The futuristic sixth-generation (6-G) networks will empower ultrareliable and low latency communications (URLLC), enabling a wide array of mission-critical applications such as mobile edge computing (MEC) systems, which are largely unsupported by fixed communication infrastructure. To remedy this issue, unmanned aerial vehicle (UAV) has recently come to the limelight to facilitate MEC for internet of things (IoT) devices as they provide desirable line-of-sight (LoS) communications compared to fixed terrestrial networks, thanks to their added flexibility and 3-D positioning. In this article, we consider UAV-enabled relaying for MEC systems for uplink transmissions in 6-G networks, and we aim to optimize mission completion time subject to the constraints of resource allocation, including UAV transmit power, UAV CPU frequency, decoding error rate, blocklength, communication bandwidth, and task partitioning as well as 3-D UAV positioning. Moreover, to solve the nonconvex optimization problem, we propose three different algorithms, including successive convex approximations, altered genetic algorithm (AGA), and smart exhaustive search. Thereafter, based on time-complexity, execution time, and convergence analysis, we select AGA to solve the given optimization problem. Simulation results demonstrate that the proposed algorithm can successfully minimize the mission completion time, perform power allocation at the UAV side to mitigate information leakage and eavesdropping as well as map a 3-D UAV positioning, yielding better results compared to the fixed benchmark submethods. Lastly, subject to 3-D UAV positioning, AGA can also effectively reduce the decoding error rate for supporting URLLC services.

The exponential growth of traffic in mobile networks is leading to increased pressure on the infrastructure of mobile networks and in particular on their backhaul networks. It is more critical than ever to carefully plan backhaul networks. In this paper, we formulate and solve the problem of hierarchical wireless backhaul network design. In formulating our problem, we cover different requirements, namely: topology simplicity, network resiliency, and link reliability. We formulate the problem as an Integer Linear Programming (ILP) problem, allowing us to solve the problem to optimality. Furthermore, we provide a graph theory-based algorithm that allows solving the problem over a large scale. The proposed algorithm exploits the properties of the graph that represents the network. The results of our evaluations in various network scenarios demonstrate the efficiency of our ILP formulation and the proposed algorithm in keeping the backhaul network simple, resilient, and reliable. Using a practical channel propagation model and different node densities that are representative of small-scale and large-scale urban environments, our results also show that even with high resiliency requirements, the network traffic can be backhauled with only 5-10% of the nodes for the considered densities. Our results also demonstrate that our algorithm leads to near-optimal solutions in different scenarios.

In this paper, we analyze the weather information for 14 waterbodies from geographical areas with different meteorological characteristics. We estimate the sub-hourly instances of the evaporation duct height (EDH) throughout a period of 10 years. Then, considering the frequency range 1 to 6 GHz, based on the parabolic equation method, we analyze the quality for a presumed shore-to-ship link throughout 100 km range. We evaluate the maximum range that can be supported for different reliability requirements and we focus specifically on analyzing the gain that can be obtained when antenna height and/or band diversity are used. It was found that for high reliability requirements, the antenna height at the shore is the main factor on deciding the maximum communication range that can be maintained. On the other hand, for applications that tolerate delay and work seasonally on an opportunistic basis, the evaporation duct statistics is the main factor deciding the likelihood of increasing the link range and establishing over-the-horizon communications.

This article describes a design for a frequency synthesizer architecture based on a phase-locked loop (PLL) for avionic software-defined radio (SDR) applications at up to 9 GHz. Three basic architectural schemes: wide range voltage-controlled oscillator (VCO), single sideband (SSB) mixing, and multiple VCOs can be used to extend the frequency ranges. This article compares these schemes through quantitative evaluation to select the best synthesizer architecture to use according to the application specs. The chosen scheme is an optimized combination of a single VCO and a single SSB mixer. Using a quadrature VCO (QVCO) with a switched capacitor (SC) bank, the synthesizer provides a wide frequency band of operation ranging from 100 MHz to 9 GHz covering several avionic communication applications and several existing wireless standards’ frequency requirements. The proposed QVCO is able to generate in-phase and quadrature-phase signals spread into a frequency band between 6 and 9 GHz providing a tuning range of 40% at a center frequency of 7.5 GHz. The QVCO exhibits a phase noise of −107 dBc/Hz, at a 1-MHz offset frequency, while generating a 8-GHz carrier frequency. Its power consumption is of 3.4 mW. With a loop bandwidth of 120 kHz, the frequency synthesizer generates a phase noise, measured at 8 GHz, of −106.4 dBc/Hz at a 1-MHz frequency offset. The overall power consumption of the synthesizer to generate a 140-MHz carrier frequency is 26.57 mW from a 1.2-V supply. The frequency synthesizer is implemented in 0.13-$\mu \text{m}$CMOS technology and occupies an active area of$0.72 \times 0.72$mm2.

We consider the downlink of an unmanned aerial vehicle (UAV) assisted cellular network consisting of multiple cooperative UAVs, whose operations are coordinated by a central ground controller using wireless fronthaul links, to serve multiple ground user equipments (UEs). A problem of jointly designing UAVs’ positions, transmit beamforming, as well as UAV-UE association is formulated in the form of mixed integer nonlinear programming (MINLP) to maximize the sum UEs’ achievable rate subject to limited fronthaul capacity constraints. Solving the considered problem is hard owing to its non-convexity and the unavailability of channel state information (CSI) due to the movement of UAVs. To tackle these effects, we propose a novel algorithm comprising of two distinguishing features: (i) exploiting a deep Q-learning approach to tackle the issue of CSI unavailability for determining UAVs’ positions, (ii) developing a difference of convex algorithm (DCA) to efficiently solve for the UAV’s transmit beamforming and UAV-UE association. The proposed algorithm recursively solves the problem of interest until convergence, where each recursion executes two steps. In the first step, the deep Q-learning (DQL) algorithm allows UAVs to learn the overall network state and account for the joint movement of all UAVs to adapt their locations. In the second step, given the determined UAVs’ positions from the DQL algorithm, the DCA iteratively solves a convex approximate subproblem of the original non-convex MINLP problem with the updated parameters, where the problem’s variables are transmit beamforming and UAV-UE association. Numerical results show that our design outperforms the existing algorithms in terms of algorithmic convergence and network performance with a gain of up to 70%.

In this work, we consider the downlink of an unmanned aerial vehicle (UAV) assisted cellular network consisting of multiple cooperative UAVs, whose operations are coordinated by a central ground controller using the fronthaul communications, to serve multiple ground users. A problem of jointly designing UAV's location, transmit beamforming, as well as UAV-user association is formulated in the form of mixed integer nonlinear programming (MINLP) to maximize the sum user achievable rate while considering the constraints of limited fronthaul capacity. Solving the formulated problem is computationally hard owing to the its non-convex nature and the unavailability of channel state information (CSI) due to the undetermined and flexible movement of UAVs. To tackle these effects, we propose a novel algorithm exploiting the deep Q-learning approach to take the hassles of unavailable CSI for determining UAV's location and invoking the difference of convex (DC) based optimization method to efficiently solve for the UAV's transmit beamforming and UAV-user association given the determined UAV's location. The algorithm recursively solves the formulated problem until convergence. Numerical results show that our design outperforms the existing work in terms of algorithmic convergence and network performance and achieve a gain of up to 70% compared to the existing algorithms.

Smart metering infrastructure (SMI) is the core component of the smart grid (SG) which enables two-way communication between consumers and utility companies to control, monitor, and manage the energy consumption data. Despite their salient features, SMIs equipped with information and communication technology are associated with new threats due to their dependency on public communication networks. Therefore, the security of SMI communications raises the need for robust authentication and key agreement primitives that can satisfy the security requirements of the SG. Thus, in order to realize the aforementioned issues, this paper introduces a lightweight and secure authentication protocol, "LiSA", primarily to secure SMIs in SG setups. The protocol employs Elliptic Curve Cryptography at its core to provide various security features such as mutual authentication, anonymity, replay protection, session key security, and resistance against various attacks. Precisely, LiSA exploits the hardness of the Elliptic Curve Qu Vanstone (EVQV) certificate mechanism along with Elliptic Curve Diffie Hellman Problem (ECDHP) and Elliptic Curve Discrete Logarithm Problem (ECDLP). Additionally, LiSA is designed to provide the highest level of security relative to the existing schemes with least computational and communicational overheads. For instance, LiSA incurred barely 11.826 ms and 0.992 ms for executing different passes across the smart meter and the service providers. Further, it required a total of 544 bits for message transmission during each session.

Because deep neural networks (DNNs) rely on a large number of parameters and computations, their implementation in energy-constrained systems is challenging. In this paper, we investigate the solution of reducing the supply voltage of the memories used in the system, which results in bit-cell faults. We explore the robustness of state-of-the-art DNN architectures towards such defects and propose a regularizer meant to mitigate their effects on accuracy. Our experiments clearly demonstrate the interest of operating the system in a faulty regime to save energy without reducing accuracy.

We study the downlink of a limited fronthaul capacity cloud-radio access networks (C-RANs). Three energy efficiency metrics, namely, global energy efficiency (GEE), weighted sum energy efficiency (WSEE), and energy efficiency fairness (EEF) are maximized by jointly designing transmit beamforming, remote radio head (RRH) selection, and RRH-user association. Furthermore, we incorporate a rate-dependent fronthaul power model, in which the fronthaul power consumption is proportional to the user sum rate. The formulated problems are difficult to solve. Our first contribution is to customize a branch and reduce and bound (BRB) method based on monotonic optimization to find globally optimal solutions for the three energy efficiency maximization problems. Subsequently, for a more practical approach, we propose a unified framework based on successive convex approximation (SCA) method that can be applied to all the considered problems. Our novelty lies in the equivalent transformations leading to more tractable problems that are amenable to the SCA. Specifically, appropriate continuous relaxation and convex approximation techniques are employed to arrive at a sequence of second-order cone programs (SOCPs) for which dedicated solvers are available. Then, a post-processing algorithm is devised to obtain a high-performance feasible solution from the continuous relaxation. The numerical results demonstrate that the proposed SCA-based algorithms converge rapidly and achieve near-optimal performance as well as outperform the known methods. They also highlight the importance of the rate dependent fronthaul power model in designing the energy efficient C-RANs.

Coded orthogonal frequency-division multiplexing (COFDM) is a popular modulation technique for wireless communication that guarantees reliable transmission of data over noisy wireless channels. However, a major disadvantage in implementing it is its resulting high peak to average power ratio (PAPR). Including forward error correction (FEC) in the orthogonal frequency division multiplexing (OFDM) system enables the avoidance of transmission errors. Nevertheless, the selected code may impact the value of PAPR. The objective of this paper is to analyze the impact of FEC on the PAPR for the COFDM system based on the autocorrelation of the signal, before the inverse fast Fourier transform (IFFT) block in the COFDM system, the evaluation of the complementary cumulative distribution function (CCDF) of PAPR, and the bit error rate (BER). The autocorrelation of the COFDM system is calculated based on a Markov chain model. From the results, we can reach a conclusion on the characteristics we need to consider in order to choose the codes relating to the PAPR performance in the COFDM system.

Inherent interfering signals generated by the underlying elements found in power substations have been known to span over consecutive noise samples, resulting in bursty interfering noise samples. In the impulsive noise environments, we elaborate a space-sensitive technique using multiple-input multiple-output (MIMO), which is particularly well suited in these usually very difficult situations. We assume the availability of channel state information (CSI) at the transmitter to achieve typical MIMO system gains in ad hoc mode. In this paper, we show that more than 10 dB gains are obtained with the most efficient system that we propose for achieving smart grid application requirements. On the one hand, the results obviously illustrate that the max-dmin precoder associated with the rank metric coding scheme is especially adapted to minimize the bit error rate (BER) when a maximum likelihood (ML) receiver is employed. On the other hand, it is shown that a novel node selection technique can reduce the required nodes transmission energies.

We consider the downlink virtualized cloud-radio access networks (C-RANs) with limited capacity fronthaul. A novel virtual computing resource allocation (VCRA) which can dynamically split the users workload into smaller fragments to be served by virtual machines is presented. Under the proposed scheme, we aim at maximizing the network energy efficiency (EE) by a joint design of virtual computing resources, transmit beamforming, remote radio head (RRH) selection, and RRH-user association, considering rate dependent fronthaul power consumption model. The formulated problem is generally combinatorial and NP-hard. For an appealing solution approach, we resort to the difference of convex algorithm (DCA) to solve the continuous relaxed problem. In particular, Lipschitz continuity is derived for non-convex parts to arrive at a sequence of convex quadratic programs, which can be solved efficiently by modern convex solvers. Finally, a post-processing procedure is proposed to obtain a high-performance feasible solution from the continuous relaxation. Numerical results show that the proposed algorithms converge rapidly and the proposed scheme significantly improves the network EE compared to the existing schemes.

We consider the virtualization technique in the downlink transmission of limited fronthaul capacity cloud-radio access networks. A novel virtual computing resource allocation (VCRA) method which can dynamically split the users workload into smaller fragments to be served by virtual machines is presented. Under the proposed scheme, we aim at maximizing the network energy efficiency by a joint design of virtual computing resources, transmit beamforming, remote radio head (RRH) selection, and RRH-user association. Moreover, we construct a more realistic fronthaul power consumption model, which is directly proportional to users' rate transmitted by the corresponding RRHs. The formulated problem is combinatorial and difficult to solve in general. Our first contribution is to customize a branch-and-reduce-and-bound method to attain a globally optimal solution. To compute a high-quality approximate solution, a standard routine is used to deal with the continuous relaxation of the original problem. However, the proposed continuous relaxation is non-convex which implies another challenge. For a practically appealing solution approach, we resort to a local optimization method, namely the difference of convex algorithm. Our second contribution is on the use of Lipschitz continuity to arrive at a sequence of convex quadratic programs, which can be solved efficiently by modern convex solvers. Finally, a post-processing procedure is proposed to obtain a high-performance feasible solution from the continuous relaxation. Extensive numerical results demonstrate that the proposed algorithms converge rapidly and achieve near-optimal performance as well as outperform other known methods. Moreover, we numerically show that the VCRA scheme significantly improves the system energy efficiency compared to the existing schemes.

This paper considers the downlink transmission of cloud-radio access networks with limited fronthaul capacity constraint. Unlike the existing approaches where power of fronthaul is a quadratic or linear function of respective variables, we consider a more practical model where the power consumed by fronthaul depends on the rate served by the corresponding remote radio head (RRH). Then, we formulate a joint design of RRH selection, RRH-user association, and transmit beamforming for the problem of energy efficiency maximization. The formulated problem is a mixed-integer nonconvex program, which is generally NP-hard. For this nonconvex program, we leverage successive convex approximation (SCA) method to develop efficient iterative algorithms to find a high performance. Particularly, we iteratively approximate the continuous nonconvex constraints by conic ones so that the problem obtained at each iteration is a mixed-integer second order cone programming (MI-SOCP) for which dedicated solvers are available. To further reduce the computational complexity, an algorithm based on continuous relaxation and post-processing is proposed. Results show that our proposed algorithms converge faster and outperform known solutions.

This paper considers the downlink transmission of cloud-radio access networks (C-RANs) with limited fronthaul capacity. We formulate a joint design of remote radio head (RRH) selection, RRH-user association, and transmit beamforming for simultaneously optimizing the achievable sum rate and total power consumption, using the multi-objective optimization concept. Due to the non-convexity of per-fronthaul capacity constraints and introduced binary selection variables, the formulated problem is combinatorial and nonconvex, which is generally NP-hard. To deal with this difficulty, we develop a new framework which iteratively approximates the continuous non-convex constraints by convex ones in the form of second order cones. The problem arrived at each iteration is a mixed integer second order cone programming which can be solve optimally and efficiently. Numerical results show that our proposed algorithms converge rapidly and outperform the existing solutions.

Integrating wireless sensor networks (WSNs) in power substations for the future smart grid is growing in interest. Nevertheless, high voltage (HV) substations are harsh environments. In particular, impulsive noise needs to be taken into account. To tackle the constraints of these environments, we propose in this paper an efficient wideband channel coding scheme. The proposed approach consists in a robust physical layer based on the integration of several very interesting error correcting codes with Orthogonal Frequency Division Multiplexing (OFDM). Using real measurements of impulsive noise, the impact of rank metric (RC), Low Rank Parity Check codes (LRPC) and polar codes is evaluated in terms of BER and PER in a realistic multipath channel. The results show that using this coding scheme is very efficient in mitigating the bursty nature of impulsive noise while having a quite low level of complexity.

This paper derives the equations leading to the analytic expression of the frequency spectrum at the output of multi-bit delta-sigma modulators afflicted by component mismatch in the digital-to-analog converter used in the feedback path. The effect of the mismatch is modeled as an error signal added to an ideal digital-to-analog converter. The frequency content of this error signal is derived from the probability density functions of the input signal and the shaped quantization noise. The analysis is applied to band-limited Gaussian input signals. Several simulation results are reported, showing a 0.3 dB accuracy of the analytic expressions whenever the number of quantization bits is higher than two.

In this paper, a fully integrated frequency synthesizer architecture, designed in 0.13 μm CMOS technology, for avionic software defined radio (SDR) applications is presented. The synthesizer provides a carrier frequency range from 100 MHz to 12 GHz covering the avionic communication applications and existing wireless standards. The switched capacitors voltage controlled oscillator (VCO) used realizes a wide tuning range from 8 GHz to 12 GHz. The VCO phase noise simulated at 12 GHz is −125 dBc/Hz at a 10 MHz offset frequency with a power consumption of 1.4 mW. The transient phase locked loop (PLL) response shows a settling time of 3.92 μs whereas the PLL loop bandwidth is of about 600 kHz. Furthermore, the synthesizer exhibits a phase noise, simulated at 12 GHz, of −104 dBc/Hz at a 1 MHz frequency offset with an overall power consumption of 14.88 mW, comparing favourable to other documented schemes, but with four time the frequency range.

Vehicular Ad-Hoc networks (VANETs) have become an interesting research area especially with growing need to improve the quality of service and the performance of vehicle-to-vehicle (V2V) wireless communication systems. This paper analyses a peer-to-peer V2V wireless communication system in the presence of interference. In this vein, the performance metrics of the proposed system are investigated over Nakagami-m fading channels where no interference cancellation is assumed at the receiver side. In particular, the mathematical expression of the probability density function (PDF) of the resultant signal-to-interference-plus-noise ratio (SINR) of the system is derived. The closed-form expression of the PDF derived here lays the foundation for deriving analytical expressions for the moment generating function and the probability of the average bit error rate of the system under consideration. Finally, the closeness of our analytical expressions are corroborated through Monte Carlo simulation results.

With the exponential growth of demand in terms of traffic and data rates, one of the most promising potential features of the fifth generation (5G) of mobile network is the use of the millimeter-wave (mmWave) frequency bands. Although the available bandwidth in the mmWave frequency is significantly large, high frequencies pose several challenges in term of propagation loss, hence suitable models for these frequencies use are needed. Due to significant pathloss, the higher mmWave bands are better suited to the operation of short ranged small cells, while the lower frequency bands are appropriate for outdoors users. We propose in this paper, a spatial frequency reuse model for two-tier ultra-dense networks, where a dedicated band is allocated to inner and outer regions of macrocells and small-cells in order to properly exploit the advantages and limits of the mmWave frequencies. The performance of this scheme are evaluated both analytically in terms of coverage probability, and through system-simulation in terms of achieved throughput, and compared to traditional microwave systems and mmWave models with no reuse. We reach an average of 20% of coverage gain with more than 70% of the users having a throughput greater than 500 Mbps and nearly 40% greater than the target 1 Gbps.

HetNets have attracted many attentions these last five years, as they are a promising solution to improve network capacity and indoor coverage. In these emerging networks, technical challenges remain, principally user mobility management through handover decision. Consequently, we propose a novel utility-based handover algorithm to improve the performance of the mobility management in a two-tier network, where a mobile user (MU) enters the coverage of a femtocell. The main idea of the approach is the design of new utility functions through a specific quality of service (QoS)- aware objective function. Thse utility functions are used to compute optimally the handover offset in a given handover decision policy. The main purpose of the offset is to counterbalance the large asymmetry in the transmit power of macrocell and femtocell. Then, we bring some performance comparison on our handover approach vs. proposed approaches in literature and get results in terms of expected reference signal received power (RSRP), assignment probabilities to the macro base station (MBS) and to the femto base station (FBS), handover probability and the number of resulting handoffs. Numerical results show a considerable gain of more than 90% related to the user assignment probability to FBS while the number of handoffs remains acceptable.

By relying on a wireless backhaul link, relay stations enhance the performance of cellular networks by achieving the required reliability at a savings of infrastructure cost and energy, but at the same time, they can aggravate the interference issue. In this paper, we analyze the maximum energy gain provided by relays for several coding schemes, including energy-optimized partial decode-forward relaying, accounting for the additional relay-generated interference to neighboring cells. First, we define new energy-efficient service areas for relaying in log-normal shadowing environments and propose easily computable and tractable models to predict: 1) the probability of energy-efficient relaying; 2) the spatial distribution of energy consumption within a cell; and 3) the average interference generated by relays. These models allow finding the optimal location and the number of relays with significantly lower complexity and execution time, as compared with system simulations. Finally, we analyze the gains provided by more advanced relaying coding schemes and propose a map showing how to use them across a cell, as a function of their respective circuitry consumption. The inclusion of more advanced relaying schemes not only alleviates the interference issue, but also leads to a reduction in the number of relays required for the same rate and outage performance.

This paper investigates the problem of communication relay establishment for multi-ground units using an unmanned aircraft. It is required to drive the aircraft to the optimal position for communication relay without knowledge of ground units' positions. As an alternative to positions information, two measurements are employed for each ground unit, the signal strength and its angle of arrival. Two navigation laws are proposed, the first employs all measured signals whereas the second only employs the two smallest signals. Simulations are carried out to show the effectiveness of the proposed approaches.

With the exponential growth of small cells in the next generation of mobile networks, the Macrocell User Equipments (MUEs) located in the vicinity of the Femtocell Access Points (FAPs) suffer from high downlink interferences. The hybrid access mode of FAPs has shown promising features to mitigate these interferences but the FAPs prioritize the closed suscribers group (CSG) users over the public users. In this paper, we propose a framework for macrocell-femtocell cooperation in order to protect harmed public users whether it is from a prioritized serving FAP or from interfering neighbouring femtocells. When the harmed MUE connects to a nearby FAP, we model the interference management and resource allocation problem as a game with coalition structure (GCS) where the paired FAP and MUE form a priori union. Two coalitional values are identified and compared to compute the payoff of the GCS, namely the Solidarity-Shapley value and the Weighted Owen value. For the MUEs who failed to connect to the nearby FAP, a canonical game is played with the Solidarity value as imputation, to protect the harmed MUEs from powerful FAPs in the game. We show through extensive simulations that the combination of theses schemes compared to other solutions and access modes of the art, shows the best performances for the MUEs and Femtocell user equipments (FUEs) of the system in term of throughput and fairness.

This paper considers the power minimization problem in downlink of cloud radio access networks with limited fronthaul capacity. A joint design of beamforming, remote radio head (RRH) selection and RRH-user association that explicitly takes into account per- fronthaul capacity constraints is considered. The problem of interest is in fact a combinatorial program which is generally NP- hard. We naturally write the considered problem as a mixed integer program by introducing binary selection variables. The challenge is that even if these binary selection variables are relaxed to be continuous, the resulting problem is still nonconvex. For such a problem, finding a high- quality solution, rather than an optimal one, is a more realistic goal. Towards this end we propose two iterative algorithms to deal with combinatorial nature of the joint design problem. In the first method, by novel transformations, we iteratively approximate the continuous nonconvex constraints by convex conic ones using successive convex approximation framework. More explicitly the problem arrived at each iteration of the first method is a mixed-integer second order cone program (MISOCP) for which dedicated solvers are available. The second method is a simplified variant of the first one where we further relax the binary variables in each iteration to be continuous. That is to say, the second method merely requires solving a sequence of SOCPs. After convergence, we then perform a postprocessing procedure on the relaxed selection variables to search for a high-performance solution. Numerical results are presented to demonstrate the superiority of the proposed algorithms over existing methods based on sparse-inducing norm.

This paper presents wireless sensor network unmanned aerial vehicle (WSN-UAV) system for military remote monitoring and surveillance. Large scale WSN is deployed in a battlefield or wide hostile region to collect information of interest and send it to a UAV. Collaborative beamforming (CB) is used to achieve the ground-to-air transmissions. An automatic dependent surveillance-broadcast (ADS-B) based multilateration is used to obtain the UAV location and tracking information. It is found that a minimum distance between the UAV and the WSN is required for proper operation of the CB due to the precision of the multilateration and the movement of the UAV.

A cognitive detect and avoid radar system based on chaotic UWB-MIMO waveform design to enable autonomous UAV navigation is presented. A Dirichlet-process-mixture-model (DPMM)-based Bayesian clustering approach to discriminate extended targets and a change-point (CP) detection algorithm are applied for the autonomous tracking and identification of potential collision threats. A DPMM-based clustering mechanism does not rely upon any a priori target scene assumptions and facilitates online multivariate data clustering/classification for an arbitrary number of targets. Furthermore, this radar system utilizes a cognitive mechanism to select efficient chaotic waveforms to facilitate enhanced target detection and discrimination. We formulate the CP mechanism for the online tracking of target trajectories, which present a collision threat to the UAV navigation; thus, we supplement the conventional Kalman-filter-based tracking. Simulation results demonstrate a significant performance improvement for the DPMM-CP-assisted detection as compared with direct generalized likelihood-ratio-based detection. Specifically, we observe a 4-dB performance gain in target detection over conventional fixed UWB waveforms and superior collision avoidance capability offered by the joint DPMM-CP mechanism.

Fractional Frequency Reuse (FFR) is considered to provide enhancement in total throughput and an important reduction of the outage probability in two-tier macrocell-femtocell networks. However the allocation in FFR can create high cross-tier interferences to users located in the boundaries of the various zones. We propose a FFR scheme to alleviate the downlink cross-tier interference for users in these particular zones, joint with a QoS- aware analytical model to derive the blocking probabilities for different cell zones. The optimal parameters for cell channel partitioning in the proposed FFR-scheme are integrated to enhance the proposed system. Numerical results demonstrate the performance enhancement of the proposed joint FFR allocation and admission control scheme. Compared to current FFR and admission control strategies, our scheme permits to increase overall traffic by up to 40 % at cell center and 30 % at cell edge, for any given blocking probability.

Supporting a high quality multimedia transfer has become a significant challenge for telecommunication industry. Numerous efforts have been done in different network layers to improve system performance based on real-time traffic transmission. The main contribution of this paper is to introduce a downlink packet scheduler for IEEE 802.16 standard MAC layer that improves the QoS of real-time traffic while not deteriorating the performance of non-real-time data. This scheduler categorizes the packets into three priority levels. Unlike the existing priority- based schedulers, in this model a budget calculation process is provisioned to prevent the low priority data from starving. The scheduler has been developed in a simulated IEEE 802.16 network scenario in NS3, hosting mixed types of traffic. Extensive simulation experiments show that the proposed scheduling model prevents bandwidth misuse which significantly improves the QoS parameters of real-time traffic comparing to a conventional packet scheduler.The scheme and conclusions are readily extendable to other 4G standards using the described mapping mechanism.

This paper presents experimental results of overwater radio path loss in the 4.4 to 5.0 GHz band. These measurements involve horizontal and vertical polarizations. Based on electromagnetic theory, a deterministic two ray model that mimics measurements is developed. The model can predict the received power level for all distances lower and higher than the critical distance. The model is consistent with measurements in MIMO modes using any kind of linear polarized antennas.

Relay-based cellular networks are likely to play an important role in the race for energy efficiency. However, potential gains greatly depend on how relay stations are deployed within the cell. Using a geometrical model for energy-efficient analysis, we investigate the impact of the number and location of relays on energy consumption, and its dependence on the relay coding scheme and the propagation environment, i.e. the pathloss and the line-of-sight conditions. In addition to the transmit energy, we account for the economic cost of relay deployment, as well as the overhead energy dissipated at each relay stations due to data processing and network maintenance. We then bring out four key trade-offs which balance the cost and flexibility of relay deployment, the energy efficiency and the coverage extension.

The performance analysis of a relaying system implementing modulation diversity is investigated in this work. Our relaying system is quite novel, since, we assume that the relay always transmits during the relaying phase, i.e., is never silent. Whereas in the other related works assume that the relay first decodes its received signal and upon a successful decoding, transmits to the destination, i.e., the relay is silent upon an unsuccessful decoding. Modulation diversity creates diversity by transforming the angle of a classical modulation to create signal points with distinct components, followed by subsequent interleaving over the components. Assuming transmission over independent Rayleigh fading channels and maximum likelihood detection on the reordered signals at the receiver, the analysis starts with finding the probability density function of the end-to-end signal-to-noise (SNR) ratio. Then, a tight upper-bound expression for the error probability is obtained. Following that, we achieve the exact outage probability of the relaying system under-study. Then, exact and upper-bound expressions for the system capacity are presented. Finally, numerical results and comparisons with Monte Carlo simulations are presented.

This study carries out the first‐ever investigation of the analysis of a cooperative decode‐and‐forward (DF) relay network with chaos shift keying (CSK) modulation. The performance analysis of DF‐CSK in this study takes into account the dynamical nature of chaotic signal, which is not similar to a conventional binary modulation performance computation methodology. The expression of a lower bound bit error rate (BER) is derived in order to investigate the performance of the cooperative system under independently and identically distributed Gaussian fading wireless environments. The effect of the non‐periodic nature of chaotic sequence leading to a non‐constant bit energy of the considered modulation is also investigated. A computation approach of the BER expression based on the probability density function of the bit energy of the chaotic sequence, channel distribution and number of relays is presented. Simulation results prove the accuracy of the authors BER computation methodology.

Optimum ordering strategies for the coded Vertical Bell Labs Layered Space-Time (V-BLAST) architecture with capacity achieving temporal codes on each stream are analytically studied, including 4 different power/rate allocation strategies among data streams. Compact closed-form solutions are obtained for the case of zero-forcing (ZF) V-BLAST with two transmit antennas and necessary optimality conditions are found for the general case. The optimal rate allocation is shown to have a major impact (stronger streams are detected last) while the optimal power allocation does not alter the original Foschini ordering (stronger streams are detected first). Sufficient conditions for the optimality of the greedy ordering are established: it is optimal for the ZF V-BLAST under an optimal rate allocation with two transmit antennas at any SNR and with any number of antennas in the low and high SNR regimes. It satisfies the necessary optimality conditions for larger systems at any SNR and is nearly-optimal in many cases. An SNR gain of ordering is introduced and studied, including closed-form expressions as well as lower and upper bounds and the conditions for their achievability. For the minimum mean square error (MMSE) V-BLAST under an optimal rate allocation, any ordering is shown to deliver the same system capacity. All the results also apply to a multiple-access channel with the successive interference cancelation receiver.

The performance of a relay-based cellular network is greatly affected by the relay location within a cell. Existing results for optimal relay placement do not reflect how the radio propagation environment and choice of the coding scheme can impact system performance. In this paper, we analyze the impact on relaying performance of node distances, relay height and line-of-sight conditions for both uplink and downlink transmissions, using several relay coding schemes. Our first objective is to propose a geometrical model for energy-efficient relay placement that requires only a small number of characteristic distances. Our second objective is to estimate the maximum cell coverage of a relay-aided cell given power constraints, and conversely, the averaged energy consumption given a cell radius. We show that the practical full decode-forward scheme performs close to the energy-optimized partial decode-forward scheme when the relay is ideally located. However, away from this optimum relay location, performance rapidly degrades and more advanced coding scheme, such as partial decode-forward, is needed to maintain good performance and allow more freedom in the relay placement. Finally, we define a trade-off between cell coverage and energy efficiency, and show that there exists a relay location for which increasing the cell coverage has a minimal impact on the average energy consumed per unit area.

In this paper, a multi user Multi-Carrier Differential Chaos Shift Keying (MC-DCSK) modulation is presented. The system endeavors to provide a good trade-off between robustness, energy efficiency and high data rate, while still being simple. In this architecture of MC-DCSK system, for each user, chaotic reference sequence is transmitted over a predefined subcarrier frequency. Multiple modulated data streams are transmitted over the remaining subcarriers allocated for each user. This transmitter structure saves energy and increases the spectral efficiency of the conventional DCSK system.

A new Multi-Carrier Differential Chaos Shift Keying (MC-DCSK) modulation is presented in this paper. The system endeavors to provide a good trade-off between robustness, energy efficiency and high data rate, while still being simple compared to conventional multi-carrier spread spectrum systems. This system can be seen as a parallel extension of the DCSK modulation where one chaotic reference sequence is transmitted over a predefined subcarrier frequency. Multiple modulated data streams are transmitted over the remaining subcarriers. This transmitter structure increases the spectral efficiency of the conventional DCSK system and uses less energy. The receiver design makes this system easy to implement where no radio frequency (RF) delay circuit is needed to demodulate received data. Various system design parameters are discussed throughout the paper, including the number of subcarriers, the spreading factor, and the transmitted energy. Once the design is explained, the bit error rate performance of the MC-DCSK system is computed and compared to the conventional DCSK system under multipath Rayleigh fading and an additive white Gaussian noise (AWGN) channels. Simulation results confirm the advantages of this new hybrid design.

We analyze coding for energy efficiency in relay channels at a fixed source rate. We first propose a half-duplex decode-forward coding scheme for the Gaussian relay channel. We then derive three optimal sets of power allocation, which respectively minimize the network, the relay and the source energy consumption. These optimal power allocations are given in closed-form, which have so far remained implicit for maximum-rate schemes. Moreover, analysis shows that minimizing the network energy consumption at a given rate is not equivalent to maximizing the rate given energy, since it only covers part of all rates achievable by decode-forward. We thus combine the optimized schemes for network and relay energy consumptions into a generalized one, which then covers all achievable rates. This generalized scheme is not only energy-optimal for the desired source rate but also rate-optimal for the consumed energy. The results also give a detailed understanding of the power consumption regimes and allow a comprehensive description of the optimal message coding and resource allocation for each desired source rate and channel realization. Finally, we simulate the proposed schemes in a realistic environment, considering path-loss and shadowing as modelled in the 3GPP standard. Significant energy gain can be obtained over both direct and two-hop transmissions, particularly when the source is far from relay and destination.

Convexity properties of error rates of a class of decoders, including the maximum-likelihood/min-distance one as a special case, are studied for arbitrary constellations, bit mapping, and coding. Earlier results obtained for the additive white Gaussian noise channel are extended to a wide class of noise densities, including unimodal and spherically invariant noise. Under these broad conditions, symbol and bit error rates are shown to be convex functions of the signal-to-noise ratio (SNR) in the high-SNR regime with an explicitly determined threshold, which depends only on the constellation dimensionality and minimum distance, thus enabling an application of the powerful tools of convex optimization to such digital communication systems in a rigorous way. It is the decreasing nature of the noise power density around the decision region boundaries that ensures the convexity of symbol error rates in the general case. The known high/low-SNR bounds of the convexity/concavity regions are tightened and no further improvement is shown to be possible in general. The high-SNR bound fits closely into the channel coding theorem: all codes, including capacity-achieving ones, whose decision regions include the hardened noise spheres (from the noise sphere hardening argument in the channel coding theorem), satisfy this high-SNR requirement and thus has convex error rates in both SNR and noise power. We conjecture that all capacity-achieving codes have convex error rates. Convexity properties in signal amplitude and noise power are also investigated. Some applications of the results are discussed. In particular, it is shown that fading is convexity-preserving and is never good in low dimensions under spherically invariant noise, which may also include any linear diversity combining.

We propose three energy-optimal distributed schemes for the half-duplex relay channel with block fading to maintain a desired source rate. We consider both network energy consumption and consumption of the relay alone, assuming only local channel knowledge. Then, we combine both into a generalized distributed energy-efficient scheme. In these schemes, the source uses message splitting and allocates resources dynamically, such that direct transmission, decode-forward or partial decode-forward is performed at each block, depending on the channel quality. The optimal distributed power allocation is computed from the corresponding centralized scheme by using an estimate of the relay consumption. Compared to decode-forward with no message splitting as often used in distributed designs, the proposed schemes significantly decrease the peak power and provide up to 15% average energy gain for the network consumption and a minimum of 3.3dB gain for the relay consumption.

In this paper, implementation of discrete-time chaotic generators widely used in digital communications is studied and evaluated. The study focuses on power consumption, resource usage, and maximum execution frequency of implementations for two common Field Programmable Gate Arrays (FPGAs). While the Bernoulli map ranks first in all three aspects, results show significant ranking differences among the other chaotic generators. Results were obtained by first implementing the chaotic generators in a high level register to transistor level description language and then using tools from FPGA manufacturers to obtain the resource usage as well as estimate the other desired characteristics.

The feasibility of having chaos-based communication in a MIMO system is presented. A promising chaotic symbolic dynamics modulation is chosen, and an Alamouti space-time code scheme is used with 2 transmit and 2 receiver antennas. The diversity technique is combined with chaotic modulation to improve the performance of the system. The performance of the proposed system is evaluated, and then the analytical BER expression is derived.

Motivated by the increasing importance of knowing which operating systems are running in a given network, we evaluated operating system discovery (OSD) tools. The results indicated a serious lack of accuracy in current OSD tools. This thesis proposes a new approach to OS discovery which addresses the limitations of existing tools and leads to a more flexible, less intrusive, and much more accurate tool. Moreover, unlike existing OSD tools which are completely ad hoc, our approach is formal and follows the principles of diagnosis problem solving. This formalism allows us to: (a) characterize the complexity of OSD; (b) use well-tested algorithms and (c) benefit from numerous possible extensions. To fully address the needs of OSD, we generalize the theory of diagnosis with a query-based extension. This extension leads to a spectrum of test selection algorithms to solve each query.

This paper deals with the allocation of resources to the MAC layers of frequency hopped wireless networks. The research has been carried out on new efficient scheduling methods for robust systems to handle distortion and reception. The frequency and time slots are variable during the same point to point or point to multipoint communication. The chosen time intervals are small enough so as to limit distortion. By combining random packets with priority settings such as signal strength and band allocation queue length, the total capacity of the link was increased up to twice that offered by random allocations. This is functional as long as there is band availability; a better latency is also obtained.

This study presents a spread-spectrum chaos-based communication system with polarisation diversity in a multipath channel. The propagation model takes into account the random direction angle of arrival and the polarisation orientation assigned to each version of the transmitted signal. To improve the performance of the proposed system, the receiver integrates monopoles with different orientations and no space diversity. Once the number of antennas is defined, many antenna positions are simulated, and then the optimal position is deduced to improve the performance of the system. To demodulate the received signal, a RAKE receiver is used for multi-antenna processing. An analysis is carried out leading to the analytical expression of the system bit error rate (BER). Simulation results show first that our system performance is improved with the use of this new receiver, and the perfect match observed between simulations and analytical BER expressions confirms the exactitude of our computation approach. Finally, the performance of our studied system is compared and discussed to that of a conventional spread-spectrum system using gold codes as spreading sequences.

Cognitive radio ad hoc networks (CRAHNs) have become a popular network architecture for connecting mobile nodes thanks to the flexibility and adaptability of such type of network. In this paper, we propose a novel scheme for efficient routing design in CRAHNs. The proposed routing scheme firstly forms a simple directed graph for the given physical network. Using the simple directed graph, multiple optimal routing paths can be computed for a pair of cognitive radio users. An optimal routing path minimizes both the hop count and the adjacent hop interference. Examples are used to demonstrate the performance and efficiency of the proposed CRAHN routing technique. Results are also compared with other existing routing techniques for CRAHNs.

In this paper, we propose a robust synchronization technique for an asynchronous spread spectrum communication system based on chaotic symbolic dynamics modulation. A back-ward iteration of the chaotic map is used to avoid the problem of sensitivity to initial conditions of the chaotic generator. The proposed system integrates a spread spectrum unit, which is used to increase transmission security and to achieve the transmission in a multi-user case. The synchronization technique is assessed in terms of probability of detection and of probability of false alarm. Simulation results prove that the proposed system can achieve phase synchronization with a low signal-to-noise ratio.

This paper analyzes the performance of chaotic communications in a MIMO system. The robustness of chaos-based communications systems makes Differential Chaos Shift Keying (DCSK) the preferred modulation choice. In order to improve the performance of such a system, the Alamouti space-time code is used for 2 transmit and 2 receive antennas. A new approach for computing the bit-error-rate (BER) performance is provided, and an analytical BER expression is derived. The approach used explores the dynamic properties of chaotic sequences and takes into account the fact that the bit energy varies from one transmitted bit to the next. Simulation results confirm the accuracy of this approach.

We explore the issue of the network energy efficiency in relay channels. We first propose a half-duplex decode-forward coding scheme. We then optimize the power allocation to minimize the total power consumption while maintaining a desired source rate. We show that this scheme significantly outperforms direct and two-hop transmissions. Moreover, it reduces the relay energy consumption by up to 7dB, which is beneficial for shared relay stations, and smooths out transmit power peaks, which simplifies interference management.

Fourth generation standards will provide interoperability between different wireless access technologies. This will be partly enabled by Vertical Handoff (VHO) which ensures a continuation of service when the access technology is switched, e.g. from a Wireless Local Area Network (WLAN) to a Cellular Network (CN) and vice versa. In this paper, we propose a VHO decision algorithm based on scalar Kalman filtering. Criteria such as probability of false handoff, number and position of handoffs are used to evaluate and compare our work with existing handoff algorithms based on filtering techniques. Our algorithm is shown to limit by 40 percent, in a worst case scenario, the probability of false handoff when compared to other HO algorithms.

This paper carries out the first-ever study of the feasibility of using chaos shift keying (CSK) in a Multiple-Input, Multiple-Output (MIMO) channel. To that end, an Alamouti space time code scheme is combined with the CSK system for 2 transmit and 2 receiver antennas. Once the design of CSK-MIMO system is presented, the performance of the proposed system is analyzed in a mono-user case. An exact computation approach of the BER expression based on the probability density function of the bit energy of the chaotic sequence is presented. Simulation results prove the accuracy of our BER computation methodology.

This paper investigates a Decode-and-Forward (DF) two-hop relaying system in which Orthogonal Frequency Division Multiplexing (OFDM) is used. The relay forwards the message received from the source on a subset of available subchannels in the second time slot. Firstly, a pairing and selecting algorithm is proposed. Then, power will be allocated to the both base station and relay station under individual power constraints in order to maximize the capacity. The pairing and selecting algorithm and resource allocation is based on instantaneous channel state information (ICSI). Finally, the simulation results show that selective relaying combined with subcarrier pairing and power allocation will improve the system capacity to a considerable extent.

In this paper, a new way to predict the performance of single user differential chaos shift keying communication system over an m-distributed fading channel is presented. Since the Gaussian approximation used to compute the performance leads to inaccurate results especially for low spreading factor, this new approach based on the chaos bit energy distribution gives accurate results. Computer simulations verify the precision of our approach to compute the performance of this chaos-based communication system.

Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which also includes coding under maximum-likelihood decoding. Under this generic setting, the pairwise probability of error and bit error rate are shown to be convex functions of the SNR and noise power in the high SNR/low noise regime with explicitly-determined boundary. Any code, including capacity-achieving ones, whose decision regions include the hardened noise spheres (from the noise sphere hardening argument in the channel coding theorem) satisfies this high SNR requirement and thus has convex error rates in both SNR and noise power. We conjecture that all capacity-achieving codes have convex error rates.

In this paper, we investigate joint overlay and underlay power allocation for OFDM-based cognitive radio (CR) systems. Unlike existing work in literature where power is allocated in either overlay only or underlay fashion, we propose schemes which perform a joint allocation. Specifically, the total capacity of CR is maximized while maintaining a total power budget and keeping the interference introduced to the primary user (PU) band below a threshold. As the complexity of optimal scheme can be high, a suboptimal scheme has also been proposed. Presented simulation results show that a significant gain in transmission capacity is achieved by using joint overlay and underlay allocation scheme as compared to either overlay or underlay only scheme. Further, numerical results show that even our proposed suboptimal scheme outperforms either overlay or underlay only scheme.

This letter presents a novel approach for deriving a lower bound on the outage probability of interference cancellation receiver in ad hoc networks for a class of channel fading. Our approach is based on the following observation: under the power decay law model for large-scale fading with an exponent ¿ strictly greater than 2, the sum of the interferences at a receiver has the same order as the strongest signal. This feature still holds when the small-scale fading has a finite 2/¿-fractional moment. This fact is used to develop an approximation which is also a compact lower bound on the outage probability.

Motivated by a recent surge of interest in convex optimization techniques, convexity/concavity properties of error rates of the maximum likelihood detector operating in the AWGN channel are studied and extended to frequency-flat slow-fading channels. Generic conditions are identified under which the symbol error rate (SER) is convex/concave for arbitrary multidimensional constellations. In particular, the SER is convex in SNR for any one- and two-dimensional constellation, and also in higher dimensions at high SNR. Pairwise error probability and bit error rate are shown to be convex at high SNR, for arbitrary constellations and bit mapping. Universal bounds for the SER first and second derivatives are obtained, which hold for arbitrary constellations and are tight for some of them. Applications of the results are discussed, which include optimum power allocation in spatial multiplexing systems, optimum power/time sharing to decrease or increase (jamming problem) error rate, an implication for fading channels (¿fading is never good in low dimensions¿) and optimization of a unitary-precoded OFDM system. For example, the error rate bounds of a unitary-precoded OFDM system with QPSK modulation, which reveal the best and worst precoding, are extended to arbitrary constellations, which may also include coding. The reported results also apply to the interference channel under Gaussian approximation, to the bit error rate when it can be expressed or approximated as a nonnegative linear combination of individual symbol error rates, and to coded systems.

This paper studies the performance of antenna array processing in distributed multiple access networks without power control. The positions of nodes are determined by a Poisson point process. Desired and interfering signals are subject to both path-loss (with an exponent greater than 2) and to independent Rayleigh fading. Using these assumptions, we derive the exact closed form expression for the cumulative distribution function of the output signal-to-interference-plus-noise ratio when optimum combining is applied. This results in a pertinent measure of the network performance in terms of the outage probability, which in turn provides insights into the network capacity gain that could be achieved with antenna array processing. We present and discuss examples of applications, as well as some numerical results.

We study the end-to-end capacity of a cooperative relaying scheme using OFDM modulation, under power constraints for both the base station and the relay station. The relay uses an amplify-and-forward cooperative relaying technique to retransmit messages on a subset of the available subcarriers. The power used in the base station and the relay station transmitters is allocated in such a manner that the overall system capacity is maximized. The subcarrier selection and power allocation are obtained based on convex optimization formulations and an iterative algorithm. The proposed technique outperforms nonselective relaying schemes over a range of relay power budgets.

Abstract In this paper, we present a finite‐signal‐to‐noise ratio (finite‐SNR) framework to establish tight bounds on the diversity‐multiplexing tradeoff of a multiple input multiple output (MIMO) system. We focus on a more realistic propagation environment where MIMO channel fading coefficients are correlated and where SNR values are finite. The impact of spatial correlation on the fundamental diversity‐multiplexing tradeoff is investigated. We present tight lower bounds on the outage probability of both spatially uncorrelated and correlated MIMO channels. Using these lower bounds, accurate finite‐SNR estimates of the diversity‐multiplexing tradeoff are derived. These estimates allow to gain insight on the impact of spatial correlation on the diversity‐multiplexing tradeoff at finite‐SNR. As expected, the diversity‐multiplexing tradeoff is severely degraded as the spatial correlation increases. For example, a MIMO system operating at a spectral efficiency ofRbps/Hz and at an SNR of 5 dB in a moderately correlated channel, achieves a better diversity gain than a system operating at the same spectral efficiency and at an SNR of 10 dB in a highly correlated channel, when the multiplexing gainris greater than 0.8. Another interesting point is that provided that the spatial correlation channel matrix is of full rank, the maximum diversity gain is not affected by the spatial correlation. Copyright © 2009 John Wiley & Sons, Ltd.

Recent technological advances in code division multiple access (CDMA) with multiuser detection (MUD) allow to consider this technology for future wireless Ad Hoc networks. Due to the fundamentally different physical layer architecture, application of MUD in Ad Hoc networks requires novel approaches for medium access control (MAC) and scheduling mechanisms in order to take advantage of the new features. This paper proposes a new MAC and scheduling paradigm which addresses three design issues: distributed dynamic code assignment that avoids code collision, distributed scheduling scheme that provides fairness among contending nodes, and organization of the data transmission based on multiuser detection. Simulation model is used to verify the performance gains from the increased spectrum reuse due to multiuser reception and from the reduced interference due to multiuser detection. This is done by comparisons with existing MAC paradigms, such as CSMA/CA and parallel CDMA.

This paper introduces the Tabu Search optimization algorithm to solve the regenerator allocation problem in translucent networks. The problem consists of finding the minimum number of regenerator nodes which primarily affects the cost of the translucent network. The problem is first solved with an ILP formulation to find the optimal solution without taking into consideration its time performance. The optical reach limit due to the dispersion compensation module and full (static) traffic demand with a 1+1 protection scheme are considered in the network model. The proposed algorithm is then compared with two other heuristics: the maximum infeasibility reduction (MIR) algorithm and the maximum regeneration demand (MRD) algorithm. Numerical results show that the Tabu Search procedure either outperforms or equals the performance of the reference algorithms, while having a lower implementation complexity and comparable convergence speed.

The channel capacity and the channel statistics are both important performance metrics to consider for appropriate design of wireless systems. In tactical mobile ad hoc networks environment, the capacity and the second order statistics are investigated based on an optimized physical layer simulation tool which includes tactical scenarios generator and propagation modeler. The possible link data rate is stemmed from the average channel capacity analysis between all pair of nodes. And based on the minimum data rate requirement for typical services (web, audio and video streaming, VoIP, videoconference), connectivity graphs are constructed. Moreover, level cross rate (ICR) and average duration of fade (ADF) are simulated as function of double mobility degree and the results show how the double mobility affects the second order channel statistics and the error probability.

In this paper, we introduce a spectrum holes detection approach, which combines blind modulation classification, angle of arrival estimation and number of sources detection. We perform eigenspace analysis to determine the number of sources, and estimate their angles of arrival. In addition, we classify detected sources as primary or secondary users with their distinct second-order/one-conjugate cyclostationarity features. Extensive simulations carried out indicate that the proposed system identifies and locates individual sources correctly, even at -4 dB SNR.

We address the capacity of a discrete-time memoryless Gaussian channel, where the channel state information (CSI) is neither available at the transmitter nor at the receiver. The optimal capacity- achieving input distribution at low signal-to-noise ratio (SNR) is precisely characterized, and the exact capacity of a non-coherent channel is derived. The derived relations allow to better understanding the capacity of non-coherent channels at low SNR. Then, we compute the non- coherence penalty and give a more precise characterization of the sub- linear term in SNR. Finally, in order to get more insight on how the optimal input varies with SNR, upper and lower bounds on the non-zero mass point location of the capacity-achieving input are given.

Multiuser detection based Medium Access Control (MAC) can give significant gains in throughput and Quality of Service (QoS) when applied to wireless Ad Hoc networks. To realize these gains, one has to implement a distributed neighborhood scheduling that provides the desired performance objectives. In this paper, we propose an approach for analyzing and comparing optimal or suboptimal distributed neighborhood scheduling schemes with different objectives. Then, we demonstrate the viability of this approach by implementing a scheduling scheme that uses Start Time Fair Queuing (STFQ) algorithm and by comparing its performance to a published suboptimal distributed scheduling for multiuser detection based MAC. In particular, the numerical results show that the delay performance of the priority voice packets can be significantly improved by using STFQ algorithm.

In this paper we present an analysis of the outage probability in DS-CDMA ad hoc network using interference cancellation receiver under a path loss attenuation channel model. A simple conceptual tool that gives a closed form approximation of the outage probability with variable precision on the interference cancellation is developed.

Variable environments in ad hoc networks require a joint control of physical (PHY) and medium access control (MAC) layers resources in order to optimize performance. In this paper, we propose a framework to perform such cross-layer control and optimization. The PHY layer and cross-layer engine estimate and predict the channel variations to evaluate the linkpsilas future packet error rate (PER), for MAC layer optimization. We consider high capacity code division multiple access (CDMA) ad hoc networks where nodes are equipped with matched filter receivers.

The capacity of a discrete-time memoryless Gaussian channel, where the channel state information (CSI) is neither available at the transmitter nor at the receiver, is addressed. A closed form expression of the optimal capacity-achieving input distribution at low signal-to-noise ratio (SNR) is derived, and the exact capacity of a non-coherent Single Input Single Output (SISO) channel is given. The derived relations allow to better understanding the capacity of non-coherent channels at low SNR. Then, we compute the non-coherence penalty and give a more precise characterization of the sub-linear term in SNR. Finally, upper and lower bounds on the capacity of a multiple input multiple output (MIMO) channel are derived in terms of its counterpart SISO channel capacity. We show that these bounds are sufficient to characterize the MIMO channel capacity at low SNR.

Recent technological developments in code division multiple access (CDMA) with multiuser detection (MUD) make multiple packets reception a more appropriate model for the physical layer of future wireless networks. To take advantage of the new features, a shift of responsibility from transmitters to

Outage and error rate performance of the ordered BLAST with more than 2 transmit antennas is evaluated for i.i.d. Rayleigh fading channels. A number of lower and upper bounds on the 1st step outage probability at any SNR are derived, which are further used to obtain accurate approximations to average block and total error rates. For m Tx antennas, the effect of the optimal ordering at the first step is an m-fold SNR gain. As m increases to infinity, the BLER decreases to zero, which is a manifestation of the space-time autocoding effect in the V-BLAST. While the sub-optimal ordering (based on the before-projection SNR) suffers a few dB SNR penalty compared to the optimal one, it has a lower computational complexity and a 3 dB SNR gain compared to the unordered V-BLAST and can be an attractive solution for low-complexity/low-energy systems. Uncoded D-BLAST exhibits the same outage and error rate performance as that of the V-BLAST. An SNR penalty of the linear receiver interfaces compared to the BLAST is also analytically evaluated.

The impact of spatial correlation on the performance limits of multielement antenna (MEA) channels is analyzed in terms of the diversity-multiplexing tradeoff (DMT) at finite signal-to-noise ratio (SNR) values. A lower bound on the outage probability is first derived. Using this bound accurate finite-SNR estimate of the DMT is then derived. This estimate allows to gain insight on the impact of spatial correlation on the DMT at finite SNR. As expected, the DMT is severely degraded as the spatial correlation increases. Moreover, using asymptotic analysis, we show that our framework encompasses well-known results concerning the asymptotic behavior of the DMT.

This paper introduces a new game theoretic formulation for the design and routing of resilient and translucent networks. An integer linear programming (ILP) modeling is also presented and used as a reference to evaluate the game theoretic algorithm performances. Both formulations include primary and link-disjoint protection paths pre-calculation and take into account the system maximal optical reach distance. Numerical results show that the game theoretic formulation considerably decreases the optimization time and provides near optimal solutions, in term of required number of regenerator nodes.

The goal of operating system (OS) discovery is to learn which OS is running on a distant computer. There are two main strategies for OS discovery: active and passive. Each of them has advantages as well as drawbacks. This paper discusses how answer set programming, a new logic programming paradigm, can be used to address, in a simple and elegant way, the problem of operating system discovery in computer networks by logically specifying the problem and providing solutions through automated reasoning. As a result of using such a knowledge representation framework, it is possible to unify the active and the passive methods to OS discovery in a single hybrid approach that has the advantages of both strategies while being much more versatile. Moreover, this paper presents a proof of concept prototype for hybrid operating system discovery.

Convexity/concavity properties of symbol error rates (SER) of the maximum likelihood detector operating in the AWGN channel (non-fading and fading) are studied. Generic conditions are identified under which the SER is a convex/concave function of the SNR. Universal bounds for the SER 1st and 2nd derivatives are obtained, which hold for arbitrary constellations and are tight for some of them. Applications of the results are discussed, which include optimum power allocation in spatial multiplexing systems, optimum power/time sharing to decrease or increase (jamming problem) error rate, and implication for fading channels.

In general, the performance and radio resource utilization of Ad Hoc networks are limited by half-duplex operation and possible collisions. In this paper, we propose a novel approach for MAC design that practically eliminates collisions and significantly increases the bandwidth utilization. The key element of this approach is the CDMA multiuser detection technology that allows receiving several signals in parallel without inflicting self-interference. These features give a promise of significant performance improvements. The main goal of this paper is to assess the range of this gain when compared to other existing alternatives. In particular, we compare the performance of the proposed multiuser detection based MAC design with MAC design based on IEEE 802.11 concept and with MAC design based on multi-code CDMA with one signal reception by one user at a time.

We present tight upper bounds on the channel mutual information of spatially correlated and uncorrelated multielement antenna (MEA) channels. Using these upper bounds, accurate lower bounds on the outage probability are derived. Similarly, tight upper bounds on the outage rate are obtained. Interestingly, these bounds are even tighter as the spatial correlation increases. Simulation results show that, in a highly correlated channel, the worst gap between our outage probability lower bounds and the exact values (given by simulation) is about 0.2 and 0.3 dBs, respectively for 2 times 2 and 3 times 3 MEA systems. This tightness suggests using the derived lower bounds on the outage probability in order to characterize the performance limits of MEA in terms of the finite-SNR diversity-multiplexing tradeoff in correlated and uncorrelated spatial fading channels.

In general, the performance and radio resource utilization of Ad Hoc networks are limited by half-duplex operation and possible collisions. In this paper, we propose a novel approach for MAC design that practically eliminates collisions and significantly increases the bandwidth utilization. The key element of this approach is the CDMA multiuser detection technology that allows receiving several signals in parallel without inflicting self-interference. These features give a promise of significant performance improvements. The main goal of this paper is to assess the range of this gain when compared to other existing alternatives. In particular, we compare the performance of the proposed multiuser detection based MAC design with MAC design based on IEEE 802.11 concept and with MAC design based on multi-code CDMA with one signal reception by one user at a time.

An intrusion detection system (IDS) is a crucial element of a network security posture. Although there are many IDS products available, it is rather difficult to find information about their accuracy. Only a few organizations evaluate these products. Furthermore, the data used to test and evaluate these IDS is usually proprietary. Thus, the research community cannot easily evaluate the next generation of IDS. Toward this end, DARPA provided in 1998, 1999 and 2000 an intrusion detection evaluation data set. However, no new data set has been released by DARPA since 2000, in part because of the cumbersomeness of the task. In this paper, we propose a strategy to address certain aspects of generating a publicly available documented data set for testing and evaluating intrusion detection systems. We also present a tool that automatically analyzes and evaluates IDS using our proposed data set

The peak factor of a continuous digitally- modulated signal is often analyzed from its samples taken at the Nyquist rate. This, however, may involve a significant error. It has been claimed, based on an illustrative example, that the peak factor of a continuous signal may be arbitrary large while the peak factor of the corresponding sampled signal is limited [Wulich, D., 2000]. A validity of this example has been questioned in [Ermolova, N., 2001; Minn, E., et al., 2001] based on a flaw in [Wulich, D., 2000]. In this paper, we demonstrate that the original illustrative example requires a small modification only to remove the flaw. It is also demonstrated that the continuous peak factor, in its traditional definition, may be arbitrary large while the sampled peak factor and the signal energy are bounded. An upper bound on the continuous peak factor of a BPSK sequence is derived.

We present a tight lower bound on the outage probability of a spatially correlated multielement antenna (MEA) channel. Using this lower bound, an accurate flnite-SNR estimate of the diversity-multiplexing tradeoff over a spatially correlated Rayleigh fading channel is derived. This estimate allows gaining insight on the impact of spatial correlation on the diversity-multiplexing tradeoff at finite SNR. As expected, the diversity multiplexing tradeoff is severely degraded as the spatial correlation increases. For example, a MIMO system operating at a transmission rate of R = rlog2(1+ g ldr eta) bps/Hz, where r is the multiplexing gain, g is the array gain and eta is the SNR at each receive antenna, and an SNR of 5 dB in a moderately correlated channel, achieves a better diversity gain than a system operating at an SNR of 10 dB in a highly correlated channel, when r ges 0.8. Another interesting point is that the maximum diversity gain is unaffected by the correlation, provided that the spatial channel correlation matrix is of full rank.

Abstract — The BLAST algorithm is simple and, hence, popular solution for a signal processing at the MIMO receiver. In this paper, we present a closed-form analytical analysis of the V-BLAST without optimal ordering. A result on the zero-forcing maximum ratio combining weights at each detection step is derived to obtain a number of results: independence of noise, distribution of signal to noise ratio and block or bit error rates. We present a detailed analytical analysis and closed-form expressions for instantaneous and average BER at each detection step, which account for the error propagation and hold true for any modulation format and take simple form in some cases (BPSK). Asymptotic form, for large average SNR, of these expressions is especially simple; the effect of the error propagation in this mode is to increase the total average BER by about 20, which is not catastrophic at all. It is demonstrated that the conventional V-BLAST and QR-decomposition based V-BLAST are essentially identical and have the same performance. Extensive Monte-Carlo simulations validate the analytical results and conclusions. Index Terms—MIMO, V-BLAST, multi-antenna system, BER, outage, fading,

The Bell Labs layered space-time (BLAST) algorithm is simple, and hence, a popular choice for a multiple-input multiple-output (MIMO) receiver. Its bit-error rate (BER) performance has been studied mainly using numerical (Monte Carlo) techniques, since exact analytical evaluation presents serious difficulties. Close examination of the problem of BLAST BER performance analysis reveals that the major difficulty for analytical evaluation is due to the optimal ordering procedure. Hence, we analyze the algorithm performance without optimal ordering. While this is a disadvantage of the analysis, there are certain advantages as well. Exact closed-form analytical evaluation is possible for arbitrary number of transmit and receive antennas in an independent, identically distributed Rayleigh fading channel, which provides deep insight and understanding that cannot be gained using the Monte Carlo approach alone. A result on the maximum ratio combining weights, which is used at each detection step, is derived to obtain a number of results: independence of noise, distribution of signal-to-noise ratio (SNR), and block- or bit-error rates. We present a detailed analysis and expressions for uncoded error rates at each detection step, which hold true for any modulation format and take simple closed form in some cases. Asymptotic form of these expressions for large SNRs is particularly simple. Extensive Monte Carlo simulations validate the analytical results and conclusions

This paper investigates an adaptive M-QAM modulation scheme with constant peak power for which the received signal is divided by the estimated channel gain. Generally, for adaptive modulation schemes, the transmitter adjusts its modulation parameters based on the received power. The receiver estimates channel conditions and sends feedback information via a return channel to the transmitter. In this paper, we consider Rayleigh flat fading channels. At the receiver the fading is estimated using pilot symbols. To cancel the channel impact, we correct the received signal by dividing it by the estimated value of the fading. So, we propose to adjust the modulation level by examining the statistics of the corrected signal. The modulation switching protocol take into account the channel estimation error variance. Since linear region of practical amplifiers is limited, when switching from one modulation scheme to an other, the peak power is kept constant.

In this paper, we present new results on the search and determination of wide-sense convolutional self-doubly orthogonal codes (CSO/sup 2/C-WS) which can be decoded using a simple iterative threshold decoding algorithm without interleaving. For their iterative decoding, in order to ensure the independence of observables over the first two iterations without the presence of interleavers, these CSO/sup 2/C must satisfy specific orthogonal properties of their generator connections. The error performances of CSO/sup 2/C, depend essentially on the number of taps J of the code generators but not on the code memory length. Since the overall latency of the iterative threshold decoding process is proportional to the memory length of the codes, therefore, when searching for the best CSO/sup 2/C-WS of a given J value, the memory length of the codes should be chosen to be as small as possible. In this paper, we present a code-searching technique based on heuristic computer searching algorithms which have yielded the best known CSO/sup 2/C-WS. The construction method for CSO/sup 2/C-WS has provided the best known r=1/2 codes with the shortest memory length having J/spl les/30. Although not very complex to implement, the search method presented here is quite efficient especially in reducing very substantially the execution time required to determine the codes with the shortest spans. Furthermore, in addition to presenting the search results for the codes, error performances obtained by simulation are also provided.

In this paper, we consider the detection of turbo coded symbols in orthogonal frequency division multiplexed (OFDM) systems and propose a turbo detector composed of a turbo decoder and a channel estimator. These modules perform jointly and exchange a soft information through an iterative process. The decoder consists of the maximum a posteriori MAP-BCJR algorithm and the channel estimator is based on the minimum mean square error (MMSE) criterion. The proposed approach allows for the use of all available information, increases the quality of channel estimation and improves the system performance. Simulation results for rate 1/3 turbo code show the efficiency of the proposed detector.

A geometrically based analytical approach to the performance analysis of the V-BLAST algorithm is presented in this paper, which is based on the analytical model of the Gramm-Schmidt process. This approach presents a new geometrical view of the V-BLAST and explains some of its properties in a complete and rigorous form, including a statistical analysis of postprocessing signal-to-noise ratios for a 2/spl times/n system (where n is the number of receive antennas). Closed-form analytical expressions of the vector signal at ith processing step and its power are presented. A rigorous proof that the diversity order at ith step (without optimal ordering) is (n-m+i) is given (where m is the number of transmit antennas). It is shown that the optimal ordering is based on the least correlation criterion and that the after-processing signal power is determined by the channel correlation matrices in a fashion similar to the channel capacity. Closed-form analytical expressions are derived for outage probabilities and average BER of a 2/spl times/n system. The effect of the optimal ordering is shown to be to increase the first step SNR by 3 dB (rather than to increase the diversity order as one might intuitively expect based on the selection combining argument) and to increase the second step outage probability twice.

A novel iterative error control technique based on the threshold decoding algorithm and new convolutional self-doubly orthogonal codes is proposed. It differs from parallel concatenated turbo decoding as it uses a single convolutional encoder, a single decoder and hence no interleaver, neither at encoding nor at decoding. Decoding is performed iteratively using a single threshold decoder at each iteration, thereby providing good tradeoff between complexity, latency and error performance.

Fade depth prediction on airborne line-of-sight communication links is considered. There is no specific model for this scenario at the moment. The two ray multipath model, adapted to a realistic scenario of hilly or mountainous terrain, was used to account for flight and terrain geometry and for antenna parameters. Surprisingly, it was found that (i) in many practically important cases the fade depth depends on the path clearance angle only and (ii) the two-ray model predicts roughly the same fade depth dependence on the path clearance angle as the well-known Olsen-Segal model. This may be considered as a theoretical justification, to the best of our knowledge for the first time, of the path elevation angle factor in that model.

In this paper we present a novel iterative error control technique which circumvents both the complexity and latency shortcomings of the usual turbo codes. It differs from usual turbo coding techniques as it uses a single encoder (hence with no interleaver at the encoding process) and a single decoder. The technique is based on a novel class of orthogonal threshold decodable codes called convolutional self doubly orthogonal codes (CSO/sup 2/C).

The performance of suboptimal convolutional decoding over fading channels is explored. The suboptimal decoding algorithm used is the bidirectional algorithm. By estimating a "decoder weight spectrum" for the decoder, an "equivalent free distance" may be observed. Furthermore, by using this "decoder weight spectrum", useful estimations of the error probabilities are obtained and compared to computer-simulation results in the case of very slow and very fast fading. The resultant curves are shown to be very tightly related. Computer-simulation results are also shown for various signal-to-noise ratios, normalized Doppler spreads, and frame length on three typical fading channels: the Rayleigh fading channel with exponential and Bessel autocorrelation functions and the Rician fading channel with exponential autocorrelation function. We show that considerable gains (up to 4 dB) can be obtained with respect to a similar-complexity Viterbi decoder at a frame error probability P/sub e/=10/sup -3/ and a slightly smaller gain (up to 1.8 dB) at a bit error probability P/sub b/=10/sup -5/.

This paper describes a complete digital radio system model which takes into account the effects of most degradations due to channel conditions and equipment imperfections. System parameters which are taken into consideration include, but are not limited to, the following: modulator imbalance, filter frequency responses, power amplifier nonlinearities, carrier and symbol timing recovery loops, and synthesizer phase noise. The parameters for each module in the radio can be varied, and the end-to-end performance computed. Furthermore, a novel semianalytic method is developed for the purpose of speeding up the simulation leading to the calculation of the bit error rate (BER) versus E/sub b//N/sub o/ for the radio model. This novel technique, when compared with classical semianalytic methods, provides 1 dB improvement in the accuracy of the simulation results. The model accurately predicts the radio performance as measured by BER versus E/sub b//N/sub o/, dispersive fade margin, transmitted frequency spectrum, and transient acquisition responses. Simulation results for 16 QAM and OQPSK systems were compared to measurements on two physical radios. The accuracy of the simulation results was found to be within 0.1 dB in E/sub b//N/sub o/ at a BER of 10/sup -6/ without the RF portions and between 0.2 and 0.45 dB for a complete radio system.

This paper describes the design and the prototyping of a compiling tool for the automated implementation of distributed applications: ALFred. This compiler starts from the formal specification of an application written in ESTEREL and then integrates end-to-end communication functions tailored to the application characteristics (described in the specification); it finally produces a high performance implementation. The paper describes the communication architecture associated with the approach. The compiler consists of a control compiler, also called ALF compiler, and a data manipulation compiler (the ILP compiler) that combines data manipulation functions in an efficient way (the ILP loop). The ALFred compiler has been designed to allow the development and the analysis of non-layered high performance communication architectures based on ALF and ILP.

New designs for soft-decision threshold decoders are developed to significantly reduce the complexity and increase the coding gain as compared to previously proposed architectures. The approximate a posteriori probability (AAPP) decoder considered here is a digital approximation of the a posteriori probability (APP) decoder introduced by Massey (1976). These designs are useful for high-rate self-orthogonal convolutional codes with a long constraint length. The study case considered in this paper is for a rate 23/24, constraint length 4056 code used in a typical microwave digital radio. The new decoder architecture provides a four-fold decrease in complexity and an additional 0.3 dB coding gain as compared to previous designs.>

Two new schemes are presented to improve the error performances of coding and modulation on slow fading channels. The first scheme consists of permuting coordinates of multidimensional modulation and trellis coded modulation (TCM) on interleaved channels. Theoretical and simulation results show that this simple permutation may provide gains of 3.8 dB on slow Rayleigh fading channels for uncoded modulation. It also improves by 5 dB the performance of fully interleaved 16-QAM TCM. The second scheme consists of using coded frequency diversity. Without bandwidth expansion, the signal is spread over different independent fading channels. For two very slow fading channels, where interleaving is impractical and coding usually does not provide any gain, coded diversity and 16-QAM TCM provides gains of 13 dB at a BER of 10/sup -4/.>

New upper bounds on the error performance of coded systems for Rician channels are presented. The fading channels need not be fully interleaved to obtain meaningful performance results. These bounds hold for coherent, differentially coherent and noncoherent demodulation of binary signals. They provide a useful analytical approach to the evaluation of the error performance of convolutional or block coding and they may be generalized to M-ary signals and trellis modulation. The approach allows for complex bounds using the fine structure of the code, for simpler bounds similar to those on memoryless channels and finally for a random coding bound using the cutoff rate of the channel. The analysis thus permits a step by step evaluation of coded error performances for Rician-fading channels.>