machine learning logic based on supervised learning is developed for on-line selection of the HEV operating mode, thus the particular set of clutches to be engaged. An efficiency-based approach is then adopted to determine the optimal power-split between powertrain components. Later, the developed strategy finds integration in an optimal design methodology for multimode power-split HEVs considering the effectiveness and ease of on-line controllability. The obtained results are compared with the ones by the traditional HEV design methodology that only considers off-line energy management. The illustrated design methodology with on-line control reveals efficient at identifying the multimode HEV design that demonstrates optimal predicted fuel economy values and ease of on-line controllability simultaneously. Results suggest that the HEV design optimization procedure may produce different outcomes and demonstrate more effective when the evaluation of the on-line controlled operation is integrated. [ABSTRACT FROM AUTHOR]

As Vehicular Ad hoc Network (VANET) features random topology and accommodates freely connected nodes, it is important that the cooperation among the nodes exists. This paper proposes a trust model called Implicit Web of Trust in VANET (IWOT-V) to reason out the trustworthiness of vehicles. Such that untrusted nodes can be identified and avoided when we make a decision regarding whom to follow or cooperate with. Furthermore, the performance of Cooperative Intelligent Transport System (C-ITS) applications improves. The idea of IWOT-V is mainly inspired by web page ranking algorithms such as PageRank. Although there does not exist explicit link structure in VANET because of random topology and dynamic connections, social trust relationship among vehicles exists and an implicit web of trust can be derived. To accomplish the derivation, two algorithms are presented, i.e., BayesTrust and VehicleRank. They are responsible for deriving the local and global trust relationships, respectively. The simulation results show that IWOT-V can accurately identify trusted and untrusted nodes if enough local trust information is collected. The performance of IWOT-V affected by five threat models is demonstrated, and the related discussions are also given. [ABSTRACT FROM AUTHOR]

In this correspondence paper, an underlay cognitive radio multicast network, consisting of a cognitive base station (CBS) and multiple multicast groups of secondary users (SUs), is considered. All SUs, belonging to a particular multicast group, are served by the CBS using a common primary user (PU) channel. The goal is to maximize the energy efficiency (EE) of the system, through dynamic adaptation of target rate and transmit power for each multicast group, under the PUs’ individual interference constraint. The optimization problem formulated for this is proved to be nonquasi-concave with respect to the joint variation of the CBS's transmit power and target rate. An efficient iterative algorithm for EE maximization is proposed along with its complexity analysis. Simulation results illustrate the performance gain of our proposed scheme. [ABSTRACT FROM AUTHOR]

This paper uses an information-theoretic lens to view the error bound of wireless local area network (WLAN) localization, which is recognized as one of the superior candidate localization techniques in the GPS-denied environment. Interestingly, we analogize the process of WLAN localization into one of information propagation in a parallel Gaussian noisy channel, and then derive the corresponding localization error bound from the channel capacity of the analogical information propagation system. Experimental results show that compared with the widely-known Cramer-Rao Lower Bound (CRLB), the proposed approach performs better in localization error bound estimation under most of the cases of different access point deployment and reference point calibration. [ABSTRACT FROM AUTHOR]

In this paper, we propose a deep reinforcement learning (DRL)-based method that allows unmanned aerial vehicles (UAVs) to execute navigation tasks in large-scale complex environments. This technique is important for many applications such as goods delivery and remote surveillance. The problem is formulated as a partially observable Markov decision process (POMDP) and solved by a novel online DRL algorithm designed based on two strictly proved policy gradient theorems within the actor-critic framework. In contrast to conventional simultaneous localization and mapping-based or sensing and avoidance-based approaches, our method directly maps UAVs’ raw sensory measurements into control signals for navigation. Experiment results demonstrate that our method can enable UAVs to autonomously perform navigation in a virtual large-scale complex environment and can be generalized to more complex, larger-scale, and three-dimensional environments. Besides, the proposed online DRL algorithm addressing POMDPs outperforms the state-of-the-art. [ABSTRACT FROM AUTHOR]

As a response to the challenge of data traffic explosion in wireless networks, content caching in device-to-device (D2D) communication networks has emerged as a promising solution. However, in practical deployment, D2D content caching has its own problems. In particular, not all of the user devices are willing to share the content with others due to numerous concerns, such as security, battery life, and social relationship. In this paper, we consider the factor of social relationship in the deployment of D2D content caching. First, we apply stochastic geometry theory to derive an analytical expression of downloading performance for the D2D caching network. Specifically, a social relationship model with respect to the physical distance is adopted in our analysis to obtain the average download delay performance using random and deterministic caching strategies. Second, to achieve a better performance in more practical and specific scenarios, we develop a socially aware distributed caching strategy based on a decentralized learning automaton, to optimize the cache placement operation in D2D networks. Different from the existing caching schemes, the proposed algorithm not only considers the file request probability and the closeness of devices as measured by their physical distance but also takes into account the social relationship between D2D users. Our simulation results show that the proposed algorithm can converge quickly and outperforms the random and deterministic caching strategies. With these results, our work sheds insights on the design of D2D caching in the practical deployment of 5G networks. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel algorithm for peak-to-average power ratio (PAPR) reduction of OFDM signals by executing partial transmit sequence (PTS) in minimal trellis of block codes. The proposed method uses a linear code with good minimal trellis to select the transmitted OFDM signal with minimum PAPR and to transmit side information with error correction. The goals of combining strategy of trellis and PTS are twofold: to provide a low complexity PTS for weighting vector search and to highlight error protection capability for side information. Simulation results show that the proposed scheme achieves good PAPR reduction with lower complexity, compared to other PTS approaches. [ABSTRACT FROM PUBLISHER]

In this paper, a mathematical model for the beacon-enabled mode of the IEEE 802.15.4 medium-access control (MAC) protocol is provided. A personal area network (PAN) composed of multiple nodes, which transmit data to a PAN coordinator through direct links or multiple hops, is considered. The application is query based: Upon reception of the beacon transmitted by the PAN coordinator, each node tries to transmit its packet using the superframe structure defined by the IEEE 802.15.4 protocol. Those nodes that do not succeed in accessing the channel discard the packet; at the next superframe, a new packet is generated. The aim of the paper is to develop a flexible mathematical tool able to study beacon-enabled 802.15.4 networks organized in different topologies. Both the contention access period (CAP) and the contention-free period defined by the standard are considered. The slotted carrier-sense multiple access with collision avoidance (CSMA/CA) algorithm used in the CAP portion of the superframe is analytically modeled. The model describes the probability of packet successful reception and access delay statistics. Moreover, both star and tree-based topologies are dealt with; a suitable comparison between these topologies is provided. The model is a useful tool for the design of MAC parameters and to select the better topology. The mathematical model is validated through simulation results. The model differs from those previously published by other authors in the literature as it precisely follows the MAC procedure defined by the standard in the context of the application scenario described. [ABSTRACT FROM AUTHOR]

Most existing scheduling algorithms for multimedia traffic incode-division multiple-access (CDMA) networks have been designed under the assumption that the physical layer operates with a bounded bit error rate (BER) such that the packet error rate (PER) in the link layer is also bounded. However, there is a tradeoff between the PER and the packet drop rate (PDR) caused by delay violations, i.e., by slightly degrading the PER, more packets can be sent, thus lowering the PDR. In this paper, we present a new cross-layer enhancement to optimize the cross-layer qualityof-service (QoS) parameter - the packet loss rate (PLR) - that accounts for both the PER and the PDR. Furthermore, we study the fairness issue in terms of the PLR experienced by different users. Then, we propose a novel algorithm to schedule uplink multimedia traffic in time-division multicode CDMA networks, which optimizes the PLR experienced by each user in each frame, subject to fair distribution of packet losses between users according to the proposed cross-layer enhancement and fairness constraint. Simulation results show that the proposed algorithm provides fairness in packet losses among users of different traffic classes and achieves superior performance over two previous algorithms in terms of increasing the system capacity and reducing the PLR and average delay because of the cross-layer enhancement. [ABSTRACT FROM AUTHOR]

In this paper, we propose a fast and efficient adaptive transmission algorithm for the Mobile WiMAX system. In our algorithm, we select the position of the boundary between the downlink and uplink subframes, the positions of the service, flows within the frame, the coding and modulation schemes, and the transmission power values. Our algorithm gains high spectral efficiency, satisfies quality-of-service (QoS) requirements for the service flows, and has low computational complexity. The algorithm includes a frame boundary position optimization procedure, downlink and uplink optimization procedures, as well as a procedure that selects a transmission power value that enables satisfaction of the QoS requirements. All these procedures are novel, efficient, and fast. We evaluate the adaptive transmission algorithm by performing a system-level simulation of the Mobile WiMAX system with multisector topology. We show that our algorithm has high spectral efficiency and low computational complexity, enabling QoS provisioning. [ABSTRACT FROM AUTHOR]

There are numerous research challenges that need to be addressed until a wide deployment of vehicular ad hoc networks (VANETs) becomes possible. One of the critical issues consists of the design of scalable routing algorithms that are robust to frequent path disruptions caused by vehicles' mobility. This paper argues the use of information on vehicles' movement information (e.g., position, direction, speed, and digital mapping of roads) to predict a possible link-breakage event prior to its occurrence. Vehicles are grouped according to their velocity vectors. This kind of grouping ensures that vehicles, belonging to the same group, are more likely to establish stable single and multihop paths as they are moving together. Setting up routes that involve only vehicles from the same group guarantees a high level of stable communication in VANETs. The scheme presented in this paper also reduces the overall traffic in highly mobile VANET networks. The frequency of flood requests is reduced by elongating the link duration of the selected paths. To prevent broadcast storms that may be intrigued during path discovery operation, another scheme is also introduced. The basic concept behind the proposed scheme is to broadcast only specific and well-defined packets, referred to as "best packets" in this paper. The performance of the scheme is evaluated through computer simulations. Simulation results indicate the benefits of the proposed routing strategy in terms of increasing link duration, reducing the number of link-breakage events and increasing the end-to-end throughput. [ABSTRACT FROM AUTHOR]

Recently, ultra wide-band (UWB) wireless communication technology, which provides high data transmission rates and is capable of linearly trading off between throughput and signal-to-noise ratio (SNR), has drawn much attention for short-range wireless networks. To fully exploit its desirable features and to minimize its interference with coexisting other systems requires knowledge of the SNRs at the receivers. In this paper, we propose an algorithm for estimating the pulse energy-to-noise ratio of an UWB signal through utilization of output samples from a correlator in the receiver and evaluate the performance of the proposed algorithm through computer simulation. A notable feature of the proposed algorithm is that it does not affect the effective throughput because the estimation process does not require any additional specific training signals. [ABSTRACT FROM AUTHOR]

The deployment of large-scale UAV clusters for cluster advantages will lead to high competition and excessive congestion of spectrum resources, which results in mutual interference. This paper investigates the interference-aware online spectrum access problem for multicluster Flying Ad-Hoc Network (FANET) under different network topologies, i.e., the locations of UAV clusters are varying. First, the problem is formulated as a data-assisted multistage channel access game with the goal of mitigating interference of all UAV clusters and decreasing channel switching cost during each slot. As we prove that the game is an exact potential game that guarantees at least one pure-strategy Nash equilibrium and interference-aware online channel preserving based concurrent best response (IOCPCBR) algorithm, an online distributed algorithm is proposed to achieve the desirable solution. Finally, the simulation results demonstrate the validity and effectiveness of the multistage channel access game as well as IOCPCBR algorithm. [ABSTRACT FROM AUTHOR]

The deployment of cloud and edge computing forms a three-tier mobile computing network, where each task can be processed locally, by the edge nodes, or by the remote cloud server. In this paper, we consider a cooperative three-tier computing network by leveraging the vertical cooperation among devices, edge nodes and cloud servers, as well as the horizontal cooperation between edge nodes. In this network, we jointly optimize the offloading decision and the computation resource allocation to minimize the average task duration subject to the limited battery capacity of devices. However, the formulated problem is a large-scale mixed integer non-linear optimization problem with the growing number of base stations and devices, which is NP-hard in general. To develop an efficient offloading scheme with low complexity, we conduct a series of reformulation based on reformulation linearization technology and further propose a parallel optimization framework by utilizing alternating direction method of multipliers (ADMM) method and difference of convex functions (D.C.) programming. The proposed scheme decomposes the large-scale problem into some smaller subproblems, which are done across the multiple computation units in a parallel fashion to speed up the computation process. Simulation results demonstrate that the proposed scheme can obtain a near-optimal performance with low complexity, and can reduce up to 24% of the task duration compared with other schemes. Simulation also shows how much the vertical and horizontal computation cooperations affect the system performance under different network parameters. [ABSTRACT FROM AUTHOR]

In this paper, we study the energy efficiency (EE) optimization for simultaneous wireless information and power transfer in multiple-input-multiple-output two-way amplify-and-forward relay networks, where the energy-constrained relay harvests energy from two sources’ signals by power splitting (PS) scheme to forward the information of two sources. Our objective is to jointly design the sources and relay precoding matrices and the PS ratio to maximize the EE of the network, under the transmit power constraints at sources and relay and the minimum spectral efficiency requirement. We transform the nonconvex precoding and PS design problem into a difference of convex programming and propose an efficient iterative algorithm based on the constrained concave convex procedure to obtain a local optimum. To reduce computational complexity, we propose a generalized singular value decomposition based channel diagonalization scheme to simplify the optimization into a joint source and relay power allocation problem. The alternating optimization method is employed to solve this problem and a suboptimal solution to the EE maximization problem is obtained. Simulation results demonstrate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

In wireless sensor-actor networks, sensors probe their surroundings and forward their data to actor nodes. Actors collaboratively respond to achieve predefined application mission. Since actors have to coordinate their operation, it is necessary to maintain a strongly connected network topology at all times. Moreover, the length of the inter-actor communication paths may be constrained to meet latency requirements. However, a failure of an actor may cause the network to partition into disjoint blocks and would, thus, violate such a connectivity goal. One of the effective recovery methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary recovery schemes either impose high node relocation overhead or extend some of the inter-actor data paths. This paper overcomes these shortcomings and presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies on the local view of a node about the network to devise a recovery plan that relocates the least number of nodes and ensures that no path between any pair of nodes is extended. LeDiR is a localized and distributed algorithm that leverages existing route discovery activities in the network and imposes no additional prefailure communication overhead. The performance of LeDiR is analyzed mathematically and validated via extensive simulation experiments. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of real-time transmission scheduling over time-varying channels. We first formulate this transmission scheduling problem as a Markov decision process and systematically unravel the structural properties (e.g., concavity in the state-value function and monotonicity in the optimal scheduling policy) exhibited by the optimal solutions. We then propose an online learning algorithm that preserves these structural properties and achieves \varepsilon-optimal solutions for an arbitrarily small \varepsilon. The advantages of the proposed online method are given as follows: 1) It does not require a priori knowledge of the traffic arrival and channel statistics, and 2) it adaptively approximates the state-value functions using piecewise linear functions and has low storage and computation complexity. We also extend the proposed low-complexity online learning solution to enable prioritized data transmission. The simulation results demonstrate that the proposed method achieves significantly better utility (or delay)–energy tradeoffs compared to existing state-of-the-art online optimization methods. [ABSTRACT FROM PUBLISHER]

Recent research has led to the design of effective steering control strategies that employ, as controlled variables, the steering velocity and the yaw rate. The yaw rate can be measured by an inertial platform, which is usually already installed on modern motorcycles for advanced traction and braking control systems. Thus, there is an interest in developing effective steering angle estimators to implement single-sensor control strategies without introducing any additional cost for the semi-active steering damper control system. This paper proposes a robust minimum variance linear time-invariant filter and a linear parametrically varying observer to estimate the steering angle based on yaw rate and vehicle speed measurements, the performance of which is compared both via simulation and experimental data. The closed-loop performance of the single-sensor control strategies is finally evaluated and compared with that obtained with the two-sensor algorithm. [ABSTRACT FROM PUBLISHER]

Electronically controlled air suspension systems have been used in vehicles to improve ride comfort and handling safety by adjusting vehicle height. This paper proposes a new nonlinear controller to adjust the height of the vehicle sprung mass (height control) and to regulate the roll and pitch angles of the vehicle body (leveling control) by an air suspension system. A sliding mode control algorithm is designed to improve the tracking accuracy of the control and to overcome nonlinearities and uncertainties in the air suspension system. A mathematical model of the air suspension system is formulated in a nonlinear affine form to describe the dynamic behavior of the system and to derive the control algorithm. The sliding mode observer is also designed to estimate the pressures inside four air springs. The effectiveness and performance of the proposed control algorithm are verified by simulations and actual vehicle tests. [ABSTRACT FROM PUBLISHER]

Driving simulators are increasingly being used for driver evaluation and/or education. In this paper, we describe the design and the modeling aspects of a 2-degree-of-freedom (2-DOF) low-cost motion platform allowing the rendering of the longitudinal and yaw movements. This prototype will be used to study various configurations of motion rendering and the impact of these variants on controllability and simulator sickness. The whole motion platform is considered as two coupled systems that are linked mechanically. The first system consists of a motorized rail for the longitudinal movement, which is mounted on top of the second system, which is a motorized turret allowing rotation of the platform. We present the platform mechanics and a number of experimental studies that have been carried out to obtain a characterization of the platform capabilities and frequency responses, as well as to assess platform performance in a classical drive operation. First conclusions and directions of future work are presented. [ABSTRACT FROM PUBLISHER]

The enhanced distributed channel access (EDCA) mechanism of the IEEE 802.11e standard provides quality-of-service (QoS) support through service differentiation by using different medium-access-control (MAC) parameters for different stations. The configuration of these parameters, however, is still an open research challenge, as the standard provides only a set of fixed recommended values that do not take into account the current wireless local area network (WLAN) conditions and, therefore, lead to suboptimal performance. In this paper, we propose a novel algorithm for EDCA that, given the throughput and delay requirements of the stations that are present in the WLAN, computes the optimal configuration of the EDCA parameters. We first present a throughput and delay analysis that provides the mathematical foundation upon which our algorithm is based. This analysis is validated through simulations of different traffic sources (both data and real time) and EDCA configurations. We then propose a mechanism to derive the optimal configuration of the EDCA parameters, given a set of performance criteria for throughput and delay. We assess the effectiveness of the configuration provided by our algorithm by comparing it against 1) the recommended values by the standard, 2) the results from an exhaustive search over the parameter space, and 3) previous configuration proposals, which are both standard and nonstandard compliant. Results show that our configuration outperforms all other approaches. [ABSTRACT FROM AUTHOR]

Relay selection is crucial in improving the performance of wireless cooperative networks. Most previous works for relay selection use the current observed channel conditions to make the relay-selection decision for the subsequent frame. However, this memoryless channel assumption is often not realistic given the time-varying nature of some mobile environments. In this paper, we consider finite-state Markov channels in the relay-selection problem. Moreover, we also incorporate adaptive modulation and coding, as well as residual relay energy in the relay-selection process. The objectives of the proposed scheme are to increase spectral efficiency, mitigate error propagation, and maximize the network lifetime. The formulation of the proposed relay-selection scheme is based on recent advances in stochastic control algorithms. The obtained relay-selection policy has an indexability property that dramatically reduces the computation and implementation complexity. In addition, there is no need for a centralized control point in the network, and relays can freely join and leave from the set of potential relays. Simulation results are presented to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we consider cross-layer scheduling for the downlink of amplify-and-forward (AF) relay-assisted orthogonal frequency-division multiple-access (OFDMA) networks. The proposed cross-layer design takes into account the effects of imperfect channel-state information (CSI) at the transmitter (CSIT) in slow fading. The rate, power, and subcarrier allocation policies are optimized to maximize the system goodput (in bits per second per hertz successfully received by the users). The optimization problem is solved by using dual decomposition, resulting in a highly scalable distributed iterative resource-allocation algorithm. We also investigate the asymptotic performance of the proposed scheduler with respect to (w.r.t.) the numbers of users and relays. We find that the number of relays should grow faster than the number of users to fully exploit the multiuser diversity (MUD) gain. On the other hand, diversity from multiple relays can be exploited to enhance system performance when the MUD gain is saturated due to noise amplification at the AF relays. Furthermore, we introduce a feedback-reduction scheme to reduce the computational burden and the required amount of CSI feedback from the users to the relays. Simulation results confirm the derived analytical results for the growth of the system goodput and illustrate that the proposed distributed cross-layer scheduler only requires a small number of iterations to achieve practically the same performance as the optimal centralized scheduler, even if the information exchanged between the base station (BS) and the relays in each iteration is quantized, and the proposed CSI feedback reduction scheme is employed. [ABSTRACT FROM AUTHOR]

In this paper, we present an iterative joint channelestimation and data-detection technique for multiple-input-multiple-output (MIMO) code-division multiple-access (CDMA) systems over Rayleigh fading channels. The proposed receiver performs channel estimation and data detection using the expectation-maximization (EM) algorithm. We derive a closedform expression for the optimized weight coefficients of the EM algorithm, which is shown to provide large performance improvement relative to the conventional equal-weight EM-based signal decomposition. Our results show that the receiver can achieve near-optimum performance with modest complexity using very few training symbols. Furthermore, our simulation results confirm that the proposed receiver is near-far resistant and offers fast convergence in severe near-far scenarios. [ABSTRACT FROM AUTHOR]

Determining the location of a source from its emissions has gained considerable interest over the past few years. In this paper, by utilizing the time difference of arrival (TDOA) of a signal received at spatially separated sensors, a novel algorithm for source location is proposed. The algorithm is based on the constrained total least-squares (CTLS) technique, and an iterative technique based on Newton's method is utilized to give a numerical solution. By using a perturbation analysis, the bias and covariance of the proposed CTLS algorithm are also derived. Simulation results show that the proposed CTLS algorithm gives sufficient accuracy with lower computational cost, and more importantly, it is more robust to large measurement noise than the compared algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we propose a cross-layer resource-allocation scheme for orthogonal frequency-division multiple-access (OFDMA) systems with imperfect channel-state information (CSI). In our modeling, we consider two traffic types: 1) streaming traffic, which requires a maximum guaranteed average delay, and 2) elastic traffic with flexible rate requirements. We then consider queue-state information (QSI) and CSI in a cross-layer framework to maximize the total transmission rate of elastic users while the average delay constraint for streaming users and the maximum transmission power constraint are satisfied. We also consider the impact of imperfect CSI. An algorithm is then proposed based on the dual decomposition method to obtain the subcarrier assignment and power allocation for each user. Using simulations, we evaluate the impact of streaming traffic on the total achievable rate of elastic users for different values of the required outage probability. It is also shown by simulation that, by increasing the variance of CSI estimation, the total rate of elastic traffic is decreased. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of direction-of-arrival (DOA) estimation for a multicarrier code-division multiple-access (MC-CDMA) system with an antenna array. We reconstruct the received signal to form a data model with a multi-invariance property, and then, a multi-invariance estimation of signal parameters via rotational invariance technique (ESPRIT) algorithm for DOA estimation is proposed. This algorithm has improved DOA estimation performance and identified more DOAs compared with an ESPRIT algorithm. Moreover, our algorithm enables DOA estimation of a large number of impinging waves. Simulation results illustrate the performance of this algorithm. [ABSTRACT FROM AUTHOR]

The focus of this paper is a proposal for a computationally efficient dynamic subcarrier allocation (DSA) algorithm for orthogonal frequency-division multiple access (OFDMA) systems. The proposed DSA algorithm considerably reduces the computational complexity and the amount of channel quality information (CQI) compared to amplitude- craving greedy (ACG) algorithms, which use full CQI. At the same time, the performance of the proposed algorithm closely approaches that achieved by ACG algorithms. Moreover, the authors present a new bandwidth-assignment algorithm produced by modifying bandwidth as- signment based on the signal-to-noise ratio (BABS). This modified BABS algorithm enables the proposed DSA algorithm to produce a strong outage performance gain over the conventional scheme. [ABSTRACT FROM AUTHOR]

This paper presents a modified decorrelated delay lock loop (MD-DLL) for synchronous direct-sequence code-division multiple-access (DS-CDMA) systems under multiuser environments. The structure of the MD-DLL is similar to that of a traditional delay lock loop (T-DLL), aside from the fact that the despreading signals in T-DLL are replaced by a linear combination of all the users' code sequences with various weightings and timing offsets. The basic principles of MD-DLL are given as follows: 1) to use the decorrelating technique of a multiuser detector to remove the multiple-access interference at the on-time code position instant and 2) to choose a proper timing offset for the code sequences to reduce the weighting imbalance between the two arms of the tracking loop and suppress noise enhancement. The proposed MD-DLL scheme solves the tracking bias problems in a decorrelated delay lock loop under a low-signal-to-noise-ratio (SNR) condition. Computer simulations based on Gold code sequences are used to verify the findings. It is shown that MD-DLL achieves a better and stable S-curve with negligible tracking bias, better rms tracking error and mean-time-to-lose-lock performance under high-SNR conditions, and stronger near-far resistance than T-DLL. [ABSTRACT FROM AUTHOR]

Nonline-of-sight (NLOS) conditions pose a major challenge to radio positioning. In this paper, a constrained-optimization-based location algorithm is proposed to jointly estimate the unknown location and bias by using the sequential quadratic programming (SQP) algorithm. This method does not rely on any prior statistics information, and simulation results show that the proposed method considerably outperforms existing methods. To reduce the complexity of the SQP-based algorithm, we further propose a Taylor-series expansion-based linear quadratic programming (TS-LQP) algorithm. It is demonstrated that the computational complexity of the TS-LQP algorithm is only a fraction of that of the SQP algorithm, whereas the accuracy loss is limited. Also, maximum-likelihood (ML) algorithms that are suited for different NLOS error statistics are developed under several circumstances when there are different levels of a priori information. The analytical performance of the ML estimation (MLE) is investigated. Moreover, analytical expressions to approximate the variance of the MLE with and without model parameter mismatches are derived. Simulation results show that the approximate variance can be used as a better accuracy measure than the Cramer-Rao lower bound (CRLB). [ABSTRACT FROM AUTHOR]

The dual-decomposition-based sum capacity maximization algorithm for the vector broadcast channels consists of the following two nested loops: The inner loop is an iterative water-filling-like algorithm that optimizes the covariance matrices for a fixed water level, and the outer loop finds the optimum water level by using a bisection search. Recently, an improved version has been proposed, where the inner loop is optimized only to a certain tolerance that still guarantees algorithm convergence. This requires tracking the instantaneous error of the inner loop, and this issue has not yet been addressed. In this paper, we provide a tight upper bound of the instantaneous error of the inner loop, which can be used to construct a nonheuristic stopping criterion. Specifically, we derive the Lagrange dual function of the inner optimization problem and provide a method to obtain a feasible dual variable from which a tight upper bound of the instantaneous error can easily be computed. We also show that the rate of convergence of the global algorithm can substantially be improved by introducing a covariance normalization step between two successive outer iterations. [ABSTRACT FROM AUTHOR]

Shortened turbo product codes (TPCs) have already been adopted in many standards. In this paper, we study shortened TPCs from two aspects, namely encoding design and decoding algorithm. To obtain different encoding block sizes, shortened-extended Hamming codes are used as the component codes of product codes in the IEEE 802.16 Standard. To design a good structure for the shortened TPC, we compute the undetected error probability of its corresponding component codes. The component codes are shortened-extended Hamming codes, and their optimal generator polynomials are selected in terms of their undetected error probability. For the decoding algorithm, we present an efficient Chase decoding algorithm for shortened TPCs in flat fading channels. In the proposed scheme, the reliability factor used in Pyndiah's scheme is not needed; thus, the decoding complexity is greatly reduced by avoiding the normalization operation of the whole code word at each iteration. Simulation results are also presented to verify the performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Mobile positioning has drawn significant attention in recent years. Nonline-of-sight (NLOS) propagation error is the dominant error source in mobile positioning. Most previous research in this area has focused on NLOS identification and mitigation. In this paper, we investigate new positioning algorithms to take advantage of the NLOS propagation paths rather than canceling them. Based on a prior information about the NLOS path, a geometrical approach is proposed to estimate mobile location by using two NLOS paths. On top of this, the least-squares (LS)-based position estimation algorithm is developed to take multiple NLOS paths into account, and its performance in terms of root mean-square error (RMSE) is analyzed. A general LS algorithm considering both LOS and NLOS paths is also derived, and the maximum likelihood-based algorithm is presented to jointly estimate the mobile's and scatterers' positions. The Cramer-Rao lower bound on the RMSE is derived for the benchmark of the performance comparison. The performance of the proposed algorithms is evaluated analytically and is done via computer simulations. Numerical results demonstrate that the derived analytical results closely match the simulated results. [ABSTRACT FROM AUTHOR]

In this paper, a new channel-estimation algorithm based on maximum-likelihood (ML) algorithm for estimation and tracking of the multiple-input-multiple-output (MIMO) channels is presented. The ML algorithm presents the optimum estimation when the exact channel model is known. The derived channel-estimation algorithm is very efficient, with a computational complexity comparable to the least mean square and much lower than the recursive least squares and the Kalman algorithms. The proposed algorithm is analyzed, and the effect of the channel-tracking error is applied as a modifying component for the derived algorithm. The proposed algorithm is simulated for half- and full-rank flat-fading time-varying MIMO channels for the different values of fDT, Eb/No, and training lengths via Monte Carlo simulation technique. The minimum mean-square-error (mmse) joint detector is considered as the detection algorithm. The output of the mmse receiver is considered as the virtual training data in the blind mode of operation: the same as in the decision-directed algorithm. By various simulations, the bit error rate and the mse of tracking the proposed algorithm for different values of fDT, presenting the speed of channel variations, are evaluated and compared with the Kalman filtering approach. By simulating the proposed algorithm for different values of the training length, the minimum training length required for different channel conditions is extracted. [ABSTRACT FROM AUTHOR]

In this paper, we propose an iterative detection scheme in the presence of residual frequency offsets (RFOs) using the space-alternating generalized expectation-maximization algorithm for an orthogonal-frequency-division-multiple-access uplink system. In the proposed scheme, the expectation step intends to remove intercarrier interference (ICI) due to the RFOs of simultaneous users in the received signals. Then, the maximization step is utilized to estimate the required parameters for each user (i.e., RFO, data symbols, and channel state information) employing the ICI-cancelled signals. Simulation results show that the proposed scheme achieves almost ideal bit-error-rate performance as long as the magnitude of the normalized RFO value is within 0.2. [ABSTRACT FROM AUTHOR]

It has been well recognized that significant throughput gains can be leveraged in multiuser wireless communication systems by exploiting multiuser diversity with a smart scheduler. This scheduler collects channel state information (CSI) from all users and allocates the resources to the user(s) experiencing favorable channel conditions. However, for a frequency-division-duplex system with a large number of users, how to efficiently collect the required CSI will be a challenging task, especially when the feedback links are of limited capacity. In this paper, we propose a scheduling algorithm to exploit multiuser diversity with possibly imperfect one-bit channel state feedback. The basic idea is to define a threshold λ and let each user report one-bit information to the scheduler about the comparison between its measured channel fading level and λ. Correspondingly, the scheduler uses these feedback bits to classify all users into two sets and assigns the channel to one user belonging to the set experiencing favorable channel conditions. Several implementation schemes are developed by attacking the optimization of λ under different system configurations, covering both the case when the one-bit feedback is perfect and those when the one-bit feedback is imperfect. Computer simulations show that when the user number is large, say, more than ten users, the proposed scheduling supports significantly larger data rate over the round-robin scheduling, while in comparison with the optimum scheduling with complete CSI, the performance loss is limited if the one-bit feedback is of high reliability. In addition, our studies show that we can effectively enhance the robustness against feedback imperfectness by incorporating the feedback reliability into optimization of λ. [ABSTRACT FROM AUTHOR]

Energy constraints have a significant impact on the design and operation of wireless sensor networks. This paper investigates the base station (BS) selection (or anycast) problem in wireless sensor networks. A wireless sensor network having multiple BSs (data sink nodes) is considered. Each source node must send all its locally generated data to only one of the BSs. To maximize network lifetime, it is essential to optimally match each source node to a particular BS and find an optimal routing solution. A polynomial time heuristic is proposed for optimal BS selection and anycast via a sequential fixing procedure. Through extensive simulation results, it is shown that this algorithm has excellent performance behavior and provides a near-optimal solution. [ABSTRACT FROM AUTHOR]

Privacy is becoming a major issue in ad hoc networks. In this paper, using pseudonimity for achieving communication anonymity in networks that apply geographic-routing algorithms is explored. An Anonymous Receiver-Contention POsitioning (ARCPO) routing algorithm is proposed. Node identities (IDs) are kept anonymous. Pseudonyms, i.e., the positions of destinations, are used for data-packet delivery. The anonymity for a destination relies on the difficulty of matching its position to its ID by any observer. Position servers that provide node position information act as trusted third parties and handle identity management. Node mobility makes the use of the pseudonym momentary, and therefore can further improve privacy. The anonymity for the source and intermediate nodes in the path is also achieved because they are not required to reveal any identity information. A receiver-contention mechanism is proposed so that a next hop can be generated without local position information exchange, which otherwise may lead to severe privacy degradation. Analysis and simulation show that while ARCPO guarantees anonymous communication in ad hoc networks, its routing performance degrades moderately compared with other position routing algorithms. [ABSTRACT FROM AUTHOR]

Although it has been studied extensively for additive white Gaussian noise and flat fading channels, the problem of continuous-mode frame synchronization over frequency-selective channels has received much less attention. In this paper, based on the maximum likelihood criterion, we derive a computationally efficient continuous-mode algorithm for joint frame synchronization, channel and frequency offset estimation for linear modulations transmitted through unknown frequency-selective channels affected by carrier-frequency offset. Computer simulations show that the proposed algorithms exhibit low implementation complexity and good performance. [ABSTRACT FROM AUTHOR]

In this paper, a novel low-complexity tree-search (TS) algorithm, which is referred to as a hierarchical tree search (HTS), is proposed for soft-output multiple-input–multiple-output (MIMO) detection to mitigate the performance loss caused by an early termination. The proposed HTS algorithm is realized by the following two components: the hierarchical set partitioning to find all hypotheses with reasonable quality as fast as possible and to fairly improve them and the new cost metric to determine the search order by considering the quality of the hypotheses found so far. Through simulation, it is shown that the performance–complexity tradeoff of the proposed HTS algorithm surpasses those of the existing algorithms in various MIMO configurations. [ABSTRACT FROM PUBLISHER]

In traditional multiple-input–multiple-output (MIMO) channel and MIMO one-way relay system, nonlinear precoding design has shown significant performance gain over linear design. In this paper, we aim to study nonlinear precoding design for MIMO amplify-and-forward (AF) two-way relay systems, where nonlinear minimal mean square error (MMSE) decision feedback equalizers (DFEs) are used in two destinations, and linear transmit precoding is applied at the source and relay nodes. We first investigate nonlinear precoding design, where the precoding is only conducted at two sources for a fixed-relay precoder. After some transformations, we prove that this design problem is convex, and an efficient algorithm is provided to find the optimal solution. Then, we consider the nonlinear joint precoding design to further incorporate relay precoding. Due to the nonconvexity of this problem, we first propose an iterative algorithm (Algorithm I) to approach the optimal solution. It is proven that Algorithm I is convergent and can converge to a stationary point of the joint design problem. Moreover, we present a simplified iterative algorithm (Algorithm II) for joint precoding design to reduce the design complexity. It is found that Algorithm II almost achieves the same performance as Algorithm I in most cases. Our simulation results show that the proposed nonlinear joint precoding design significantly outperforms the linear joint precoding design. It is also shown that the choice between the proposed nonlinear source precoding design and the linear relay precoding design is dependent on specific conditions. [ABSTRACT FROM PUBLISHER]

For a low-mobile Poisson bipolar network and under line-of-sight/non-line-of-sight (LOS/NLOS) path-loss model, we study repetitive retransmissions (RR) and blocked incremental redundancy (B-IR). We consider spatially-coded multiple-input multiple-output (MIMO) zero-forcing beamforming (ZFBF) multiplexing system, whereby the packet success reception is determined based on the aggregate data rate across spatial dimensions of the MIMO system. Characterization of retransmission performance in this low-mobile configuration is practically important, but inherently complex due to a substantial rate correlation across retransmissions and intractability of evaluating the probability density function of aggregate data rate. Adopting tools of stochastic geometry, we first characterize the rate correlation coefficient (RCC) for both schemes. Our results show that, compared to the RR scheme, the B-IR scheme has higher RCC while its coverage probability is substantially larger. We demonstrate that the spotted contention between coverage probability and RCC causes the mean transmission delay (MTD) of B-IR to become either smaller or larger than the MTD of the RR scheme. Finally, we develop a numerical approximation of MTD, and evaluate the effective spatial throughput (EST), which is reciprocal to MTD, of the RR and B-IR schemes. Our numerical results highlight fundamental tradeoffs between densification, multiplexing gain, block length, and activity factor of nodes. We further observe that for dense networks: first, LOS component is considerably instrumental to enhance EST; second, EST of the B-IR scheme can be much higher than that of the RR scheme; third, when Doppler spread exists, it can improve MTD of B-IR, whereas it does not cast any meaningful effect on MTD of RR. [ABSTRACT FROM AUTHOR]

According to Bluetooth specifications, communications between slave devices within a piconet are controlled by its master node. In other words, a master node has to be involved in all packet exchange activities in its associated piconet. Consequently, how to determine the polling sequence and how to estimate service time for individual slave nodes are two critical intrapiconet missions to a master and are usually categorized as the intrapiconet polling and scheduling problem. Obviously, a good polling sequence can reduce the average packet delay, whereas accurate service time estimation would result in better throughput performance. Furthermore, the packet delay of intrapiconet transmission is mostly caused by the inadequate behavior in which the master node polls an idle slave since other nonidle slaves belonging to the same piconet have to wait for the completion of such POLL/NULL packet transmissions. Certainly, unnecessary pollings would cause bandwidth utilization reduction as well. Therefore, the adaptability to traffic pattern is a necessary condition to a good intrapiconet polling and scheduling algorithm. In this paper, we proposed a traffic-aware algorithm to deal with the polling and scheduling issue within a piconet. The objective of our work is to maximize the throughput performance and to reduce the average intrapiconet packet delay as simultaneously as possible. As expected, the simulation results verify that our work designs an intrapiconet scheduling scheme with low delay and high throughput, which is adaptive to various traffic scenarios as well. [ABSTRACT FROM AUTHOR]

In this paper, we consider the joint power allocation and base station (BS) assignment in nonorthogonal downlink transmission code-division multiple-access (CDMA) communication systems. In addition to the popular sum-power criterion, we introduce three novel criteria that better take into account the network requirements and particularly the separate power limit of each of the BSs. In our model, we allow each user to be connected to more than one BS and show that such a scheme can improve the system capacity (while currently this mechanism is only used to support soft handoff). Nevertheless, we show that in any optimal solution, the actual number of connections used by each user is small. We propose a unified approach to optimization, which allows the use of linear programming (LP)-based iterative algorithms to solve all of the presented optimization problems. The proposed scheme is verified by simulations for several scenarios. The simulation results show that by taking into account the power constraints of each of the BSs, the system capacity can be increased by up to 33%. The results can also approximate the performance of orthogonal CDMA networks with precision that increases with system bandwidth. [ABSTRACT FROM AUTHOR]

An iterative receiver for a multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) system is considered to jointly decode the transmitted bits and estimate the channel state. The receiver consists of a list detector, a turbo decoder, and a channel estimator that is based on the space-alternating generalized expectation-maximization (SAGE) algorithm. This paper proposes a way to improve the convergence of the iterative detection and decoding by using a priori information to also recalculate the candidate list, aside from the log-likelihood ratios (LLRs) of the coded bits. A new list parallel interference cancellation (PlC) detector is derived to approximate an a posteriori probability (APP) algorithm with reduced complexity and minimal losses of performance. Further- more, the organization of spectrally efficient decision-directed (DD) SAGE channel estimation under a constrained number of detector-decoder iterations is optimized by computer simulations, and the SAGE algorithm itself is modified for nonconstant envelope constellations. The list recalculation is shown to improve convergence. It is also shown that the list PlC detector with good initialization outperforms the K-best list sphere detector (LSD) in the case of small list sizes, whereas the complexities of the algorithms are of the same order. Despite the low preamble density and fast-fading channel, the proposed iterative receiver shows robust performance. [ABSTRACT FROM AUTHOR]

In recent years, wireless location estimation has attracted a significant amount of attention in different areas. Various types of radio signals are applied for the development of location-estimation algorithms. In this paper, the range measurements acquired from the received time-based information are adopted, and the modified least square (LS) method is utilized to process the raw data and to finally locate the target object. Practical issues, such as the nonline-of-sight (NLOS) errors and the geometric dilution of precision (GDOP) effect, are of concern. The NLOS error will cause a large nonnegative bias while measuring the propagation delay, which will lead to an unreliable result for location estimation. On the other hand, a large GDOP value corresponds to a poor geometric topology, which will result in inferior performance by adopting most of the existing location algorithms. The proposed location-estimation algorithms with virtual base stations (VBSs) will both mitigate the influence from the NLOS errors by imposing the geometric constraints and reduce the GDOP effect by incorporating the assisted VBSs. Two iterative schemes are proposed, including the center-of-gravity-based VBS (VBS-CG) and the minimal GDOP-based VBS (VBS-MG) algorithms, to determine the required number and the locations of the assisted VBSs. The proposed VBS algorithms are compared with other existing location-estimation schemes via simulations. The performance of the VBS-MG algorithm is observed to outperform the other schemes, particularly under the environments with larger NLOS errors and poor geometric layouts. [ABSTRACT FROM AUTHOR]

In this paper, we investigate efficient wireless data access algorithms in mobile hotspots. We introduce a proxy cache (PC) and propose PC-based poll-each-read (P-PER) and PC-based callback (P-CB) data access algorithms to reduce the transmission cost over wireless links in mobile hotspots. An analytical model is developed, and extensive simulations are conducted to demonstrate the performance of P-PER and P-CB. It is shown that P-PER and P-CB can improve cache hit performance and significantly reduce transmission cost. A tradeoff between P-PER and P-CB suggests the need to use a hybrid proxy-based approach to attain optimal performance of wireless data access in mobile hotspots. [ABSTRACT FROM AUTHOR]

Communication receivers that utilize I/Q downconversion are troubled by amplitude and phase mismatches between the analog I and Q branches. These mismatches are unavoidable in practice and reduce the obtainable image frequency attenuation to the 20-40-dB range in practical receivers. In wideband multi-channel receivers, where the overall bandwidths are in the range of several megahertz and the incoming carriers located at each other's mirror frequencies have a high dynamic range, the image attenuation of the analog front-end (FE) alone is clearly insufficient. In this paper, two novel blind low-complexity I/Q imbalance compensation techniques are proposed and analyzed to digitally enhance the analog FE image attenuation in wideband direct-conversion receivers. The proposed algorithms are grounded on the concept of circular or proper complex random signals, and they are, by design, able to handle the often overlooked yet increasingly important case of frequency-dependent I/Q mismatches. The first technique is an iterative one, stemming from adaptive filtering principles, whereas the second one is a moment-estimation-based block method. The performance of the algorithms is evaluated through computer simulations, as well as real-world laboratory signal measurement examples in practical multicarrier receiver cases. Based on the obtained results, the proposed compensation techniques can provide very good compensation performance with low computational resources and are robust in the face of different imbalance levels and dynamics of the received signals, as well as many other crucial practical aspects such as the effects of the communications channel and carrier synchronization. [ABSTRACT FROM AUTHOR]

In fast-varying channels, an orthogonal frequency-division multiplexing system needs to insert denser pilot symbols among transmitted symbols in tracking the variation of a channel. However, using denser pilot symbols reduces transmission throughput. In this paper, we propose a pseudopilot algorithm for data detection in fast-varying channels without increasing the pilot density. Our algorithm is based on a regressional model-based least-squares-fitting approach. Within a block of received symbols, we select some data symbols and regard them as pseudopilot symbols. The receiver considers all the possible patterns of the pseudopilots and associates each of them with a data sequence and a corresponding metric. The associated data sequence, whose metric is minimum, is selected as the detected data sequence. Our algorithm is not based on a decision-directed or decision-feedback architecture because the pseudopilots do not come from any detected symbols. The proposed algorithm needs to search all the possible patterns of the pseudopilots, and the complexity may increase with the number of pseudopilots and constellation size. To reduce the number of search, we further propose two modified approaches. The simulation results show that the performance of the proposed algorithms could approach a bit-error probability lower bound that is obtained by letting the receiver know the true values of the pseudopilots. Compared with the linear interpolation method, the proposed algorithm shows obvious improvement in fast-varying channels. The proposed modified approaches could also effectively reduce the number of search while maintaining the performance. We also give the complexity analysis of the proposed algorithm and an approach to determine the degree of the regression polynomial. [ABSTRACT FROM AUTHOR]

In this paper, a second stage for algorithms applying iterative soft decision interference cancellation (ISDIC) for channel equalization is proposed, which performs error search and correction. Analysis by simulations shows that matched filter (MF)-based ISDIC (MF ISDIC) with subsequent second stage can outperform more complex minimum-mean-square-error (MMSE) based ISDIC. Furthermore, the latter can be improved by the proposed second stage by up to 2 dB. It is shown that the ISDIC schemes with subsequent second stage can reach the MF bound up to a fraction of a decibel for all analyzed channels and 4-ary quadrature amplitude modulation (QAM) transmission, and up to 1 dB for 16-ary QAM transmission. In the work of Gerstacker et al., it has been reported that MF ISDIC performs very well for highly dispersive channels, e.g., with 60 symbol-spaced taps, but for channels of moderate dispersion, an error floor occurs. By utilizing performance bounds for delayed decision-feedback sequence estimation (DDFSE), we show that now for channels of moderate length, e.g., 20 symbol-spaced taps, even low-complexity MF ISDIC with the proposed subsequent second stage outperforms a DDFSE approach with 230 = 1 073 741 824 states. [ABSTRACT FROM AUTHOR]