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This paper introduces a novel analytical model for analyzing the performance of handoff algorithms based on absolute and relative signal strength measurements. The performance is analyzed in multicell and multisector environments where cochannel interference (CCI) is present. The model presented in this paper accounts for the distinct features of intersector handoff compared with intercell handoff. Numerical results show that the performance metrics are affected by the CCI level. The occurrence condition of unnecessary handoffs in multisector systems is also presented. [ABSTRACT FROM AUTHOR]

This paper considers a scheduling problem for multi-user transmissions over the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling exploits the time-varying radio channel and improves network performance. This paper presents a new scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution, which is referred to as Throughput Constrained Opportunistic Scheduling (TCOS), offers better service differentiation among different classes of users than the existing opportunistic scheduling algorithms with only minimum performance constraints. For ideal memoryless fading channels, TCOS provides performance comparable with an existing scheme with minimum and maximum performance constraints. For realistic fading channels with memory, TCOS significantly improves system performance due to its ability to trade off feasibility with throughput. Extensive simulation results demonstrate the improved system performance and effective service differentiation of the proposed solution under realistic channel conditions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis framework for estimating spatio-temporal distortion associated with data-gathering algorithms in sensor networks. We assume that the underlying data field being sensed is spatially and temporally correlated and that the sink node performs real-time reconstruction of the field. Unlike existing work, the proposed analysis framework assumes realistic transmission schemes and network/routing parameters, such as congestion and limited transmission range. Our simulations show that, even for a simple collision-free transmission scheme and regular deployment patterns, the distortion analyses yield starkly different results, compared with the analyses performed in the absence of these assumptions. The analytical method presented in this paper could easily be extended to consider the real-time data-reconstruction problem under different transmission schemes, node distributions, and reconstruction methods. [ABSTRACT FROM AUTHOR]

In this paper, the authors study the performance of scheduling algorithms exploiting the multiuser selection diversity. Schedulers with affordable-rate transmission and adaptive transmission based on the absolute signal-to-noise ratio (SNR) and the normalized SNR are considered. In contrast to previous studies on the multiuser-diversity systems, the channel dynamics is taken into consideration in this paper by a novel formulation based on the level crossing analysis of stochastic processes. Then, the authors make the connection between the Doppler frequency shift, which indicates the channel temporal correlation, and the average (channel) access time, the average waiting time (AWT) between accesses, and the average access rate (AAR) of active users. These properties are important for the scheduler design, especially for applications where delay is a concern. In addition, analytical expressions for the system throughput and the degree of fairness (DOF) when users have nonidentical average channel conditions are presented. These expressions quantify the effect of disparateness in users' average channel conditions on the system performance. [ABSTRACT FROM AUTHOR]

Reverse link capacity of a direct-sequence code-division multiple-access (DS-CDMA) system in a multicell environment has been studied recently, and significant capacity improvements due to the use of beamforming have been observed. However, system performance with beamforming will be affected by several impairments, such as direction of arrival estimation errors, array perturbations, mutual coupling, and signal spatial spreads. In this paper, reverse link performance of CDMA systems with beamforming under these impairments (imperfect beamforming) is investigated. A simplified beamforming model is developed to evaluate the system performance in terms of user capacity, bit-error rates (BER), and outage probabilities. Both signal-to-interference-ratio-based power control and strength-based power control are considered in this paper. The capacity and BER degradations due to different impairments are shown, and outage probabilities under different power control schemes are examined. [ABSTRACT FROM AUTHOR]

The location information of sensor nodes in wireless sensor networks is crucial for various applications such as emergency rescue operations, environmental monitoring, home automation, and traffic control. In this paper, a new method to improve the anchor location accuracy in wireless sensor networks is proposed based on fusion of Global Positioning System (GPS) measurements and anchor-to-anchor parameter estimates. Novel algorithms are derived to increase the accuracy of anchor locations using both anchor-to-anchor distance and angle-of-arrival (AOA) estimates for both line-of-sight (LOS) and non-LOS (NLOS) scenarios. When using anchor-to-anchor distance estimates in LOS conditions, an optimization-based algorithm is developed. The Cramer-Rao lower bound (CRLB) is derived to benchmark positioning accuracy in 3-D environments with both GPS measurements and anchor-to-anchor parameter estimates, which has not been studied in the literature. Simulation results demonstrate that the proposed algorithms can substantially improve anchor position accuracy, and the performance of the proposed algorithms approaches the CRLB. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSNs), the field information (e.g., temperature, humidity, airflow) is acquired via several battery-equipped wireless sensors and is relayed toward a sink node. As the size of the WSNs increases, it becomes inefficient (in terms of power consumption) when gathering all information in a. single sink. To tackle this problem, one can increase the number of sinks. The set of sensor nodes that are sending data to sink k is called commodity k. In this paper, we formulate the lexicographically optimal commodity lifetime (LOCL) routing problem. A stepwise centralized algorithm called the LOCL algorithm is proposed, which can obtain the optimal routing solution and lead to lexicographical fairness among commodity lifetimes. We then show that, under certain assumptions, the lexicographical optimality among commodity lifetimes can be achieved by providing lexicographical optimality among node lifetimes. This motivates us to propose our second algorithm, which is called the lexicographically optimal node lifetime (LONL) algorithm, which is suitable for practical implementation. Simulation results show that our proposed LOCL and LONL algorithms increase the normalized commodity and node lifetimes compared with the maximum lifetime with multiple sinks (MLMS) and lexicographical max-min fair (LMM) routing algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a channel-driven rate and power adaptation (CDRPA) algorithm is proposed for wireless local area networks (WLANs) in generalized Nakagami fading channels. Through the channel information of the first packet, the CDRPA algorithm can lower the complexity of comparing various rates and power levels. In the case of the IEEE 802.11 WLAN, the computation complexity of the CDRPA algorithms is reduced by more than 94% compared with the complete-search link adaptation. A physical and/or medium access control (MAC) cross-layer analytical model is also developed to evaluate the goodput and energy efficiency of the carrier sense multiple access with a collision avoidance MAC protocol in Nakagami fading channels. Our numerical results show that the CDRPA algorithm is not only more energy efficient in the Nakagami fading channel but can also achieve comparable and even higher throughput compared with the complete-search link adaptation approach. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) can be used to monitor the interested region using multihop communication. Coverage is a primary metric to evaluate the capacity of monitoring. Connectivity also needs to be guaranteed so that the sink node receives all sensed data for future processing. In this paper, we study the m-coverage and n-connectivity problem under border effects. We consider the scenario where the heterogeneous sensor nodes are randomly distributed in a circular region. We first exactly derive the network m-coverage ratio that is provided by N sensor nodes by the mathematical formulas. Then, the lower bound of the network n-connectivity probability is also derived. Since sensor nodes are equipped with energy-limited batteries, energy conservation in such networks is of paramount importance to prolong the lifetime of the network. Accordingly, we propose a location-independent, energy-efficient routing algorithm EECCR, which simultaneously preserves the network m-coverage ratio and the sensor n-connectivity probability. Extensive simulation results are provided to demonstrate that our algorithm is correct and effective. [ABSTRACT FROM AUTHOR]

Although power control has been explored since the early 1990s, there still remains the need for further research. Most of the algorithms so far consider either the problem of minimizing the sum of transmitted power under quality of service (QoS) constraints given in terms of minimum signal-to-interference-plus-noise ratio (SINR) in a static channel or the problem of mitigating fast fading in a single dynamic link. In this paper, we suggest a new approach to the power control by treating the QoS requirement as another objective for the power control and a fully distributed method for solving the multiobjective power optimization problem. The obtained solution is parameterized so that a tradeoff can be made between power consumption and QoS. In the limit case, when only QoS is weighted, the algorithm reduces to the well-known distributed power control algorithm (IEEE Trans. Commun., vol. 42, no. 2/3/4, pt. 1, Feb./Mar./Apr. 1994). In the other limit, the algorithm reduces to transmission with fixed minimum power. The convergence properties of the proposed algorithm are studied both theoretically and with numerical simulations. Although we only consider SINR and power sum, our algorithm could be easily modified to take other objectives, such as throughput, into account. [ABSTRACT FROM AUTHOR]

Several channel-allocation algorithms have been pro- posed in the literature for traditional cellular networks with static base stations (BS5), while not much attention has been given to channel-allocation problems for cellular networks where BSs are mobile. In cellular networks with mobile BSs (MBSs), the network topology is dynamic due to the mobility of the BSs. This makes the channel-allocation problem in such networks more challenging. Moreover, the MBSs may fail and degrade the performance of the cellular network. Therefore, it is desirable that the channel- allocation algorithm be fault tolerant. Thus, even in the presence of failure of the MBSs, the channel-allocation algorithm should work reasonably well. It is also desirable to design a channel-allocation approach that guarantees that the request from a mobile host (MH) is responded to in a timely manner. In this paper, a distributed dynamic channel-allocation algorithm that addresses these problems in cellular networks with MBSs is proposed. The proposed algorithm is fault tolerant and guarantees that the time to respond to an MH's request for supporting a call is upperbounded. The performance evaluation of the proposed algorithm shows that the proposed algorithm performs well, even in the presence of failure of the MBSs. [ABSTRACT FROM AUTHOR]

The distributed coordination function (DCF) of IEEE 802.11 standard adopts the binary exponential backoff (BEB) for collision avoidance. In DCF, the contention window is reset to an initial value, i.e., CWmin, after each successful transmission. Much research has shown that this dramatic change of window size may degrade the network performance. Therefore, backoff algorithms, such as gentle DCF (GDCF), multiplicative increase-linear decrease (MILD), exponential increase- exponential decrease (ELED), etc., have been proposed that try to keep the memory of congestion level by not resetting the contention window after each successful transmission. This paper proposes a multichain backoff (MCB) algorithm, which allows stations to adapt to different congestion levels by using more than one backoff chain together with collision events caused by stations themselves as well as other stations asindications for choosing the next backoff chain. The performance of MCB is analyzed and compared with those of 802.11 DCF, GDCF, MILD, and EIED backoff algorithms. Simulation results show that, with multiple backoff chains and collision events as reference for chain transition, MCB can offer a higher throughput while still maintaining fair channel access than the existing backoff algorithms. [ABSTRACT FROM AUTHOR]

A new multicarrier system, termed multisymbol encapsulated orthogonal frequency division multiplexing (MSE-OFDM), is proposed, in which one cyclic prefix (CP) is used for multiple OFDM symbols. The original motivation for the MSE-OFDM proposal is to reduce the redundancy due to the CP in static-channel environments. The authors then found that an alternative implementation of the system can be used to improve the robustness to frequency offset and reduce the peak-to-average power ratio (PAPR). Equalization and demodulation algorithms for the MSE-OFDM system are proposed. A new preamble and the corresponding frequency-offset and channel estimation techniques are studied for the MSE-OFDM system. Using the proposed MSE-OFDM preamble, the joint maximum likelihood (ML) estimation of the frequency offset and the channel impulse response (CIR) is investigated in this paper. Possible ways to reduce the joint estimation complexity, including exploitation of the preamble structure, approximation of the joint ML estimator, and fast Fourier transform (FFT) pruning, are discussed. The performance of the proposed MSE-OFDM systems and channel estimators are analyzed and verified through numerical simulations. An analysis on the bandwidth efficiency, the performance with frequency offset, and the PAPR of the MSE-OFDM system are also presented. [ABSTRACT FROM AUTHOR]

This paper examines the problem of quality-of-service group communications in a heterogeneous network, which consists of multiple mobile ad hoc networks attached to the backbone Internet. A heuristic multicast algorithm named delay and delay variation multicast algorithm (DDVMA) is proposed. DDVMA is designed for solving the delay- and delay-variation-bounded multicast tree problem, which has been proved to be NP-complete. It can find a multicast tree satisfying the multicast end-to-end delay constraint and minimizing the multicast delay variation. Two concepts, which can help the DDVMA achieve better performance in terms of multicast delay variation than the delay and delay variation constraint algorithm that is known to be the most efficient so far, are proposed, namely, 1) the proprietary second shortest path and 2) the partially proprietary second shortest path. An analysis is given to show the correctness of DDVMA, and simulations are conducted to demonstrate the performance improvement of DDVMA in terms of multicast delay variation. It is also shown that the strategy employed by DDVMA is also applicable to handling the mobility of mobile hosts in a heterogeneous network. [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]

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution. [ABSTRACT FROM AUTHOR]

Joint scheduling and power control schemes have previously been proposed to reduce power dissipation in wireless ad hoc networks. However, instead of power consumption, throughput is a more important performance concern for some emerging multihop wireless networks, such as wireless mesh networks. This paper examines joint link scheduling and power control with the objective of throughput improvement. The MAximum THroughput link Scheduling with Power Control (MATH-SPC) problem is first formulated and then a mixed integer linear programming (MILP) formulation is presented to provide optimal solutions. However, simply maximizing the throughput may lead to a severe bias on bandwidth allocation among links. To achieve a good tradeoff between throughput and fairness, a new parameter called the demand satisfaction factor (DSF) to characterize the fairness of bandwidth allocation and formulate the MAximum Throughput fAir link Scheduling with Power Control (MATA-SPC) problem is defined. An MILP formulation and an effective polynomial-time heuristic algorithm, namely, the serial linear programming rounding (SLPR) heuristic, to solve the MATA-SPC problem are also presented. Numerical results show that bandwidth can be fairly allocated among all links/flows by solving the MILP formulation or by using the heuristic algorithm at the cost of a minor reduction of network throughput. In addition, extensions to end-to-end throughput and fairness and multiradio wireless multihop networks are discussed. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

With the convergence of multimedia applications and wireless communications, there is a need to support real-time traffic in wireless networks. In general, real-time packets must be delivered before a certain delay upper bound. In the literature, feasible earliest due date (FEDD) is one of the scheduling algorithms proposed to provide packet delay upper bound guarantees over a time-varying wireless channel. However, FEDD is reactive with respect to changes in the wireless channel. In view of this, we propose a novel deadline-based scheduling algorithm called proactive earliest due date (PEDD), which dynamically adjusts a packet's deadline in anticipation of an upcoming change in the channel condition. Similar to FEDD, PEDD is idealistic, as they both assume the availability of the exact channel knowledge. This is not implementable and, thus, this paper further proposes a realistic version of PEDD, called R-PEDD. R-PEDD uses a probing mechanism to acquire the channel knowledge, which in turn is used for the packet deadline adjustment. Since probe packets consume bandwidth, a modified version of R-PEDD, called R-PEDD+ is proposed to derive the required channel information from recent packet transmissions. We have performed extensive simulations using OPNET to evaluate the performance of these proposed algorithms. In short, PEDD always outperforms a couple of existing algorithms in the literature. R-PEDD and R-PEDD+ are both capable of approximating the performance of the idealistic PEDD in a realistic wireless channel. However, their performance deteriorates with more rapid changes in the channel condition. [ABSTRACT FROM AUTHOR]