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Intelligent reflecting surface (IRS) is a promising new paradigm to achieve high spectral and energy efficiency for future wireless networks by reconfiguring the wireless signal propagation via passive reflection. To reap the promising gains of IRS, channel state information (CSI) is essential, whereas channel estimation errors are inevitable in practice due to limited channel training resources. In this paper, in order to optimize the performance of IRS-aided multiuser communications with imperfect CSI, we propose to jointly design the active transmit precoding at the access point (AP) and passive reflection coefficients of the IRS, each consisting of not only the conventional phase shift and also the newly exploited amplitude variation. First, the achievable rate of each user is derived assuming a practical IRS channel estimation method, which shows that the interference due to CSI errors is intricately related to the AP transmit precoders, the channel training power and the IRS reflection coefficients during both channel training and data transmission. Next, for the single-user case, by combining the benefits of the penalty method, Dinkelbach method and block successive upper-bound minimization (BSUM) method, a new penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection coefficients for maximizing the achievable data transmission rate subjected to CSI errors; while for the multiuser case, a new penalty dual decomposition (PDD)-based algorithm is proposed to maximize the users’ weighted sum-rate. Finally, simulation results are presented to validate the effectiveness of our proposed algorithms as compared to benchmark schemes. In particular, useful insights are drawn to characterize the effect of IRS reflection amplitude control (with/without the conventional phase-shift control) on the system performance under imperfect CSI. [ABSTRACT FROM AUTHOR]

The broadcast nature of wireless communications makes transmission susceptible to eavesdropping. Recently, physical-layer security has been extensively studied to secure the wireless transmissions, but the security is severely compromised when the eavesdropper has the superiority in the channel quality. Toward this issue, we in this paper propose a joint ARQ and network coding method exploiting the characteristics of both the physical layer and the link layer. Specifically, we relate the message to be transmitted in the current slot with the successfully decoded messages in previous slots, where the ARQ is employed at the legitimate side to guarantee the successful transmission and decoding. Once one or more received messages fail to be decoded at the eavesdropper, it further prevents the eavesdropper from decoding the transmissions in later slots and thus the message transmitted currently and later is secured at the legitimate side. Moreover, for the more disadvantageous case that the eavesdropper is geographically closer to the transmitter, we further propose a destination-aided network coding scheme, which secures private information no matter where the eavesdropper is. The closed-form expressions of intercept probability and loss probability of the private information are analytically presented. The simulation results are provided to confirm our theoretical findings. [ABSTRACT FROM AUTHOR]

In a high-speed digital communication system, jitter performance plays a crucial role in bit-error rate. It is important to accurately derive each type of jitter as well as total jitter and to identify root causes of jitter by jitter decomposition as a key tool. In this paper, we extend our previously reported algorithm to decompose duty cycle distortion as well as other deterministic jitter components including periodic jitter (PJ), intersymbol interference (ISI), and random jitter (RJ), and describe more detail of this algorithm with extensively simulation and measurements to verify the algorithm. The proposed ISI model only requires the time invariant condition, which is true for almost all systems, while the traditional ISI model is valid only with linear time invariant assumption. Compared to the conventional methods, the proposed jitter decomposition method is able to obtain estimated individual jitter component values with good accuracy by using fewer samples of total jitter data. The efficiency and accuracy of the proposed method were demonstrated by simulation and hardware experiments. [ABSTRACT FROM AUTHOR]

With the rapid emergence of applications in Mobile Opportunistic Networks (MONs), understanding and characterizing their properties becomes extremely important. A fundamental model for MONs is time-varying graph, which currently remains poorly understood since many well-recognized properties of static graphs have no obvious counterpart in dynamic ones. In MONs, the dynamical links change opportunistically and usually the system energy is very limited, which results in unique and unknown properties about the network connectivity and reachability. In this paper, taking the communication energy into account, we introduce the concept of Energy-aware Temporal Reachability Graphs (ETRG), which characterizes the connectivity of MONs with the consideration of communication consumed energy, and consequently reveals the communication capabilities of MONs with the given of real-world system parameters of data size, tolerable delay, and energy budget. We come up with efficient algorithm to calculate ETRG from the corresponding time-varying graphs. By applying ETRG to several mobile networks recorded by real-life human and vehicular mobility traces, we characterize their network connectivity properties in terms of average reachability, communication asymmetry, and stability. Moreover, utilizing ETRG that places upper bounds of the communications capabilities, we reveal the fundamental relations and tradeoffs among large-scale variability of the system metrics of energy budget, tolerable delay, and data size on the system performance. [ABSTRACT FROM AUTHOR]

In this paper, we model a vehicular multihop network as an evolving graph and formulate the problem of optimal data dissemination over the network in terms of minimum number of transmissions. We show that the problem belongs to the NP complexity class and provide an easy to implement polynomial-time \2 \tau H(\Delta)-approximation algorithm, where \tau is the number of different subgraphs that comprise the evolving graph, and H(\Delta) is the harmonic number of the degree of the evolving graph. By means of applying our heuristic over a vehicular scenario generated by a microscopic road-traffic simulator, we provide some insight into the data dissemination issue. In addition, the proposed algorithm is employed to benchmark a state-of-the-art communication protocol. We hope this paper will inspire more efficient heuristics and data dissemination solutions. [ABSTRACT FROM PUBLISHER]

This paper investigates simultaneous wireless information and power transfer (SWIPT) for a multiple-input–single-output (MISO) secrecy channel. First, transmit beamforming without artificial noise (AN) is designed to achieve the secrecy rate maximization problem subject to the transmit power and the energy harvesting (EH) constraints. This problem is not convex, but this can be solved by applying a bisection search to a sequence of the associated power minimization problems, each of which can be solved by using a novel relaxation approach. Moreover, we extend our proposed algorithms to the robust case by incorporating channel uncertainties. Then, transmit beamforming with AN is investigated for the secrecy rate maximization problem, where two relaxation approaches are presented, i.e., a two-level optimization algorithm and a successive convex approximation (SCA), to solve the secrecy rate maximization problem. In addition, tightness analyses of rank relaxation are provided to show that the optimal transmit covariance matrix exactly returns rank one. Simulation results are provided to validate the performance of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

In heterogeneous networks (HetNets), the load between macrocell base stations (MBSs) and small-cell base stations (SBSs) is imbalanced due to their different transmission powers and locations. This load imbalance significantly impacts system performance and affects the experience of mobile users (MUs) with different priorities. In this paper, we aim to distributively optimize the user association in HetNets with various user priorities to solve the load balancing problem. Since the user association is a binary matching problem, which is NP-hard, we propose a distributed belief propagation (BP) algorithm to approach the optimal solution. We first develop a factor graph model, using the network topology, to represent this user association problem. With this factor graph, we propose a novel distributed BP algorithm by adopting the proportional fairness as the objective. Next, we theoretically prove the existence of the fixed point in our BP algorithm. To be more practical, we develop an approximation method to significantly reduce the computational and communication complexity of the BP algorithm. Furthermore, we analyze some properties of the factor graph relevant to the performance of the BP algorithm using the stochastic geometry. Simulation results show that 1) the proposed BP algorithm well approaches the optimal system performance and achieves a much better performance compared with other association schemes and that 2) the analytical results on the average degree distribution and sparsity of the factor graph match with those obtained from the Monte Carlo simulations. [ABSTRACT FROM PUBLISHER]

The opportunities and flexibility in relay networks and orthogonal frequency-division multiple access (OFDMA) make the combination a suitable candidate network and air-interface technology for providing reliable and ubiquitous high-data-rate coverage in next-generation cellular networks. Advanced and intelligent radio resource management (RRM) schemes are known to be crucial toward harnessing these opportunities in future OFDMA-based relay-enhanced cellular networks. However, it is not very clear how to address the new RRM challenges (such as enabling distributed algorithms, intra-cell/inter-cell routing, intense and dynamic co-channel interference (CCI), and feedback overhead) in such complex environments comprising a plethora of relay stations (RSs) of different functionalities and characteristics. Employment of conventional RRM schemes in such networks will highly be inefficient if not infeasible. The next-generation networks are required to meet the expectations of all wireless users, irrespective of their locations. High-data-rate connectivity, mobility, and reliability, among other features, are examples of these expectations. Therefore, fairness is a critical performance aspect that has to be taken into account in the design of prospective RRM schemes. This paper reviews some of the prominent challenges involved in migrating from the conventional cellular architecture to the relay-based type and discusses how intelligent RRM schemes can exploit the opportunities in relay-enhanced OFDMA-based cellular networks. We identify the role of multiantenna systems and explore the current approaches in literature to extend the conventional schedulers to next-generation relay networks. This paper also highlights the fairness aspect in such networks in the light of the recent literature, provides some example fairness metrics, and compares the performances of some representative algorithms. [ABSTRACT FROM AUTHOR]

We study power-allocation problems in wireless systems through a network utility maximization framework. In this framework, the type of utility function represents the characteristics of each service. Hence, to deal with multiclass services in the system, it is important to accommodate various types of utility functions. In this paper, we consider four types of utility functions that can represent most of the services in wireless networks. We first develop a simple algorithm that solves a general optimization problem with those four types of utility function. We show that, even though the proposed algorithm might not provide the optimal solution, it provides an asymptotically optimal solution, which could be a good approximation to the optimal solution. The proposed algorithm can be applied to various resource-allocation problems in wireless systems. Among them, in this paper, we show that the proposed algorithm can be applied to both uplink and downlink power-allocation problems. [ABSTRACT FROM AUTHOR]

Contour line estimation in a monitored physical phenomenon using wireless sensor networks (WSNs) with cross-layer considerations is investigated in this paper. Herein, we present a statistical approach to locate contour points for contour line construction in the presence of irregular sensor deployment with the assistant of Delaunay triangular meshes. The proposed contour-estimation algorithm has certain error-correction capability, and it is robust to the data degradation coming from sensing and/or communication noise. To ensure the success of the proposed algorithm, we further analyze three sources of signal distortion: sensing noise, data quantization error, and data communication noise. We find that choosing a proper data quantization level can balance the communication cost and the desired signal quality. Meanwhile, the impact of channel impairment can be mitigated by the appropriate data-fusion mechanism. In this paper, an adaptive data-fusion mechanism is proposed to avoid excessive packet retransmissions. The correctness of the proposed approach is verified through simulation, and the effects of different system parameters on the overall system performance are also given to show the robustness of the proposed algorithm. This paper also offers some guidelines on the design of the WSN system. [ABSTRACT FROM AUTHOR]

Orthogonal frequency division multiplexing (OFDM) system suffers extra performance degradation in fast fading channels due to intercarrier interference (Id). Combining frequency domain equalization and bit-interleaved coded modulation (BICM), the iterative receiver is able to harvest both temporal and frequency diversity. Realizing that ICI channels are intrinsically IS! channels, this paper proposes a soft-in soft-out (SISO) maximum a posteriori (MAP) equalizer by extending Ungerboeck's maximum likelihood sequence estimator (MLSE) formulation to ICI channels. The SISO MAP equalizer employs BCJR algorithm and computes the bit log-likelihood ratios (LLR) for the entire received sequence by efficiently constructing a trellis that takes into account of the ICI channel structure. A reduced state (RS) formulation of the SISO MAP equalizer which provides good performance/complexity tradeoff is also described. Utilizing the fact that ICI energy is clustered in adjacent subcarriers, frequency domain equalization is made localized. This paper further proposes two computational efficient linear minimum mean square error (LMMSE) based equalization methods: recursive q-tap SIC-LMMSE equalizer and recursive Sliding-Window (SW) SIC-LMMSE equalizer respectively. Simulations results demonstrate that the iterative SISO RS-MAP equalizer achieves the performance of no ICI with normalized Doppler frequency fdTs up to 20.46% in realistic mobile WiMAX environment. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) can be used to support high-data-rate transmissions over time-dispersive fading channels. Many OFDM-based communication systems use packet-based transmission, where channel estimation is needed for the detection of information-carrying symbols. The finite impulse response (FIR) channel model is simple and effective for some simulations of channel estimation for the OFDM-based communication systems over the time-dispersive channels; yet, it is only an approximate channel model that cannot be used in the case of accurate channel estimation. Unfortunately, many researchers have overlooked this issue and have been devising channel-estimation algorithms squarely based on the FIR channel model. While the channel estimation results from these algorithms can be impressive for the FIR channels, the algorithms can hardly be applied in real-world applications. This paper explains in detail the reason the FIR channel model is only an approximate channel model for the OFDM-based communication systems, trying to discourage the inappropriate usage of this model, which can lead to fruitless efforts. This paper also presents a realistic channel model for OFDM-based communication systems, which can be used to realistically access the channel parameter-estimation algorithms. [ABSTRACT FROM AUTHOR]

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, we consider the downlink of a multiuser wireless communication system with multiple antennas at the base station and users each with a single receive antenna. It is known that when channel state information (CSI) is available at the transmitter a large performance gain can be achieved. In a system employing time-division duplexing (TDD), CSI can be obtained at the base station if there is reciprocity between the forward and reverse channels. CSI can also be conveyed from the users to the base station via a limited-rate feedback channel in a frequency-division duplexing (FDD) system. !n any case, channel estimation errors are inevitable due to the presence of background noise in the estimated signal and due to the finite number of feedback bits used in a limited-rate feedback system model. In this paper, we first consider the general case when partial CSI is available at the transmitter. We derive an MMSE based precoding technique that considers channel estimation errors as an integral part of the system design. Using rate-distortion theory and the generalized Lloyd vector quantization algorithm, we then specialize our results for the more practical limited-rate feedback system model. Compared to previously proposed precoding techniques such as channel inversion and regularized channel inversion, it is shown that the proposed precoding technique significantly improves the average bit error rate (BER) in the system. Furthermore, the performance of the proposed technique is investigated in the high signal-to-noise ratio (SNR) regime, and similar to [1], [21, it is shown that the proposed technique suffers from a ceiling effect that asymptotically limits the system performance. [ABSTRACT FROM AUTHOR]

This paper tackles a power minimization problem of interleave-division multiple-access (IDMA) systems over a fading multiple-access channel. The problem is minimizing the total power received by the receiver while keeping the bit error rates (BERs) of all users below a predefined value. The original formulation of the problem has highly nonlinear and implicitly defined functions, which render most existing optimization methods incapable. A new formulation is proposed in this paper, whose solution can effectively be obtained by a branch-and-bound (B&B) technique. An algorithm is devised based on B&B, and its effectiveness is also demonstrated by numerical experiments of systems with a moderate numbers of users. [ABSTRACT FROM AUTHOR]

A new fast forward error correction (FEC) allocation algorithm for unequal error protection (UEP) of video transmission over wireless channels is proposed in this paper. First, an UEP scheme, which takes into consideration the non-uniformly distributed importance of frames in a group of pictures (GOP) and macroblocks in a video frame, is proposed. An enhanced video error propagation model, namely expected number of macroblocks error propagation (ENMEP) is also proposed in this paper to measure the amount of error propagation caused by transmission errors. Finally, by making use of our proposed ENMEP error propagation model, a fast FEC allocation algorithm for our proposed UEP scheme is also proposed. Simulation results demonstrate that our scheme outperforms the previous UEP scheme and the classical equal error protection (EEP) scheme. [ABSTRACT FROM AUTHOR]

Wireless systems have evolved into supporting non- real-time data services. However, as the data rates for the services increase, the number of base stations per service area needs to expand, which leads to a high degree of base-station density. On the other hand, the so-called best effort resource management has been extensively studied for nonreal-time data services. One example of such efforts can be found in packet scheduling. The purpose of this paper is to investigate the economic impact of the down-link scheduling in terms of the base-station density. To this end, equations that can calculate the base-station density for the given quality of service (QoS) requirements such as outage probabilities, average data rates, and target Eb /Io were derived. Under specific QoS requirements on Rayleigh-fading channel environments, it is found that the one-by-one downlink scheduling (round-robin) requires about 50%-60% of the base stations required by the conventional simultaneous transmission. It was also found that this impact is almost the same as simply doubling the spectrum bandwidth for the simultaneous transmission. The base-station density is directly related to the infrastructure cost and thus may be translated into service prices. Therefore, the analysis in this paper provides a new insight into an economic aspect; how much the service prices for downloading the nonreal-time data would decrease with the introduction of packet scheduling in the code division multiple access downlink. [ABSTRACT FROM AUTHOR]

Channel estimation and tracking pose real problems in broadband single-carrier wireless communication systems employing multiple transmit and receive antennas. An alternative to estimating the channel is to adaptively equalize the received symbols. Several adaptive equalization solutions have been researched for systems operating in the time domain. However, these solutions tend to be computationally intensive. A low-complexity alternative is to adaptively equalize the received message in the frequency domain. In this paper, we present an adaptive frequency-domain equalization (FDE) algorithm for implementation in single-carrier (SC) multiple-input multiple-output (MIMO) systems. Furthermore, we outline a novel method of reducing the overhead required to train the proposed equalizer. Finally, we address the issues of complexity and training sequence design. Other computationally efficient adaptive FDE algorithms for use in SC systems employing single transmit and receive antennas, receive diversity, or space-lime block codes (STBC) can be found in the literature. However, the algorithm detailed in this paper can be implemented in STBC systems as well as in broadband spatial multiplexing systems, making it suitable for use in high data rate MIMO applications. [ABSTRACT FROM AUTHOR]

Location-based services (LBSs), considered as a killer application in the wireless data market, provide information based on locations specified in the queries. In this paper, we examine the indexing issue for querying location-dependent data in wireless LBSs; in particular, we focus on an important class of queries, planar point queries. To address the issues of responsiveness, energy consumption, and bandwidth contention in wireless communications, an index has to minimize the search time and maintain a small storage overhead. It is shown that the traditional point-location algorithms and spatial index structures fail to achieve either objective or both. This paper proposes a new index structure, called D-tree, which indexes spatial regions based on the divisions that form the boundaries of the regions. We describe how to construct a binary D-tree index, how to process queries based on the D-tree, and how to page the binary D-tree. Moreover, two parameterized methods for partitioning the original space, called fixed grid assignment (FGA) and adaptive grid assignment (AGA), are proposed to enhance the D-tree. The performance of the D-tree is evaluated using both synthetic and real data sets. Experimental results show that the proposed D-tree outperforms the well-known indexes such as the R*-tree, and that both the FGA and AGA approaches can achieve different performance trade-offs between the index search time and storage overhead by fine-tuning their algorithmic parameters. [ABSTRACT FROM AUTHOR]

Spectral efficiency improvement is essential for mobile systems development in the light of growing demand for high data transmission rate. The Time-domain synchronous OFDM transmission system increases bandwidth utilization by time-domain channel estimation without any support from frequency-domain pilot signals. Channel identification methods use a training sequence, added at the beginning of every OFDM symbol. Sparse nature of the channel impulse response, which manifests itself during wireless broadband transmission, enables one to implement compressed sensing techniques for channel identification. Channel sparsity reduces the number of measurement samples required in channel reconstruction procedure, but they should be taken from the inter-block interference (IBI) free part of the received training sequence. If maximum delay spread of the channel is comparable with the length of the training sequence, the number of measurements within the IBI-free region may be insufficient for accurate channel identification. This paper discusses a new iterative approach to sparse channels estimation, which uses the measurements from outside the IBI-free region. The proposed solution is examined for simulated transmission over randomly generated doubly-selective channels when compared with the conventional CS technique and perfect channel state information condition. The experiments reveal an enhancement of the transmission quality in terms of SER for slow-time selective channels when both delays and gains of the channel impulse response are estimated with the orthogonal matching pursuit algorithm. Further improvement, also for transmission over moderate varying channels, is observed when the path delays are found in advance. A suitable frame structure is proposed to do so. [ABSTRACT FROM PUBLISHER]

In this paper, we study the power allocation problem in a multiuser cooperative network, where users help each other's transmissions to an access point. We use iterative double auction (IDA) game to model the interaction among the users and the access point. In each iteration of this game, the users first submit bids for buying other users' power and asks for selling its own power, and then, the access point determines the power allocation based on users' bids and asks. We propose a distributed algorithm for the implementation of the IDA-based power allocation. We also show that the proposed algorithm achieves a weighted sum signal-to-noise ratio (sum-SNR)-optimal solution. Simulation results are conducted to verify the performance of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

Intra-session network coding has been shown to offer significant gains in terms of achievable throughput and delay in settings where one source multicasts data to several clients. In this paper, we consider a more general scenario where multiple sources transmit data to sets of clients over a wireline overlay network. We propose a novel framework for efficient rate allocation in networks where intermediate network nodes have the opportunity to combine packets from different sources using randomized network coding. We formulate the problem as the minimization of the average decoding delay in the client population and solve it with a gradient-based stochastic algorithm. Our optimized inter-session network coding solution is evaluated in different network topologies and is compared with basic intra-session network coding solutions. Our results show the benefits of proper coding decisions and effective rate allocation for lowering the decoding delay when the network is used by concurrent multicast sessions. [ABSTRACT FROM AUTHOR]

In this paper, we dynamically select the transmission rate and design wireless network coding to improve the quality of services, such as delay for time-critical applications. In a network coded system, with a low transmission rate and, hence, a longer transmission range, more packets may be encoded, which increases the coding opportunity. However, a low transmission rate may incur extra transmission delay, which is intolerable for time-critical applications. We design a novel joint rate selection and wireless network coding (RSNC) scheme with a delay constraint to maximize the total benefit (where we can define the benefit based on the priority or importance of a packet for example) of the packets that are successfully received at the destinations without missing their deadlines. We prove that the proposed problem is NP-hard and propose a novel graph model to mathematically formulate the problem. For the general case, we propose a transmission metric and design an efficient algorithm to determine the transmission rate and coding strategy for each transmission. For a special case when all delay constraints are the same, we study pairwise coding and present a polynomial-time pairwise coding algorithm that achieves an approximation ratio of \1 -(\1/e) to the optimal pairwise coding solution, where $e$ is the base of the natural logarithm. Finally, simulation results demonstrate the superiority of the proposed RSNC scheme. [ABSTRACT FROM PUBLISHER]

This paper considers the problems of minimizing the completion time and reducing decoding complexity for relay-aided wireless broadcast. Both network coding and scheduling problems are considered. A deterministic network coding algorithm is designed to select innovative encoding vectors, which is applicable to both the base station and the relay. The proposed algorithm can reduce decoding complexity significantly by selecting sparse encoding vectors. Integrating with the proposed network coding algorithm, a scheduling scheme based on dynamic programming is proposed, which is proved to be optimal in terms of minimizing expected completion time. Considering the size of state space and computational complexity of dynamic programming, a greedy scheduling algorithm is also proposed for practical implementation. Simulation shows that the proposed network coding algorithm and scheduling schemes work very well both in reducing completion time and in decoding complexity. [ABSTRACT FROM PUBLISHER]

Quantized Congestion Notification (QCN) has been developed for IEEE 802.1Qau to provide congestion control at the Ethernet Layer or Layer 2 in data center networks (DCNs) by the IEEE Data Center Bridging Task Group. One drawback of QCN is the rate unfairness of different flows when sharing one bottleneck link. In this paper, we propose an enhanced QCN congestion notification algorithm, called fair QCN (FQCN), to improve rate allocation fairness of multiple flows sharing one bottleneck link in DCNs. FQCN identifies congestion culprits through joint queue and per flow monitoring, feedbacks individual congestion information to each culprit through multi-casting, and ensures convergence to statistical fairness. We analyze the stability and fairness of FQCN via Lyapunov functions and evaluate the performance of FQCN through simulations in terms of the queue length stability, link throughput and rate allocations to traffic flows with different traffic dynamics under three network topologies. Simulation results confirm the rate allocation unfairness of QCN, and validate that FQCN maintains the queue length stability, successfully allocates the fair share rate to each traffic source sharing the link capacity, and enhances TCP throughput performance in the TCP Incast setting. [ABSTRACT FROM AUTHOR]

In this paper, the iterative water-filling (IWF) algorithm is considered when the noise-plus-interference levels fed back from the receivers are quantized. A sufficient condition for this algorithm to have a unique Nash equilibrium is derived. This condition is shown to approach the corresponding condition for standard IWF when the quantization resolution or the transmission power are sufficiently high. [ABSTRACT FROM AUTHOR]

In this paper, we propose a systematic solution to the problem of scheduling delay-sensitive media data for transmission over time-varying wireless channels. We first formulate the dynamic scheduling problem as a Markov decision process that explicitly considers the users' heterogeneous multimedia data characteristics (e.g., delay deadlines, distortion impacts and dependences, and so on) and time-varying channel conditions, which are not simultaneously considered in state-of-the-art packet scheduling algorithms. This formulation allows us to perform foresighted decisions to schedule multiple data units for transmission at each time in order to optimize the long-term utilities of the multimedia applications. The heterogeneity of the media data enables us to express the transmission priorities between the different data units as a priority graph, which is a directed acyclic graph. This priority graph provides us with an elegant structure to decompose the multidata unit foresighted decision at each time into multiple single-data unit foresighted decisions which can be performed sequentially, from the high priority data units to the low priority data units, thereby significantly reducing the computation complexity. When the statistical knowledge of the multimedia data characteristics and channel conditions is unknown a priori, we develop a low-complexity online learning algorithm to update the value functions, which capture the impact of the current decision on the future utility. The simulation results show that the proposed solution significantly outperforms existing state-of-the-art scheduling solutions. [ABSTRACT FROM PUBLISHER]

This paper aims to optimize the overall video quality and traffic performance for multi-rate video multicast over hybrid wired/wireless networks. In order to perform layered utility maximization over tiered networks, we propose a joint source-network flow optimization scheme where individual layers of the scalable video stream are imposed on their optimal multicast paths and associated rates for the highest sustainable layered video quality with minimum costs. It sufficiently guarantees that each destination node accesses progressive layered stream in an incremental order, considers network coding across overlapping paths to destination nodes for decent multicast capacity, and addresses the link contention problem during wireless transmission. We formulate the problem into convex programming with the objective to minimize the total rate-distortion variations between layers. Using primal decomposition and the primal-dual approach, we develop a decentralized algorithm with two levels of optimization. The numerical and packet-level results compare extensive performance under different control conditions over coded and non-coded hybrid networks. It demonstrates that the proposed algorithm could actually achieve the max-flow throughput and provide better video quality with optimal layered access for heterogeneous receivers. [ABSTRACT FROM AUTHOR]

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]

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]

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 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]

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 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]

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 GNSS software receiver, blocks of digitized intermediate-frequency (IF) data are prepared at the front end and sent to the processing unit for signal acquisition, tracking, demodulation, and position fix. A problem that is observed in practice when the GNSS software module is co-located with a mobile phone device is that the digitized IF data are subject to data intermittency. The intermittency results from the use of mobile phone when the GNSS signals are being received or the execution of higher priority routine in the host computer. An improper buffering scheme at the front end may also lead to such phenomena. Such data intermittency leads to bursttype errors (rather than bit-type errors) on the data to be processed, posing a challenge for the tracking of the GNSS signals. Indeed, if not properly handled, a typical tracking algorithm is not able to accommodate such a large data gap. In the paper, a decision-aided tracking algorithm is developed for a seamless tracking of codes and phases. The effects of data intermittency on code and phase tracking are analyzed. To accounting for the effect without going through the reacquisition process, a detector based on signal power and continuity is then implemented to facilitate decision making. It is shown, through the processing of field gathered data, that the proposed algorithm can indeed be able to continuously track codes and phases in the presence of data intermittency. [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]

Frequency-domain equalization (FDE) is an effective technique for high-data-rate wireless communication systems suffering from very long intersymbol interference. Most of the existing FDE algorithms are limited to slow time-varying fading channels due to the lack of an accurate channel estimator. In this paper, we employ an interpolation method to propose new algorithms for frequency-domain channel estimation for both slow and fast time-varying fading. We show that least squares (LS)-based channel estimation and minimum mean square (MMSE)-based channel estimation with interpolations are equivalent under certain conditions. Noise variance estimation and channel equalization in the frequency domain are also discussed with fine-tuned formulas. Numerical examples indicate that the new algorithms perform very well for severe fading channels with long delay spread and high Doppler spread. It is also shown that our new algorithms outperform the recently developed frequency-domain least mean squares (LMS) and recursive LS (RLS) algorithms which are capable of dealing with moderate fading channels. [ABSTRACT FROM AUTHOR]

Can conventional differential unitary space time modulation (DUSTM) be applied when there is an unknown carrier frequency offset (CFO)? This paper answers this question affirmatively and derives the necessary maximum likelihood (ML) detection rule. The asymptotic performance of the proposed ML rule is analyzed, leading to a code design criterion for DUSTM by using the modified diversity product. The resulting proposed decision rule is a new differential modulation scheme in both the temporal and spatial domains. Two sub-optimal multiple-symbol decision rules with improved performance are also proposed. For the efficient implementation of these, we derive a modified bound intersection detector (BID), a generalization of the previously derived optimal BID for the conventional DUSTM. The simulation results show that the proposed differential modulation scheme is more robust against CFO drifting than the existing double temporal differential modulation. [ABSTRACT FROM AUTHOR]

In this paper, we design jointly optimum transmitter and receiver beamforming structures in correlated MIMO Rayleigh fading channels with noisy channel estimates, and evaluate their performance through a closed-form expression for the probability of error. At the receiver, an estimate of the channel is obtained based on the transmitted pilot symbols. The knowledge of the estimate is then made available to the transmitter through a feedback channel. It is assumed that spatial correlation exists, either at the transmitter or at the receiver. A new exact closed-form expression for the probability of error is derived and the joint effects of diversity order and channel estimation accuracy on system performance are analyzed. [ABSTRACT FROM AUTHOR]

Abstract-This paper proposes a dynamic resource-allocation (DRA) algorithm for packet data services in wireless communication systems based on Hopfield neural networks (HNNs). The resource-allocation algorithm assumes a delay-centric approach in that it maximizes resource utilization of the overall system while minimizing the packet delay. The real-time (RT) working capability of HNN hardware implementation means that a very powerful scheduling DRA algorithm can be obtained. A generic formulation of the algorithm is presented to establish the optimal bit rate allocation. In addition, some illustrative examples of this formulation are given, considering specific wireless communication systems, such as General Packet Radio Service (GPRS) or Universal Mobile Telecommunications System (UMTS). lo be more precise, the performance of the proposed DRA algorithm is evaluated in a realistic UMTS scenario, considering both RT and nonreal-time (NRT) services. To obtain the best resource distribution and fulfill the different quality-of-service (QoS) levels required by RT and NRT services, the new HNN-based delay-centric DRA algorithm is performed twice. Initially, only the RT services are considered, and following this, all the NRT services are taken into account. The results reveal that the proposed DRA algorithm outperforms other reference algorithms in terms of not only average packet delay but the allocated total bit rate as well. [ABSTRACT FROM AUTHOR]

New sphere decoding and synchronization algorithms for multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems are proposed in this paper. In particular, an iterative list branch-and-bound (BB) algorithm based on the basic BB algorithm is described to obtain a candidate list to compute soft information that is used in the iterative detector. Furthermore, an improved algorithm that uses prior information from the preceding iteration to calculate the lower bound is proposed, and the candidate list is updated every iteration. To obtain a complete modem architecture, we propose an efficient expectation-maximization (EM)-based iterative algorithm for synchronization and channel estimation to interface with the proposed list-sphere-decoding detector, and we investigate the performance of the designed MIMO-OFDM modem on a realistic fading channel. The obtained performance results show that it is possible to practically design a performing MIMO-OFDM modem with high spectral efficiency, i.e., 8 bit/s/Hz with a 4 x 4 16-QAM MIMO-OFDM system. [ABSTRACT FROM AUTHOR]

The jamming robustness of frequency hopping (FH) systems with M-ary frequency shift keying (MFSK) modulation may be potentially neutralized by a follower partial-band jammer. In this paper, a maximum likelihood (ML)-based algorithm that uses a two-element array is proposed for joint follower jamming rejection and symbol detection in slow FHJMFSK systems over quasi-static flat Rayleigh fading channels. The algorithm is derived by treating both the received jamming components and the unknown data symbols as deterministic quantities to be jointly estimated in an integrated ML operation. In addition, an approximate expression for the symbol error rate (SER) of the proposed scheme is derived when BFSK signaling is employed in a jamming dominant scenario. Analytical and simulated results show that the proposed approach is able to remove jamming and outperform the conventional and sample matrix inversion (SMI)-based beam-formers in the presence of a follower partial-band jammer. [ABSTRACT FROM AUTHOR]

Cooperative diversity systems are wireless communication systems designed to exploit cooperation among users to mitigate the effects of multipath fading. In fairly general conditions, it has been shown that these systems can achieve the diversity order of an equivalent multiple-input multiple-output (MIMO) channel and, if the node geometry permits, virtually the same outage probability can be achieved as that of the equivalent MIMO channel for a wide range of applicable signal-to-noise ratio (SNR). However, much of the prior analysis has been performed' under the assumption of perfect timing and frequency offset synchronization. In this paper, we derive the estimation bounds and associated maximum a posteriori estimators for frequency offset estimation in a cooperative communication system. We show the benefit of adaptively tuning the frequency of the relay node in order to reduce estimation error at the destination. We also derive an efficient estimation algorithm, based on the correlation sequence of the data, which has mean squared error close to the Cramér-Rao Bound (CRB). [ABSTRACT FROM AUTHOR]

In this paper, we present an opportunistic packet scheduling algorithm based on buffer management (OSBM) over the downlink of a packet cellular network. OSBM is a channel-dependent scheduling algorithm with a provable delay bound. It is able to provide differentiated services to both real-time and nonreal-time applications. Particularly, these features of OSBM are achieved through a novel buffer management scheme. Since this buffer management scheme does not involve any complex online computation, OSBM is very efficient and easy to implement in an operational environment. We also present a new analytical approach for performance analysis of opportunistic scheduling in wireless networks based on the proposed concept of effective downlink capacity (EDC). This approach attempts to adapt the service curve tool for deterministic quality-of-service analysis to the wireless environment, and the concept of the EDC serves to bridge the deterministic method and the stochastic nature of the wireless link. Using this approach, the explicit expression of the delay bound of the OSBM algorithm is obtained. Simulation results are presented to demonstrate the effectiveness of the proposed opportunistic scheduling algorithm. [ABSTRACT FROM AUTHOR]