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In a cellular wireless system, users located at cell edges often suffer significant out-of-cell interference. Assuming each base station is equipped with multiple antennas, we can model this scenario as a multiple-input single-output (MISO) interference channel. In this paper we consider a coordinated beamforming approach whereby multiple base stations jointly optimize their downlink beamforming vectors in order to simultaneously improve the data rates of a given group of cell edge users. Assuming perfect channel knowledge, we formulate this problem as the maximization of a system utility (which balances user fairness and average user rates), subject to individual power constraints at each base station. We show that, for the single-carrier case and when the number of antennas at each base station is at least two, the optimal coordinated beamforming problem is NP-hard for both the harmonic mean utility and the proportional fairness utility. For general utilities, we propose a cyclic coordinate descent algorithm, which enables each transmitter to update its beamformer locally with limited information exchange and establish its global convergence to a stationary point. We illustrate its effectiveness in computer simulations by using the space matched beamformer as the benchmark. [ABSTRACT FROM AUTHOR]

In this paper, we study joint performance optimization on network lifetime and video distortion for an energy-constrained wireless video sensor network (WVSN). To seek an appropriate tradeoff between maximum network lifetime and minimum video distortion, a framework for joint source/channel rate adaptation is proposed, where the video encoding rate, link rate, and power consumption are jointly considered, formulating a weighted convex optimization problem. In the context of lossy wireless channels, an efficient error control scheme that couples network coding and multipath routing is explored. Moreover, an integrated power consumption model, including power dissipation on video compression, error control, and data communication, is specifically developed for the video sensor node. By primal decomposition, the original problem is decomposed into a two-level optimization procedure, with the high-level procedure for source adaptation (source rate optimization) and the low-level procedure for channel adaptation (network resource allocation). Finally, a fully decentralized iterative algorithm is developed to resolve the target optimization problem. Extensive simulation results evaluate the convergence performance of the proposed algorithm and demonstrate the best tradeoff performance. [ABSTRACT FROM PUBLISHER]

Reducing power consumption of wireless networks has become a major goal in designing modern multimedia wireless systems. In an effort to reduce power consumption, this paper addresses the issue of scheduling real-time messages in multimedia wireless networks subject to both timing and power constraints. A power-consumption model is introduced to calculate power-consumption rates in accordance with message-transmission rates. Next, a new message-scheduling scheme called Power-aware Real-time Message (PARM) is developed to generate message-transmission schedules that minimize power consumption of multimedia wireless-network interfaces and the probability of missing deadlines for real-time messages. With a power-aware scheduling policy in place, the proposed PARM scheme is very energy-efficient. Experimental results based on a wide variety of synthetic workloads and eight real-world applications show that PARM significantly reduces energy dissipation while maintaining low missed rates. PARM reduces power consumption of data transmissions by up to 99.4% (with an average of 86.7%) for synthetic network traffic and saves energy by up to 60.0% (with an average of 34.1%) in the eight real-world applications. [ABSTRACT FROM AUTHOR]

This correspondence paper focuses on multicriterion combinatorial models in the “last-mile” problem for selection of user's connections. The following models are considered: 1) multicriterion ranking; 2) knapsack-like problems (e.g., multicriterion multiple-choice problem); 3) clustering; and 4) hierarchical morphological synthesis based on morphological clique problem. The last-mile problem is examined from the following viewpoints: 1) user(s); 2) provider(s) (i.e., communication service provider); and 3) users and providers. The following problems are described: 1) selection of the best connection for user; 2) selection of the best connections from several providers; 3) multistage selection of the best connections for user; 4) clustering of users; and 5) design of hierarchical connection system from provider. Numerical examples illustrate some applications. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an anonymous batch authenticated and key agreement (ABAKA) scheme to authenticate multiple requests sent from different vehicles and establish different session keys for different vehicles at the same time. In vehicular ad hoc networks (VANETs), the speed of a vehicle is changed from 10 to 40 m/s (36–144 km/h); therefore, the need for efficient authentication is inevitable. Compared with the current key agreement scheme, ABAKA can efficiently authenticate multiple requests by one verification operation and negotiate a session key with each vehicle by one broadcast message. Elliptic curve cryptography is adopted to reduce the verification delay and transmission overhead. The security of ABAKA is based on the elliptic curve discrete logarithm problem, which is an unsolved NP-complete problem. To deal with the invalid request problem, which may cause the batch verification fail, a detection algorithm has been proposed. Moreover, we demonstrate the efficiency merits of ABAKA through performance evaluations in terms of verification delay, transmission overhead, and cost for rebatch verifications, respectively. Simulation results show that both the message delay and message loss rate of ABAKA are less than that of the existing elliptic curve digital signature algorithm (ECDSA)-based scheme. [ABSTRACT FROM PUBLISHER]

Collaborative spectrum sensing (CSS) between secondary users (SUs) in cognitive networks exhibits an inherent tradeoff between minimizing the probability of missing the detection of the primary user (PU) and maintaining a reasonable false alarm probability (e.g., for maintaining good spectrum utilization). In this paper, we study the impact of this tradeoff on the network structure and the cooperative incentives of the SUs that seek to cooperate to improve their detection performance. We model the CSS problem as a nontransferable coalitional game, and we propose distributed algorithms for coalition formation (CF). First, we construct a distributed CF algorithm that allows the SUs to self-organize into disjoint coalitions while accounting for the CSS tradeoff. Then, the CF algorithm is complemented with a coalitional voting game to enable distributed CF with detection probability (CF-PD) guarantees when required by the PU. The CF-PD algorithm allows the SUs to form minimal winning coalitions (MWCs), i.e., coalitions that achieve the target detection probability with minimal costs. For both algorithms, we study and prove various properties pertaining to network structure, adaptation to mobility, and stability. Simulation results show that CF reduces the average probability of miss per SU up to 88.45%, relative to the noncooperative case, while maintaining a desired false alarm. For CF-PD, the results show that up to 87.25% of the SUs achieve the required detection probability through MWCs. [ABSTRACT FROM PUBLISHER]

Interference alignment (IA) is a transmission technique for exploiting all available degrees of freedom in the frequency- or time-selective interference channel with an arbitrary number of users. Most prior work on IA, however, neglects interference from other nodes in the network that are not participating in the alignment operation. This paper proposes three generalizations of IA for the multiple-antenna interference channel with multiple users that account for colored noise, which models uncoordinated interference. First, a minimum interference-plus-noise leakage (INL) algorithm is presented and shown to be equivalent to previous subspace methods when noise is spatially white or negligible. This algorithm results in orthonormal precoders that are desirable for practical implementation with limited feedback. A joint minimum mean square error design that jointly optimizes the transmit precoders and receive spatial filters is then proposed, whereas previous designs neglect the receive spatial filter. Finally, a maximum signal-to-interference-plus-noise ratio (SINR) algorithm is developed and proven to converge, unlike previous maximum SINR algorithms. The sum throughput of these algorithms is simulated in the context of a network with uncoordinated cochannel interferers that are not participating in the alignment protocol. It is found that a network with cochannel interference can benefit from employing precoders that are designed to consider that interference, but in extreme cases, such as when only one receiver has a large amount of interference, ignoring that the cochannel interference is advantageous. [ABSTRACT FROM PUBLISHER]

Existing works on distributed consensus explore linear iterations based on reversible Markov chains, which contribute to the slow convergence of the algorithms. It has been observed that by overcoming the diffusive behavior of reversible chains, certain nonreversible chains lifted from reversible ones mix substantially faster than the original chains. In this paper, the idea of Markov chain lifting is studied to accelerate the convergence of distributed consensus, and two general pseudoalgorithms are presented. These pseudoalgorithms are then instantiated through a class of location-aided distributed averaging (LADA) algorithms for wireless networks, where nodes' coarse location information is used to construct nonreversible chains that facilitate distributed computing and cooperative processing. Our first LADA algorithm is designed for grid networks; for a k\times k grid network, it achieves an \epsilon -averaging time of O(k\log (\epsilon ^-1)). Based on this algorithm, in a wireless network with transmission range r, an \epsilon -averaging time of O(r^-1\log (\epsilon ^-1)) can be attained through a centralized algorithm. Subsequently, a distributed LADA algorithm is presented, achieving the same scaling law in averaging time as the centralized scheme in wireless networks for all r satisfying the connectivity requirement; the constructed chain also attains the optimal scaling law in terms of an important mixing metric, the fill time, in its class. Finally, a cluster-based LADA algorithm is proposed, which, requiring no central coordination, provides the additional benefit of reduced message complexity compared with the distributed LADA algorithm. [ABSTRACT FROM PUBLISHER]

A constantly available control channel facilitates control message exchange and spectrum coordination in cognitive radio (CR) ad hoc networks. When a dedicated control channel is unavailable, a control channel must be dynamically allocated in licensed channels and vacated for the presence of primary users (PUs). As a result, the establishment of such a control channel is a challenge. In this paper, an efficient recovery control channel (ERCC) design is proposed to address this challenge. This heuristic and distributed design approach is essentially based on the observed spectrum homogeneity in a neighborhood. By adaptively updating a list of channels commonly available to neighbors, each secondary user is able to efficiently establish new control channels among neighbors in response to PU activity changes. Therefore, a virtually “always on” control channel robust to PU activity can be realized by the proposed method. The contributions are summarized as follows: 1) The proposed method efficiently recovers control channels from PU activity changes and maintains network connectivity. 2) It extends the control channel coverage to facilitate broadcast and reduce control overhead and delay. 3) It minimizes the interference with PUs. Simulation results show that the proposed solution outperforms the classic group- and sequence-based solutions in the responsiveness to rapidly changing PU activity and the maintenance of connectivity. Furthermore, the increase in control channel coverage and the allocation of the highest quality channels to control channels can be well balanced with reliability and scalability in various network scenarios. [ABSTRACT FROM PUBLISHER]

In multihop ad hoc networks over 802.11, the real bandwidth-delay product (BDP) cannot reach a value as large as in wired networks due to contention through wireless shared channels. As a result, conventional congestion-control algorithms cause an overshooting window problem and result in poor throughput in ad hoc networks. In this paper, we split the real round-trip time (RTT) into two parts: 1) congestion RTT and 2) contention RTT. We reveal that the contention RTT has nothing to do with the BDP and that the BDP is determined by only the congestion RTT if a link with the worst contention status does not lead to link breakage. An inadequate use of contention RTT causes a Transmission Control Protocol (TCP) congestion window overshooting problem. We propose a novel mechanism called congestion window adaptation through contention detection, which provides a more accurate method of estimating the contention status. Based on this mechanism, we present a congestion window adaptation method to limit the window size from overshooting. Simulation results show that our proposed mechanism outperforms the conventional TCP and the enhanced mechanisms called TCP with contention control and TCP with a maximum window. [ABSTRACT FROM PUBLISHER]

Due to the uncertainty of transmission opportunities between mobile nodes, the routing of delay-tolerant networks (DTNs) exploits the mechanism of opportunistic forwarding. Efficient algorithms and policies for opportunistic forwarding are crucial for maximizing the message delivery probability while reducing the delivery cost. In this paper, we investigate the problem of energy-efficient opportunistic forwarding for DTNs. First, we model the message dissemination by introducing a continuoustime Markov framework. Based on this framework, we formulate the optimization problem of opportunistic forwarding, with the constraint of energy consumed by the message delivery for both two-hop and epidemic forwarding. Then, based on the solution of the optimization problem, we design different kinds of forwarding policies such as static and dynamic policies. Among these policies, we find that the threshold dynamic policy is optimal for both two-hop and epidemic forwarding. By simulation results, we show the accuracy of our continuous-time Markov analysis model. Furthermore, through extensive numerical results, we demonstrate that the performance of the threshold dynamic policy is the best among the static and continuous dynamic policies, and among the continuous dynamic policies, the negative-power policy provides relatively better performance. [ABSTRACT FROM PUBLISHER]

This paper presents a distributed, low-feedback, linear-precoding technique to completely cancel interference in the presence of colored Gaussian noise. The selection of the precoder is based only on locally available channel-state information (CSI) at the receiver. We consider the downlink of a cellular broadband wireless system where base stations and user equipment are assumed to have at least two antennas each, and users are scheduled based on fractional frequency reuse. We present a distributed algorithm that helps the interfering base station (BS) to simultaneously beamform to its own user while still minimizing the interference on the unintended user. Simulation results show that the proposed scheme considerably improves the performance of the cell-edge users while causing only a mild degradation in the performance of the in-cell users, thereby leading to an increase in the overall system throughput. [ABSTRACT FROM PUBLISHER]

Despite the widespread use of forward-error correcting (FEC) coding, most multiple-input–multiple-output (MIMO) blind channel-estimation techniques ignore its presence and instead make the simplifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In this paper, we exploit the iterative channel estimation based on a posteriori information for blind MIMO separation and decoding. Experiments show improvements that are achievable by exploiting the existence of coding structures and that our technique can approach the performance of a Bahl–Cocke–Jelinek–Raviv (BCJR) equalizer with perfect channel-state information in a reasonable signal-to-noise ratio (SNR) range. In addition, by splitting the FEC codeword over multiple blocks, the impact in performance of a bad-conditioned channel matrix can be kept at a reasonable level. [ABSTRACT FROM PUBLISHER]

Distributed power control over interference limited network has received an increasing intensity of interest over the past few years. Distributed solutions (like the iterative water-filling, gradient projection, etc.) have been intensively investigated under quasi-static channels. However, as such distributed solutions involve iterative updating and explicit message passing, it is unrealistic to assume that the wireless channel remains unchanged during the iterations. Unfortunately, the behavior of those distributed solutions under time-varying channels is in general unknown. In this paper, we shall investigate the distributed scaled gradient projection algorithm (DSGPA) in a K pairs multicarrier interference network under a finite-state Markov channel (FSMC) model. We shall analyze the convergence property as well as tracking performance of the proposed DSGPA. Our analysis shows that the proposed DSGPA converges to a limit region rather than a single point under the FSMC model. We also show that the order of growth of the tracking errors is given by \cal O(1 / \barN), where \barN is the average sojourn time of the FSMC. Based on the analysis, we shall derive the tracking error optimal scaling matrices via Markov decision process modeling. We shall show that the tracking error optimal scaling matrices can be implemented distributively at each transmitter. The numerical results show the superior performance of the proposed DSGPA over three baseline schemes, such as the gradient projection algorithm with a constant stepsize. [ABSTRACT FROM PUBLISHER]

Resource discovery is an important process for finding suitable nodes that satisfy application requirements in large loosely coupled distributed systems. Besides internode heterogeneity, many of these systems also show a high degree of intranode dynamism, so that selecting nodes based only on their recently observed resource capacities can lead to poor deployment decisions resulting in application failures or migration overheads. However, most existing resource discovery mechanisms rely mainly on recent observations to achieve scalability in large systems. In this paper, we propose the notion of a resource bundle--a representative resource usage distribution for a group of nodes with similar resource usage patterns--that employs two complementary techniques to overcome the limitations of existing techniques: resource usage histograms to provide statistical guarantees for resource capacities and clustering-based resource aggregation to achieve scalability. Using trace-driven simulations and data analysis of a month-long PlanetLab trace, we show that resource bundles are able to provide high accuracy for statistical resource discovery, while achieving high scalability. We also show that resource bundles are ideally suited for identifying group-level characteristics (e.g., hot spots, total group capacity). To automatically parameterize the bundling algorithm, we present an adaptive algorithm that can detect online fluctuations in resource heterogeneity. [ABSTRACT FROM AUTHOR]

One of the major applications of wireless ad hoc networks is to extend the Internet coverage and support pervasive and efficient data dissemination and sharing. To reduce data access cost and delay, caching has been widely used as an important technique. The efficiency of data access in caching systems largely depends on the cost for maintaining cache consistency, which can be high in wireless ad hoc networks due to network dynamism. Therefore, to make better trade-off between cache consistency and the cost incurred, it would be highly desirable to provide users the flexibility in specifying consistency requirements for their applications. In this paper, we propose a general consistency model called Probabilistic Delta Consistency (PDC), which integrates the flexibility granted by existing consistency models, covering them as special cases. We also propose the Flexible Combination of Push and Pull (FCPP) algorithm which satisfies user-specified consistency requirements under the PDC model. The analytical model of FCPP is used to derive the balance of minimizing the consistency maintenance cost and ensuring the specified consistency requirement. Extensive simulations are conducted to evaluate whether FCPP can satisfy arbitrarily specified consistency requirements, and whether FCPP works cost-effectively in dynamic wireless ad hoc networks. The evaluation results show that FCPP can adaptively tune itself to satisfy various user-specified consistency requirements. Moreover, it can save the traffic cost by up to 50 percent and reduce the query delay by up to 40 percent, compared with the widely used Pull with TTR algorithm. [ABSTRACT FROM AUTHOR]

Node localization is essential to most applications of wireless sensor networks (WSNs). In this paper, we consider both range-based node localization and range-free node localization with uncertainties in range measurements, radio range, and anchor positions. First, a greedy optimization algorithm, named sequential greedy optimization (SGO) algorithm, is presented, which is more suitable for distributed optimization in networks than the classical nonlinear Gauss-Seidel algorithm. Then a unified optimization framework is proposed for both range-based localization and range-free localization, and two convex localization formulations are obtained based on semidefinite programming (SDP) relaxation techniques. By applying the SGO algorithm to the edge-based SDP relaxation formulation, we propose a second-order cone programming (SOCP)-based distributed node localization algorithm. Two distributed refinement algorithms are also proposed by using the SGO algorithm to nonconvex localization formulations. The proposed localization algorithms all can be implemented partially asynchronously in networks. Finally, extensive simulations are conducted to demonstrate the efficiency and accuracy of the proposed distributed localization algorithms. [ABSTRACT FROM AUTHOR]

Wireless networks are vulnerable to identity-based attacks, including spoofing and Sybil attacks, which allows for many other forms of attacks on the networks. Although the identity of a node can be verified through cryptographic authentication, authentication is not always possible, because it requires key management and additional infrastructural overhead. In this paper, we propose a method for detecting both spoofing and Sybil attacks by using the same set of techniques. We first propose a generalized attack-detection model that utilizes the spatial correlation of received signal strength (RSS) inherited from wireless nodes. We further provide a theoretical analysis of our approach. We then derive the test statistics for detection of identity-based attacks by using the K-means algorithm. Our attack detector is robust when handling the situations of attackers that use different transmission power levels to attack the detection scheme. We further describe how we integrated our attack detector into a real-time indoor localization system, which can also localize the positions of the attackers. We show that the positions of the attackers can be localized using either area- or point-based localization algorithms with the same relative errors as in the normal case. We further evaluated our methods through experimentation in two real office buildings using both an IEEE 802.11 (WiFi) network and an IEEE 802.15.4 (ZigBee) network. Our results show that it is possible to detect wireless identity-based attacks with both a high detection rate and a low false-positive rate, thereby providing strong evidence of the effectiveness of the attack detector utilizing the spatial correlation of RSS and the attack localizer. [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]

Sums of lognormal random variables (RVs) are of wide interest in wireless communications and other areas of science and engineering. Since the distribution of lognormal sums is not log-normal and does not have a closed-form analytical expression, many approximations and bounds have been developed. This paper develops two computational methods for the moment generating function (MGF) or the characteristic function (CHF) of a single lognormal RV. The first method uses classical complex integration techniques based on steepest-descent integration. The saddle point of the integrand is explicitly expressed by the Lambert function. The steepest-descent (optimal) contour and two closely-related closed-form contours are derived. A simple integration rule (e.g., the midpoint rule) along any of these contours computes the MGF/CHF with high accuracy. The second approach uses a variation on the trapezoidal rule due to Ooura and Mori. Importantly, the cumulative distribution function of lognormal sums is derived as an alternating series and convergence acceleration via the Epsilon algorithm is used to reduce, in some cases, the computational load by a factor of 106! Overall, accuracy levels of 13 to 15 significant digits are readily achievable. [ABSTRACT FROM AUTHOR]

In wireless communication systems, all in-phase and quadrature-phase (I/Q) signal processing receivers face the problem of I/Q imbalance. In this paper, we investigate the effect of I/Q imbalance on the performance of multiple-input multiple-output (MIMO) maximal ratio combining (MRC) systems that perform the combining at the radio frequency (RF) level, thereby requiring only one RF chain. In order to perform the MIMO MRC, we propose a channel estimation algorithm that accounts for the I/Q imbalance. Moreover, a compensation algorithm for the I/Q imbalance in MIMO MRC systems is proposed, which first employs the least-squares (LS) rule to estimate the coefficients of the channel gain matrix, beamforming and combining weight vectors, and parameters of I/Q imbalance jointly, and then makes use of the received signal together with its conjugation to detect the transmitted signal. The performance of the MIMO MRC system under study is evaluated in terms of average symbol error probability (SEP), outage probability and ergodic capacity, which are derived considering transmission over Rayleigh fading channels. Numerical results are provided and show that the proposed compensation algorithm can efficiently mitigate the effect of I/Q imbalance. [ABSTRACT FROM AUTHOR]

When an IEEE 802.11 ad hoc network achieves a capacity C using a single channel, the targeted capacity using two channels should be 2 · C. We believe that this should be used as the benchmark for capacity comparisons for multichannel schemes. However, most of the dual-channel 802.11 protocols proposed in the literature appear to achieve less than 60% of the 2 · C targeted capacity. In previous work, we proposed a link-directionality-based dual-channel medium-access-control (MAC) protocol (DCP) to boost the network capacities by up to 78% of our targeted capacities, i.e., 78% x 2 · C = 1.56 · C. However, the DCP still fails to reach the 2 · C capacity target due to the overheads incurred by the protocol. In this paper, we implement a signal-to-interference ratio (SIR) comparison algorithm (SCA) on top of the DCP in an attempt to further improve network capacity. This algorithm incurs relatively small overheads and can further relax the protocol constraints that are imposed by the virtual carrier-sensing mechanism. Interestingly, while the capacity of the pure DCP decreases when link lengths are short, the capacity of the pure SCA increases when link lengths are short. The two algorithms compensate for the downside of each other to bring about a more uniform capacity improvement. Simulations show that the proposed scheme [described as DCP with SCA (DCPwSCA)] can increase the network throughputs by 430% in lattice topologies and 213% in random topologies. [ABSTRACT FROM AUTHOR]

Current wireless access networks are able to provide relatively low data rates when compared with wired access. To extend the access to high-data-rate services to wireless users, the International Telecommunication Union (ITU) established new requirements for future wireless communication technologies of up to 100 Mb/s under high-mobility conditions and 1 Gb/s in low mobility. The low mobility goal can only be achieved through the use of highly optimized local area access networks operating at low range and low transmission power. The efficient sharing of radio resources among local area cells will be very difficult to achieve with a traditional network planning/dimensioning approach due to their intrinsic uncoordinated deployment characteristic. Cognitive radio (CR)-based networking methodologies are considered as the most promising solutions for such radio-resource-sharing problems, also enabling unlicensed/open spectrum operations. In this paper, a game-theory-inspired scalable algorithm for intercell dynamic spectrum access (IC-DSA) is introduced to enable distributed resource allocation in CR environments. Here, the new CR-based cell is called "cognitive cell (C-cell)," and it is the minimal entity that allocates a resource set. The simulation results demonstrate the effectiveness of the proposed spectrum-sharing approach. This solution achieves a better overall performance in several load and interference scenarios in terms of both outage and average capacity when compared with fixed-frequency-reuse cases. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have been proposed for facilitating various monitoring applications (e.g., environmental monitoring and military surveillance) over a wide geographical region. In these applications, spatial queries that collect data from wireless sensor networks play an important role. One such query is the K-Nearest Neighbor (KNN) query that facilitates collection of sensor data samples based on a given query location and the number of samples specified (i.e., K). Recently, itinerary-based KNN query processing techniques, which propagate queries and collect data along a predetermined itinerary, have been developed. Prior studies demonstrate that itinerary-based KNN query processing algorithms are able to achieve better energy efficiency than other existing algorithms developed upon tree-based network infrastructures. However, how to derive itineraries for KNN query based on different performance requirements remains a challenging problem. In this paper, we propose a Parallel Concentric-circle Itinerary-based KNN (PCIKNN) query processing technique that derives different itineraries by optimizing either query latency or energy consumption. The performance of PCIKNN is analyzed mathematically and evaluated through extensive experiments. Experimental results show that PCIKNN outperforms the state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

In this paper, we consider cross-layer optimization in wireless networks with wireless broadcast advantage, focusing on the problem of distributed scheduling of broadcast links. The wireless broadcast advantage is most useful in multicast scenarios. As such, we include network coding in our design to exploit the throughput gain brought in by network coding for multicasting. We derive a subgradient algorithm for joint rate control, network coding and scheduling, which however requires centralized link scheduling. Under the primary interference model, link scheduling problem is equivalent to a maximum weighted hypergraph matching problem that is NP-complete. To solve the scheduling problem distributedly, locally greedy and randomized approximation algorithms are proposed and shown to have bounded worst-case performance. With random network coding, we obtain a fully distributed cross-layer design. Numerical results show promising throughput gain using the proposed algorithms, and surprisingly, in some cases even with less complexity than cross-layer design without broadcast advantage. [ABSTRACT FROM AUTHOR]

In this paper, we present a new approach to noise suppression for power-line communications based on orthogonal frequency-division multiplexing (OFDM). Previous work for wireless systems has suggested that augmentation of OFDM using spreading codes prior to modulation offers some narrowband interference (NBI) resistant capabilities. We present a study of the performance of such a system for power-line networks-well known to be affected by such noise. Termed interference suppression OFDM (IS-OFDM) and its counterpart NBI avoidance (NBIA), we also present a further modification of these techniques in order to improve NBI suppression performance. The proposed algorithm, orthogonal narrowband interference avoidance (ONBIA), avoids narrowband interference on contaminated subcarriers while preserving the orthogonality of the spreading code. Both theoretical analysis and simulation results demonstrate the improvements of ONBIA over the standard IS-OFDM and NBIA methods across a wide range of interference-to-signal ratios (ISR). [ABSTRACT FROM AUTHOR]

The error performance of different types of receivers over an arbitrarily correlated Rician fading MIMO channel is assessed by evaluating the decision metric and the pairwise error probability. The differences are in the way channel state information at the receiver (CSIR) is recovered. We consider: i) a genie-aided receiver, based on the perfect knowledge of CSIR; ii) a mismatched receiver, based on the use of pilot-aided (imperfect) CSIR in the perfect-CSIR decision metric; iii) an optimum receiver, based on perfect channel distribution information at the receiver (CDIR), which performs jointly channel and data estimation. In this paper, the decision metric of the optimum receiver is derived, and an iterative algorithm is proposed to calculate it for sequential decoding schemes. The complexity of this iterative algorithm is analyzed and compare against the complexity of the mismatched receiver. Closed-form expressions are given for the pairwise error probabilities (PEPs) of the three receivers with arbitrarily correlated Rician fading. These expressions are further processed to obtain the asymptotic (in the SNR) PEPs, the diversity order, and the asymptotic power losses. Numerical results are presented to support the validity of this analysis and to assess the impact of power efficiency and CDIR estimation errors on the PEP versus the εb/N0 ratio. [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]

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]

Multiple antenna orthogonal frequency division multiple access (OFDMA) is a promising technique for the high downlink capacity in the next generation wireless systems, in which adaptive resource allocation would be an important research issue that can significantly improve the performance with guaranteed QoS for users. Moreover, most of the current resource allocation algorithms are limited to the unicast system. In this paper, dynamic resource allocation is studied for multiple antenna OFDMA based systems which provide multicast service. The performance of multicast system is simulated and compared with that of the unicast system. Numerical results also show that the proposed algorithms improve the system capacity significantly compared with the conventional scheme. [ABSTRACT FROM AUTHOR]

This paper addresses resource allocation for weighted sum throughput maximization (WSTM) in multicell orthogonal frequency-division multiple-access (OFDMA) networks. Two suboptimal algorithms with polynomial-time complexity are provided. First, we determine a graph-based subcarrier allocation algorithm allowing joint transmission of two interfering links whenever such a transmission fulfills the pairwise WSTM objective. An analytical expression of the optimal power allocation with two interfering cells in single-carrier transmission is obtained, and the capacity region study serves as the basis to build the interference graph. Second, we present a distributed power-control algorithm suitable for any signal-to-interferenceplus-noise ratio (SINR) regime. It rejects users and subcarriers with weighted SINR that is too low before operating in the high SINR regime for the remaining users and subcarriers. Both algorithms and their combination are assessed via dynamic simulations, where the weight of each user is proportional to its queue length. They are shown to significantly decrease resource consumption and efficiently balance users' queue lengths. [ABSTRACT FROM AUTHOR]

In cognitive radio networks (CRNs), knowledge of the position of the primary users (PUs) is important as it can be used to avoid harmful interference to the primary network while at the same time be exploited to improve the spectrum utilization. In this paper, a semi range-based localization algorithm is proposed for secondary users (SUs) in CRNs to estimate the positions of the PUs. The basic idea of the proposed algorithm is to take advantage of the estimated detection probabilities, which can be obtained from the binary detection indicators of the SUs, to estimate the distances between themselves and the PUs. Moreover, the accuracy of the proposed localization algorithm is further improved by introducing both a weighted least-squares method and an iterative procedure. The Cramer-Rao lower bound (CRLB) of the mean-square error (MSE) of the proposed localization estimator is also derived. A scenario with malicious users (MUs) is further considered, where the proposed method is modified to detect MUs. To illustrate the benefits of localization, we design a location-aware medium access control (MAC) protocol and show that significant throughput gains can be realized over conventional MAC protocols. [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]

Reconfigurability and low complexity are the two key requirements of finite impulse response (FIR) filters employed in multistandard wireless communication systems. In this paper, two new reconfigurable architectures of low complexity FIR filters are proposed, namely constant shifts method and programmable shifts method. The proposed FIR filter architecture is capable of operating for different word-length filter coefficients without any overhead in the hardware circuitry. We show that dynamically reconfigurable filters can be efficiently implemented by using common subexpression elimination algorithms. The proposed architectures have been implemented and tested Virtex 2v3000ff1152-4 field-programmable gate array and synthesized on 0.18 µm complementary metal-oxide-semiconductor technology with a precision of 16 bits. Design examples show that the proposed architectures offer good area and power reductions and speed improvement compared to the best existing reconfigurable FIR filter implementations in the literature. [ABSTRACT FROM AUTHOR]

Dynamic spectrum access (DSA), enabled by cognitive radio technologies, has become a promising approach to improve efficiency in spectrum utilization, and the spectrum auction is one important DSA approach, in which secondary users lease some unused bands from primary users. However, spectrum auctions are different from existing auctions studied by economists, because spectrum resources are interference-limited rather than quantity-limited, and it is possible to award one band to multiple secondary users with negligible mutual interference. To accommodate this special feature in wireless communications, in this paper, we present a novel multi-winner spectrum auction game not existing in auction literature. As secondary users may be selfish in nature and tend to be dishonest in pursuit of higher profits, we develop effective mechanisms to suppress their dishonest/collusive behaviors when secondary users distort their valuations about spectrum resources and interference relationships. Moreover, in order to make the proposed game scalable when the size of problem grows, the semi-definite programming (SDP) relaxation is applied to reduce the complexity significantly. Finally, simulation results are presented to evaluate the proposed auction mechanisms, and demonstrate the complexity reduction as well. [ABSTRACT FROM AUTHOR]

Recently, sensor network technologies are being applied to more places such as intelligent home, offices and universities. Localization algorithms are required for indoor wireless sensor network (WSN) applications because the identification of real positions can upgrade the importance of sensing information. In this paper, a sensor network, where small-sized, low-cost and low-rate sensors are uniformly deployed in an indoor WSN environment, is taken into account. We introduce efficient algorithms, termed multi- duolateration localization (MDL) and grouping multi- duolateration localization (GMDL), which can improve the accuracy of location identification by employing jumper setting. The MDL algorithm can estimate 2-dimensional coordinates with high accuracy by the acquisition of edge information from the setting. In addition, the GMDL algorithm can be applied to the estimation of 3-dimensional coordinates by the acquisition of edge and surface information from the setting. The proposed algorithms perform localization more accurately than trilateration and faster than multidimensional scaling (MDS). The results from a MATLAB simulation show the outperformance of the proposed algorithms and demonstrate the possibility of 3-dimensional localization. [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]

Directional antennas are preferred for efficient wireless communications in the 60-GHz spectrum. Recent efforts to adapt high-data-rate medium access control (MAC) protocols from standards that are designed for operation in the lower frequency bands face challenges in acquiring the location of nearby devices in a network. In this paper, we propose a cross-layer neighbor-discovery algorithm for directional 60-GHz networks to assist the MAC layer in efficiently using the directional antennas. We utilize linear and circular polarization and their different responses to reflection to synchronize the transmitter and the receiver. This difference in response is used to determine if there is a direct path between the transmitter and the receiver. Based on this knowledge, the direction of the neighboring devices is determined through a cyclic scanning. The proposed algorithm is analyzed based on the usage models defined in the standard for 60-GHz networks. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic priority resource-allocation (DPRA) scheme is proposed for uplinks in IEEE 802.16 wireless communication systems. The DPRA scheme dynamically gives priority values to four types of service traffic based on their urgency degrees and allocates system radio resources according to their priority values. It can maximize the system throughput and satisfy differentiated quality-of-service (QoS) requirements. Furthermore, the DPRA scheme performs consistent allocation for packets of users to conform to the uplink frame structure of IEEE 802.16, to fulfill the QoS requirement, and to reduce the computational complexity. Simulation results show that the proposed DPRA scheme performs very close to the optimal method, which is by exhaustive search in system throughput, and it outperforms the conventional efficient and fair scheduling (EFS) algorithm in the performance measures such as system throughput, real-time polling service (rtPS) packet dropping rate, ratio of unsatisfied non-real-time polling service (nrtPS), and average transmission rate of the best effort (BE) service. In addition, the DPRA scheme takes only 1/1000 and 1/10 the computational times of the optimal method and the conventional EFS algorithm, respectively, thus making it more feasible for real applications. [ABSTRACT FROM AUTHOR]

Network diversity multiple access protocols (NDMA) have been shown to considerably outperform previously proposed algorithms. However, several issues in their analysis remain unsolved, particularly under the assumption of imperfect collision-multiplicity detection in asymmetrical system configurations (i.e., configurations where the users have different channel and queuing statistics). To partially fill this gap, this paper presents a detailed study on stability, throughput and delay properties of asymmetrical nonblind NDMA protocols under such imperfect detection assumption. Additionally, the protocol formulation includes a carrier-sense mechanism which is found to improve system performance under finite-SNR environments and which can be useful in assessing the benefits of retransmission diversity on IEEE 802.11 wireless local area networks (WLANs). New expressions for the parameters and performance metrics of the NDMA protocol under different assumptions are here provided. These include the stability condition of a system without feedback to acknowledge correct packet reception and the derivation of the boundaries of the throughput region using a joint cross-layer optimization with respect to the probabilities of transmission and false alarm. Simulation results are used to further assess the performance of the protocol and to confirm the analytic results. [ABSTRACT FROM AUTHOR]

This paper studies the resource allocation problem for the relay-assisted orthogonal frequency-division multiple-access (OFDMA)-based multiuser system. A new transmission protocol, named hierarchical OFDMA, is proposed to support two-way communications between the base station (BS) and each mobile user (MU) with or without an assisting relay station (RS) in "relay" or "direct" mode, respectively. In particular, the recently discovered two-way relaying technology, based on the principle of network coding, is applied to MUs in relay mode with two possible relay-operations, namely, decode-and-forward (DF) and amplify-and-forward (AF). By applying convex optimization techniques, efficient algorithms are developed for optimal allocation of transmit resources such as power levels, bit rates, and OFDM subcarriers at the BS, RSs, and MUs. Simulation results show that substantial system throughput gains are achievable by the proposed two-way relaying and optimal resource allocation schemes over the traditional one-way relaying and fixed resource allocation schemes for relay-assisted OFDMA-based wireless networks. [ABSTRACT FROM AUTHOR]

This paper investigates the use of wireless sensor networks for estimating the location of an event that emits a signal that propagates over a large region. In this context, we assume that the sensors make binary observations and report the event (positive observations) if the measured signal at their location is above a threshold; otherwise, they remain silent (negative observations). Based on the sensor binary beliefs, a likelihood matrix is constructed whose maximum value points to the event location. The main contribution of this work is Subtract on Negative Add on Positive (SNAP), an estimation algorithm that provides an efficient way of constructing the likelihood matrix by simply adding ±1 contributions from the sensor nodes depending on their alarm state (positive or negative). This simple estimation procedure provides very accurate results and turns out to be fault tolerant even when a large percentage of the sensor nodes report erroneous observations. [ABSTRACT FROM AUTHOR]

When speech-based interfaces are used for small handheld devices such as cellular phones and personal digital assistants in mobile environments with unknown noises and surrounding talkers, all signals except the legitimate user's voice must be rejected as noise signals by the system. This paper proposes a new algorithm that detects the user's voice in spatial and temporal domains using directional and spectral information. It rejects undesirable signals that originate from noise sources or surrounding talkers. Experimental results indicate the proposed algorithm reduces the voice activity detection error rate by 34.3% relative to the conventional methods. [ABSTRACT FROM AUTHOR]

In this paper, a novel constellation extension algorithm, named as Peak-restricted Constellation Extension (PCE), is proposed for peak-to-average power ratio (PAPR) reduction in Orthogonal frequency division multiplexing (OFDM) system. This algorithm actively selects outer constellation points which contribute to the large peak magnitudes, and dynamically alter the amplitudes of these points to reduce PAPR. It does not require transmitting any side information to the receiver and there is no loss in data rate. As radio-over-fiber (ROF) network is proved to be one of the best solutions for the wireless-access technology, this algorithm is verified in an OFDM-ROF system. It is shown that this algorithm significantly reduces the PAPR of OFDM signals. The performances of the system with and without the algorithm are also compared. [ABSTRACT FROM AUTHOR]

A low complexity hierarchical quadrature amplitude modulation (QAM) symbol bits allocation algorithm for unequal error protection of video transmission over wireless channels is proposed in this paper. An unequal error protection (UEP) scheme using hierarchical QAM, which takes into consideration the non-uniformly distributed importance of intracoded frame (I-frame) and predictive coded frame (P-frame) in a group of pictures (GOP), is first proposed. In order to optimally allocate the hierarchical QAM's high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H.264/AVC video, a generic solution for optimal allocation of hierarchical QAM's high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H. 264/A VC video is then proposed. Finally, a low complexity symbol bits allocation algorithm, namely ranking search algorithm, which reduces the computational complexity of the proposed optimal symbol bits allocation algorithm, is proposed. Simulation results show that our proposed UEP scheme outperforms the classical equal error protection (EEP) scheme and also the previous UEP scheme. [ABSTRACT FROM AUTHOR]

This paper studies the performance of multiple-input multiple-output (MIMO) systems employing multichannel beam-forming in the presence of unequal power cochannel interference and noise. Our results apply to a wide class of multichannel systems which transmit on the eigenmodes of the MIMO channel, allowing for transmission on any arbitrary number of eigensubchannels, with possibly different modulation formats, and with possibly unequal powers. New exact expressions are derived for the symbol error rate (SER) of each eigensubchannel, the global SER, and the outage probability. We also present simplified closed-form expressions for the high SNR regime, and show that cochannel interference has no effect on the diversity order, but leads to a loss in array gain. Our results are based on new closed-form exact and asymptotic expressions which we derive for the marginal ordered eigenvalue distributions of a certain class of finite-dimensional complex random matrices. [ABSTRACT FROM AUTHOR]

Recently, lattice-reduction-aided detectors have been proposed for multiinput multioutput (MIMO) systems to achieve performance with full diversity like the maximum likelihood receiver. However, these lattice-reduction-aided detectors are based on the traditional Lenstra-Lenstra-Lovász (LLL) reduction algorithm that was originally introduced for reducing real lattice bases, in spite of the fact that the channel matrices are inherently complex-valued. In this paper, we introduce the complex LLL algorithm for direct application to reducing the basis of a complex lattice which is naturally defined by a complex-valued channel matrix. We derive an upper bound on proximity factors, which not only show the full diversity of complex LLL reduction-aided detectors, but also characterize the performance gap relative to the lattice decoder. Our analysis reveals that the complex LLL algorithm can reduce the complexity by nearly 50% compared to the traditional LLL algorithm, and this is confirmed by simulation. Interestingly, our simulation results suggest that the complex LLL algorithm has practically the same bit-error-rate performance as the traditional LLL algorithm, in spite of its lower complexity. [ABSTRACT FROM AUTHOR]

In this paper, we propose a resource allocation scheme to increase the effective capacity subject to the queue-overflow statistical Quality-of-Service (QoS) requirement for a multi-relay cooperative wireless network. Firstly, we consider the block fading channels and derive an algorithm in which each relay is allocated a time slot of optimal length during the cooperation phase, based on the channel statistics. Our analysis indicates that when the QoS requirement is loose, only the relay with the best average channel condition should be selected for cooperation. On the other hand, when the QoS requirement becomes more stringent, more relays should participate in cooperation. The asymptotic case when either the transmit power or the number of relays goes to infinity is discussed, and we shall reveal a tradeoff between the transmit power and the number of relays, given a target effective capacity. By modeling the channel correlation by a two-state Markov model, we will develop two sub-optimal time-slot allocation algorithms which can substantially increase the effective capacity compared with the opportunistic and equal allocation schemes. Our results will show that the channel correlation can sharply decrease the effective capacity and that applying the optimal time-slot allocation result obtained in block fading channels directly to correlated fading channels is no longer optimal. [ABSTRACT FROM AUTHOR]

In a MIMO multiple-access channel where users employ Space-Time Block Codes (STBC), interference cancellation can be used to suppress co-channel interference and recover the desired signal of each user at the receiver. Leveraging the special properties of Alamouti matrices, we first show that spatial multiplexing of Alamouti signals retains the space-time diversity gain of Alamouti signaling using our proposed low-complexity Alamouti BLAST-MMSE (A-BLAST) Algorithm. Next, in contrast to traditional transmit diversity that focuses on STBC construction at the transmitter, this paper looks at transmit diversity from the perspective of the receiver. In other words, the receiver gets to choose the STBC's, which are favourable to the channel assuming a fixed BLAST receive algorithm. In a multiuser MAC setting, we first present a systematic methodology to exploit different decomposition structure in Alamouti matrices, each with different tradeoff between performance and decoding complexity using possibly different MIMO receive algorithms. We then demonstrate that the notion of angles (the inner product of two quaternionic vectors) between multiuser channels determines the performance of MIMO receive algorithms. As an application of the general theory, we transform the decoding problem for several types of Quasi-Orthogonal STBC (QOSTBC) into multiuser detection of virtual Alamouti users. Building upon our A-BLAST Algorithm, we propose new algorithms for decoding single-user and multiuser QOSTBC. In particular, we show that bit error probability is a function of the quaternionic angle between virtual users (for a single user) or multiple users. This angle varies with the type of QOSTBC and leads to a new form of adaptive modulation called code diversity, where feedback instructs the transmitter how to choose from a plurality of codes. [ABSTRACT FROM AUTHOR]

Pilot-aided orthogonal frequency-division multiplex- ing (OFDM) channel estimation has, so far, been optimized only for open-loop systems for which the uniform spacing of pilots is optimal. In this paper, we examine closed-loop OFDM systems and show how uniform pilots may no longer be optimal. In doing so, we propose a feedback technique in which the pilot allocation mechanism is adapted to the mobile channel. After deriving a general expression for the symbol error rate as a function of pilot allocation, we optimize the pilot locations and propose two practical solutions using bounds on the objective function. We proceed to formulate pilot allocation based on the maximal average OFDM channel capacity. We examine the feedback over- head that is associated with our method and make comparisons with the conventional uniform framework. Finally, we suggest the use of vector quantization in the context of the generalized Lloyd algorithm to reduce feedback and extend our method to a multiple-input-multiple-output (MIMO)-OFDM system based on the Alamouti space-time block code. Monte-Carlo simulations illustrate the error-rate/capacity performance gains via nonuniform pilots and illustrate the effects of Doppler frequency and carrier frequency offset. [ABSTRACT FROM AUTHOR]