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As an important complement and enhancement technique for cellular communication systems, the device-to-device (D2D) technique has exhibited a number of benefits in terms of, for instance, offering an improved spectral efficiency, enabling a reduced transmit power and providing an enhanced channel capacity, etc. However, a severe interference may be imposed on the conventional cellular users by the activated D2D links, thus, substantially eroding the performance of the former. In this paper, we propose an interference limited area (ILA) based D2D-management scheme along with an appropriately designed power control algorithm for mitigating the above-mentioned interference. We first derive the closed-form expressions of the average coverage probability for both the cellular and D2D links under the proposed ILA scheme, followed by proposing a resource-allocation algorithm subject to a power control mechanism. Numerical results show that the proposed ILA scheme is capable of outperforming the conventional scheme in terms of both the coverage probability (i.e., for both cellular and D2D links) and the sum data rate, particularly in the scenarios with a high D2D density and a high signal-to-interference-plus-noise ratio. [ABSTRACT FROM AUTHOR]

It is a promising solution for real-time multitarget tracking to implement particle cardinality balanced multitarget multi-Bernoulli (CBMeMBer) filters in hardware platforms. However, this solution is difficult to materialize since there is a contradiction between the time-varying number of Bernoulli intensity components in CBMeMBer filters and the limited number of particles in hardware platforms. Moreover, real-time hardware implementation requires a resampling procedure that is suitable for parallel processing, while the existing parallel resampling algorithms oversimplify this procedure, resulting in estimation performance degradation. In this paper, we propose an optimization algorithm of particle allocation to overcome the above-mentioned contradiction, and a parallel resampling algorithm to improve the estimation performance. Numerical experiments demonstrate the effectiveness of the proposed algorithms in multitarget tracking. [ABSTRACT FROM AUTHOR]

With the advent of the Internet of things, massive machine-type communications (mMTC) have become one of the most important requirements for next generation communication systems. In the mMTC scenarios, grant-free nonorthogonal multiple access on the transmission side and compressive sensing-based multi-user detection (CS-MUD) on the reception side are a promising solution because many users sporadically transmit small data packets at low rates. In this paper, we propose a novel CS-MUD algorithm for the active user and data detection in the mMTC systems. The proposed scheme consists of the maximum a posteriori probability (MAP) based active user detector (MAP-AUD) and the MAP-based data detector (MAP-DD). By exchanging the extrinsic information between MAP-AUD and MAP-DD, the proposed algorithm improves the active user detection performance and the reliability of the data detection. In addition, we extend the proposed algorithm to exploit group sparsity. By jointly processing the multiple received data with common activity, the proposed algorithm dramatically enhances the active user detection performance. We show by numerical experiments that the proposed algorithm achieves a substantial performance gain over existing algorithms. [ABSTRACT FROM AUTHOR]

In the air–ground propagation channel, multipath propagation severely affects the performance of the communication, navigation, and surveillance systems used in civil aviation. To gain a deeper understanding of the air–ground channel, we are interested in the locations of objects causing multipath propagation. Therefore, in this paper we propose and experimentally validate an algorithm to localize reflectors causing multipath components based on channel sounding data collected using omnidirectional antennas. The algorithm relies on superresolution parameter estimation and tracking as well as on a localization algorithm. Using both simulations and channel sounding data collected from flight trials, we demonstrate the ability to reliably localize the reflectors causing multipath components. [ABSTRACT FROM AUTHOR]

This paper considers a heavy loaded full-duplex (FD) small cell consisting of one FD base station and multiple half-duplex users where the number of subchannels is less than the number of uplink and downlink users. With the objective of maximizing the total sum-rate, a joint power allocation, and user pairing problem is formulated. To solve this problem, a novel decomposition method is proposed, which decouples the power allocation and user pairing problem into two subproblems. It is proven that the optimal solution of subproblems is the optimal solution of the original problem. Then, optimal algorithms are developed for the two subproblems. Numerical results show that the proposed algorithm achieves better performance compared with the baselines of the greedy algorithm and random pairing algorithm. [ABSTRACT FROM AUTHOR]

Video streaming over vehicular networks has considerable benefits for both road safety and entertainment. In this paper, the scalable video coding over cooperative vehicular networks is investigated to improve the performance of video streaming services. We formulate a joint optimization problem to answer questions about the number of video layers that should be transmitted for each vehicle, the selection of relay vehicles to assist destination vehicles, and the assignment of radio resources to direct and cooperative communications. We decouple the problem into two subproblems, i.e., the quality of service (QoS)-driven resource allocation (QoSRA) subproblem and the layer selection (LS) subproblem. We solve the QoSRA subproblem by converting it into a generalized maximum concurrent flow problem, and propose a tabu search-based metaheuristic algorithm for the LS subproblem. The simulation results verify the efficiency of the proposed scheme and provide some insight into the tradeoff between system performance and computation complexity. [ABSTRACT FROM AUTHOR]

The hidden terminal problem degrades the uplink system throughput of wireless local area network seriously. In this paper, we propose the optimum allocation (OA) scheme of the location-based virtual sector (VS) method, which solves the hidden terminal problem without massive overheads like request-to-send and clear-to-send (RTS/CTS) packets. The VS method forms sectors virtually to make short-distance mobile terminal (MT) groups using MTs’ location information. In the group, all MTs can sense the transmission of all other MTs. In the proposed method, rough time slot control is implemented for intersector control, which does not need a highly functional centralized controller. The proposal OA scheme of the VS method improves the fairness among MTs by optimizing active periods of VS according to the number of MTs in each VS. By computer simulations, we show that the proposed method can increase the system throughput from the RTS/CTS and improve fairness among MTs even in the condition that positioning error is 1/10 of cell radius. [ABSTRACT FROM AUTHOR]

In this paper, a two-hop nonregenerative multiple-input multiple-output relay system is investigated, where the relay node relies on harvesting the radio frequency energy transferred from the source node to forward information from source to destination. We consider the time switching (TS) protocol between wireless information and energy transfer. In particular, we propose a more general energy consumption constraint at the source node during the information and energy transfer, which includes the constant power constraints used in existing works as special cases. We study the joint optimization of the source precoding matrices, the relay amplifying matrix, and the TS factor to maximize the source–destination mutual information (MI). The optimal structure of the source and relay matrices is derived, which reduces the original transceiver optimization problem to a simpler power allocation problem. We propose a primal decomposition based algorithm and an upper bound based approach to efficiently solve the power allocation problem. The first algorithm achieves the global optimum, whereas the latter one has a lower computational complexity. Numerical simulations show that both proposed algorithms yield much higher system MI and better rate-energy tradeoff than existing approaches. [ABSTRACT FROM AUTHOR]

We propose a Bayesian framework for the problem of multiuser dectection in the context of an unknown and time-varying number of active users. In this paper, we combine orthogonal frequency-division multiplexing modulation with multiantenna reception to mitigate both the asynchronism and frequency-selectivity of the wireless medium. We develop a method for user identity and data detection with joint channel parameter estimation, performed on a per-OFDM block basis to account for a highly dynamic random-access channel. Based on a factor graph approach, we derive an inference algorithm based on message-passing resulting in an iterative code-aided receiver. We show that a suitable Gaussian approximation leads to a complexity that increases only linearly with the maximum number of users. Computer simulations show that the proposed iterative receiver has a low probability of erroneous activity detection, while maintaining a high antenna diversity order for active users. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of underwater visible light communications (UVLC), from channel characterization, performance analysis, and effective transmission and reception methods. To this end, we first simulate the fading-free impulse response (FFIR) of UVLC channels using Monte Carlo numerical procedure to take into account the absorption and scattering effects; and then to characterize turbulence effects, we multiply the aforementioned FFIR by a fading coefficient modeled as a lognormal random variable (RV) for weak oceanic turbulence. Based on this general channel model, we analytically study the bit error rate (BER) performance of UVLC systems with binary pulse position modulation (BPPM). In the next step, to mitigate turbulence effects, we employ multiple transmitters and/or receivers, i.e., we apply spatial diversity technique over UVLC links. Closed-form expressions for the system BER are provided, when an equal gain combiner is employed at the receiver side, thanks to the Gauss–Hermite quadrature formula as well as approximation to the sum of lognormal RVs. We further apply saddle-point approximation, an accurate photon-counting method, to evaluate the system BER in the presence of shot noise. Both laser-based collimated and light emitting diode based diffusive links are investigated. Additionally, in order to reduce the intersymbol interference (ISI), introduced by the multiple-scattering effect of UVLC channels on the propagating photons, we also obtain the optimal multiple-symbol detection (MSD) algorithm, as well as the suboptimal generalized MSD (GMSD) algorithm. Our numerical analysis indicate good matches between the analytical and photon-counting results implying the negligibility of signal-dependent shot noise, and also between the analytical results and numerical simulations confirming the accuracy of our derived closed-form expressions for the system BER. Besides, our results show that spatial diversity significantly mitigates fading impairments while (G)MSD considerably alleviates ISI deterioration. [ABSTRACT FROM AUTHOR]

A software-defined wireless local area network (SDWLAN) has gained significant interest recently from both the academic and industrial communities and initiated a paradigmatic reconsideration on the stereotyped management and control of current WLAN due to its flexibility and programmability. However, with the proliferation of mobile devices, efficient client association with quality of service (QoS) guarantees in the high-density SDWLAN is a very challenging issue. In this paper, we study the client association problem in the SDWLAN with new features, including centralized association, global network state awareness, seamless handoff, and flow-level association. We formulate the client association in a high-density scenario as an optimization problem aiming to minimize the interpacket delay of individual flows, based on an unsaturated and heterogeneous Markovian analytical model. Furthermore, we interpret the optimization problem as an NP-hard supermodular set function minimization problem, which is solved by two low-complexity heuristic methods, namely the greedy algorithm and the bounded local search algorithm. Through simulations, we demonstrate the effectiveness of our proposed client association solution. [ABSTRACT FROM AUTHOR]

This paper proposes a distance-based two-stage ecological (eco-) driving scheme by using estimation of distribution algorithms (EDA) and model-based prediction of traffic conditions. Before departure, the optimal speed profile for an entire route is generated by an EDA in combination with speedup approaches for a faster computing time, which can optimize the complex cost function of ecodriving without simplification within a reasonably short computing time. This optimization is performed in a distance domain for localizing changes in the optimal speed profile due to traffic conditions while driving. After departure, by taking the optimal speed profile and actual traffic conditions into consideration, the speed profile for a short term—to only the next location—is adapted. In order to reliably react to actual traffic conditions, additional points are interpolated into the long-term distance step and fine control of speeds at the additional points is established, which is based on a predictive model for estimating the spacing to the preceding vehicle. The proposed ecodriving system is evaluated in two types of route conditions, and its results are compared with the optimization result by the quadratic programming method. This comparison shows that an EDA can generate a speed profile with better optimization results in terms of fuel efficiency and driving time within a shorter computing time. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the cross-layer resource optimization for wireless relay networks with dynamic node-selfishness information. The degree of intrinsic selfishness (DeIS) and the degree of extrinsic selfishness (DeES) of the relay node (RN) are defined as the effects of its own residual energy resource and the incentive in an incentive mechanism, respectively. A model of two-timescale node-selfishness dynamics is constructed to describe the time-varying characteristics of the RN's DeIS and DeES. Based on the two-timescale node-selfishness dynamics of the RNs, a two-timescale resource-optimization dynamical algorithm (TRODA) is employed to control the transmit powers of both RNs and end users (EU), as well as the flow rates of the data packets injected by all EUs. Meanwhile, the stability and the tracking error of the TRODA under the two-timescale node-selfishness dynamics are analyzed by Lyapunov theory. Our simulation results demonstrate that the two-timescale optimization algorithm is stable and has trivial tracking error. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the energy efficiency of downlink transmissions in heterogeneous networks. Our objective is to satisfy the rate requirement of users while maximizing the energy efficiency of the network. We employ the fractional frequency reuse (FFR) scheme to increase the energy efficiency of downlink transmissions and to eliminate outages for the cell-edge users. We formulate the joint cell-center boundary selection for FFR, scheduling, and power allocation problems. This formulation gives us a mixed discrete (selection of the cell-center boundary selection for FFR and scheduling) and continuous (power allocation) optimization problem which is hard to solve jointly. In order to solve this problem, we propose a three-stage resource allocation algorithm. In the first stage, we propose a dynamic method to determine the cell-center region boundaries. In the second stage, we employ the Lagrangian-directed scheduler algorithm to incorporate the rate requirements of users. The third stage solves the power allocation subproblem using the Levenberg–Marquardt method combined with dual decomposition. In order to make the base stations further reduce intercell interference, interference pricing mechanism is applied. This scheme penalizes the utility of a base station with the interference it creates. The performance of the proposed algorithm is simulated in a long-term evolution (LTE) network simulation tool. Our numerical results reveal that significant gains in terms of energy efficiency can be achieved with the proposed algorithm. The outage probability is also significantly reduced. [ABSTRACT FROM AUTHOR]

A nonisolated single-stage on-board charger for electric vehicles has been proposed to increase system efficiency and power density in previous works. However, its ability to achieve high efficiency is limited by variations in the electric utility and battery, especially during the step-down operation. This paper proposes an advanced control algorithm that improves system efficiency in the step-down mode by controlling each switch asymmetrically using a phase-shift control. The proposed algorithm consists of only one controller, which prevents transient states from causing variations in the controller. The algorithm decreases the magnitude and ripple of the inductor current, which improves the charging efficiency by approximately 4.1% over at the 3.7-kW full load that of the conventional algorithm in the step-down mode, and measured total harmonic distortion and power factor are 3.2% and 0.995, respectively. [ABSTRACT FROM AUTHOR]

The ability of mobile devices to be connected to more than one radio node at the same time enables mobile devices to transmit and receive traffic to and from multiple paths. This ability helps to increase the average mobile device data rate and to improve the network reliability. Load balancing among multiple paths become a key factor to avoid network congestion, nevertheless it requires efficient techniques to split traffic without adding more delay or generating too much packet reordering for delay-sensitive traffic. In this paper, we address two key issues in the context of uplink wireless mobile networks: 1) how to accurately split traffic among multiple paths and 2) how to minimize the end-to-end delay without increasing packet reordering. We propose delay-aware load balancing algorithm (DALBA), a novel strategy that splits traffic at the granularity of the packet. DALBA aims to minimize the splitting error (SE) and the end-to-end delay difference by effectively using all of the available paths. We analyze DALBA's performance through extensive simulations using H.264 video traffic. Numerical results demonstrate that DALBA outperforms previous algorithms in terms of SE, end-to-end delay and peak signal-to-noise ratio while keeping packet reordering to a suitable low value. [ABSTRACT FROM AUTHOR]

Relay technology is a candidate for extending the coverage or enhancing the throughput of next-generation cellular systems. In the downlink of a Long Term Evolution Advanced (LTE-A) relay network, a relay node (RN) normally reserves a small buffer for each user equipment (UE) such that the RN can minimize the number of forwarding packets during UE handover. The small buffer and a mismatch of the data rates between the access link and the relay link may result in buffer overflow for some UE and in buffer underflow for the other UE served by the same RN. This paper presents a simple analytical model to illustrate the buffer-overflow and buffer-underflow problems in the downlink of an LTE-A relay network. A dynamic flow control algorithm (DFCA) is then proposed to minimize the buffer-overflow and buffer-underflow probabilities. The proposed DFCA is designed to minimize the feedback signaling overhead by dynamically adjusting the window size and the feedback frequency based on the relevant measures obtained from individual UE. Simulation results showed that most of the flow control schemes can effectively prevent the buffer-overflow problem. However, only DFCA can provide lower buffer-underflow probabilities and higher throughput for most UEs versus what the other flow control schemes can do. [ABSTRACT FROM PUBLISHER]

The polynomial expansion (PE) multiuser detector can iteratively approximate the linear decorrelating and MMSE multiuser detectors. This is a very promising approach since the complexity of the PE detector is considerably less than that of the decorrelating and MMSE detectors. The concept of the PE multiuser detector is a weighted matrix polynomial for which optimal weighting has been suggested in the literature. Unfortunately, the optimal weights apply only to a specific correlation matrix. As soon as the correlation between the users changes (and hence also the correlation matrix), a new set of optimal weights has to be calculated. The calculation of these weights is computationally very intense. In this paper, an approach is presented where the weights are predefined and apply for all matrices. Furthermore, a normalization factor is needed to ensure convergence. It will be shown how this factor has to be chosen to obtain the optimal convergence speed. For the optimal normalization factor the minimum and maximum eigenvalues are needed. A low complexity and accurate method to estimate these eigenvalues is derived which can be applied to all correlation matrices and therefore to any code division multi. pie access (CDMA) scenario. Hence, the matrix-dependent optimal normalization factor can easily be calculated and ensures a good bit error rate (BER) performance, even if the correlation between the users changes quickly (e.g., in time-variant channels). Further[H more, it will be shown how to enhance the PE detector such that it has a high near-far resistance. Additionally, for the first time it can be proven that the approximation error of the proposed detector diminishes exponentially with the number of iterations. Finally, simulations verify the fast convergence of the proposed PE detector and its flexible usage in a variety of scenarios. [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]