Cell-free network is a new paradigm, originating from distributed MIMO, that has been investigated for a few recent years as an alternative to the celebrated cellular structure. Future networks not only consider classical data transmission but also positioning, along the lines of Integrated Communications and Sensing (ISAC). The goal of this paper is to investigate at the same time the ambiguity function which is an important metric for positioning and the understanding of its associated resolution and ambiguities, and the array gain when maximum ratio transmission (MRT) or MR combining (MRC) is implemented for data communications. In particular, the role and impact of using a waveform with non-zero bandwidth is investigated. The theoretical findings are illustrated by means of computational results.

Federated learning is envisioned to be a key enabler of network functionalities based on artificial intelligence. Multiple access mechanisms supporting the learning task must then be designed, in order to provide an efficient interplay between the communication and computation resources. This work considers thus a multi-level slotted random access scheme autonomously optimised by each node. Due to their mutual coupling, the nodes’ interaction is an instance of the Best Response Dynamics (BRD) of a Generalised Nash Equilibrium Problem (GNEP). Within this framework, levers are identified, guaranteeing the convergence of the interactions to an equilibrium point at which the federated learning task is supported. These levers, on which the network manager can act, are validated by numerical simulations. These latter moreover show that the performance loss due to the autonomous character of the nodes is negligible with respect to the result of a centralised optimisation. On a broader mathematical level, this work defines a class of GNEPs for which sufficient convergence conditions for the totally asynchronous BRD are obtained. The considered class, named the GNEPs with polyhedral strategy sets and variable right-hand sides, encompasses a wide variety of GNEPs, and in particular GNEPs which are neither jointly convex nor generalised potential games. The obtained conditions depend on the first and second derivatives of the objective and constraint functions, and they constitute thus an off-the-shelf framework to study the BRD of GNEPs belonging to the identified class.

In this paper, we present the fusion of passive Time-Difference-of-Arrival (TDoA) and active monostatic radar measurements in the context of single object localization and tracking. We assume a target equipped with a wireless transmitter so that the passive-TDoA and active-radar sensors can simultaneously detect it. For the localization problem, we base our approach on the Constrained-Weighted-Least-Squares (CWLS) method, which has better accuracy than the Least-Squares (LS) and Weighted-LS approaches. Nevertheless, CWLS suffers from estimation bias when the measurement noise is large. We show that it is possible to reduce such a bias by using both TDoA and monostatic radar measurements. For the tracking problem, we base our approach on Bayesian filtering. Therefore, we detail the TDoA, radar and combined measurement models required for the filtering process regardless of the Bayesian Filter implementation. We show that the combined measurements result in enhanced tracking capabilities, e.g., improved reliability and larger tracking area compared to the radar-only case. In addition, we present other possible combinations of radar and TDoA measurements that one could encounter in practical scenarios. Finally, we present experimental results to validate and support our work.

The use of deep learning (DL) has become more common in applications that require high accuracy, but the high computational demand of DL makes it challenging to execute on a single resource-constrained end device (ED) due to low computing capability and limited energy. One way to execute DL is to use the mobile cloud computing concept, but it results in intolerable latency, network congestion and raises privacy concerns. In the absence of powerful servers, another solution could be to form a collaboration among multiple EDs to execute DL computation. This paper proposes a distributed collaborative on-device convolutional neural network (CNN) execution scheme using model parallelism for latency-critical applications. In the proposed scheme, the ED that owns the input data uses its communication capabilities to get additional computing capabilities from other EDs. A convex optimization problem is formulated to minimize the energy consumption of all EDs by jointly optimizing the communication and computation parameters along with the number of filters assignment in each convolutional layer in the CNN model to multiple EDs. The problem is then decomposed into two sub-problems to obtain analytical expressions for the optimizing parameters and make the optimization distributed among multiple EDs. The simulation results show the importance of optimizing the communication-computation trade-off and the advantages of collaborative computing.

Estimation of User Terminals’ (UTs’) Angle of Arrival (AoA) plays a significant role in the next generation of wireless systems. Due to high demands, energy efficiency concerns, and scarcity of available resources, it is pivotal how these resources are used. Installed antennas and their corresponding hardware at the Base Station (BS) are of these resources. In this paper, we address the problem of antenna selection to minimize Cramer-Rao Lower Bound (CRLB) of a planar antenna array when fewer antennas than total available antennas have to be used for a UT. First, the optimal antenna selection strategy to minimize the expected CRLB is proposed. Then, using this strategy as a preliminary step, we present a two-stage greedy antenna selection method whose goal is to minimize the instantaneous CRLB. The optimal start point of the greedy algorithm is presented alongside some methods to reduce the algorithm’s computational complexity. Numerical results confirm the accuracy of proposed solutions. They demonstrate that the proposed antenna selection method only requires a small proportion of the total available antennas to accomplish a significant amount of the total performance, enhancing hardware utilization efficiency. Also, it is shown that the presented algorithm has a high error tolerance.

In this paper, the impact of interference between multiple phase-coded Frequency Modulated Continuous Wave (FMCW) Dual Function Radar Communication (DFRC) systems is analysed. For the RADAR receiver, interference occurs when another nearby DFRC system is active. For the communication receiver, RADAR echoes from the same DFRC system interfere with the receiver. The performance achieved by interference cancellation at both functions is studied in different scenarios. Finally, stochastic geometry is used to analyse in a two-way automotive scenario which signal component (RADAR or communication) is dominant, in order to evaluate whether the interference should be cancelled at the RADAR receiver based on the communication receiver output or the opposite.

In the next generation of wireless systems, massive Multiple Input Multiple Output (MIMO) offers high angular resolution for localization. By virtue of large number of antennas, Angle of Arrival (AoA) of User Terminals (UTs) can be estimated accurately. Measurements of Dense Multipath Channel (DMC) indicate multipath signals contribute up to 95% of total link power. This fact urges the necessity of studying the contribution of multipath signals accompanying dominant path in AoA estimation. We obtain a deterministic form for Cramer-Rao Lower Bound ($CRLB$) in multi-user scenario when contribution of multipath signals is considered. We do this when the multipath signals are independent and identically distributed (i.i.d) with arbitrary distribution. Then, we redefine a localization efficiency function for multi-user scenario and optimize it with respect to (w.r.t) the number of antennas. When only a subset of available antennas is used, we prove that$CRLB$can be minimized w.r.t which set is used. An antenna selection strategy that minimizes$CRLB$is proposed. As a benchmark, we apply the proposed antenna selection to MUltiple SIgnal Classification (MUSIC) algorithm and study its efficiency. Numerical results validate the accuracy of our analysis and show significant improvement in efficiency when the proposed antenna selection is employed.

In this paper, we consider Internet of Things (IoT) based mobile edge computing (MEC) system. IoT devices are controlled by access points (APs), which do not have access to any licensed spectrum. This puts limitations on IoT devices’ offloading capability and hence effectively reduces the number of computed bits. Under such scenario, we consider spectrum sharing, where IoT networks get access to licensed spectrum by helping a primary network (owns licensed spectrum) in cooperative relaying. We aim to maximize sum of the primary network’s communication rate and IoT networks’ total number of computed bits by jointly optimizing relay selection, licensed spectrum allocation, local computation, and offloading sequence selection. Moreover, we consider important constraints, e.g., the guaranteed rate for the primary network, IoT devices’ available energy, and available licensed spectrum resource blocks (RBs). We observe that the optimization problem is combinatoric in nature, which becomes more complicated when IoT devices’ scheduling order comes into the formulation. From our analysis, we devise an optimal and computationally efficient algorithm. In the result section, we compare with relevant benchmark systems and show the efficacy of our proposed model. Moreover, we also show how IoT and primary networks benefit from spectrum sharing.

In this paper, we investigate the application of continuous sparse signal reconstruction algorithms for the estimation of the ranges and speeds of multiple moving targets using an FMCW radar. Conventionally, to be reconstructed, continuous sparse signals are approximated by a discrete representation. This discretization of the signal’s parameter domain leads to mismatches with the actual signal. While increasing the grid density mitigates these errors, it dramatically increases the algorithmic complexity of the reconstruction. To overcome this issue, we propose a fast greedy algorithm for off-the-grid detection of multiple moving targets. This algorithm extends existing continuous greedy algorithms to the framework of factorized sparse representations of the signals. This factorized representation is obtained from simplifications of the radar signal model which, up to a model mismatch, strongly reduces the dimensionality of the problem. Monte-Carlo simulations of a K-band radar system validate the ability of our method to produce more accurate estimations with less computation time than the on-the-grid methods and than methods based on non-factorized representations.

Massive MIMO systems provide high angular resolution in the next generation of wireless systems. This opportunity can be used to estimate the location of user terminals (UTs) accurately. In this paper, we analyze the Cramer-Rao lower bound (CRLB) of planar antenna arrays in Massive MIMO systems for Angle of Arrival (AoA) estimation. With the help of Random Matrix Theory, we prove that for Massive antenna arrays with independent and identically distributed (i.i.d) multipath signals, instantaneous CRLB for AoA estimation converges toward a deterministic value, regardless of channel distribution. In this scenario, CRLB is a function of channel variance instead of instantaneous realizations. Then, antenna selection is studied, and it is shown that using different subsets significantly affects the CRLB of a planar array. Numerical results confirm the convergence of deterministic results and indicate the benefits of antenna selection and the importance of the selection strategy.

In this paper, we consider a system model in conjunction with two major technologies in 5G communications, i.e., mobile edge computing and spectrum sharing. An IoT network, which does not have access to any licensed spectrum, carries its computational task offloading activities with help of spectrum sharing. The IoT network cooperates with a licensed spectrum holding network by relaying its data and in return gets access to the licensed spectrum. The licensed spectrum holding network focuses on throughput maximization, whereas, the IoT network tries to maximize task computation rate. We formulate an optimization problem giving importance to both networks’ interests. Typical IoT nodes may be energy-constrained, which is considered along with task computation time constraints. Parallel computation is considered while computing IoT nodes’ computational tasks at the mobile edge computing server, where the processor is allocated based on IoT nodes’ offloading capabilities. The advantage of such processor allocation is shown in the result section. Moreover, we also show how both IoT and licensed spectrum holding networks benefit from the spectrum sharing by caring for each other requirements, which echoes the fact, i.e., Sharing is Caring.

In this paper, we introduce a fully distributed localization algorithm based on self-synchronization mechanism. The proposed algorithm reaches consensus for the posterior distribution of the transmitter position at each base station. To reduce the communication overhead at each iteration, we propose to represent the state variable matrices of the self-synchronization mechanism with only four parameters (radial and angular means and variances). The performance of the algorithms is numerically assessed by the mean distance error and mean Kullback–Leibler divergence. Finally, we show through Monte-Carlo simulations that our approach gets very close to the direct-centralized-localization performance after a few iterations.

Iterative localization is currently seen as an attractive solution to localize a transmitter in a cellular network. It has been shown that, by iterating between a range estimation step and a multi-lateration step, it is possible to refine the estimation in the first step, where only local information is used at iteration one. The iterative approach gets close to the performance of direct localization; nevertheless, it does not seem to converge to the direct localization performance for medium and low signal-to-noise-ratio values, due to the fact that it still suffers from loss of information due to projections and data representation. In this work, we propose to approximate the range log-likelihood at the base station with a Dirichlet kernel and to perform all the processing in a common xy-domain so that projections are no longer needed. We numerically show that our approach brings significant performance gains as compared to the time-of-arrival based iterative position estimation algorithm, getting really close to the performance of direct localization.

We consider a relay network based on Unmanned Aerial Vehicles (UAV). Terrestrial Base Stations (TBS) and UAV Relay Nodes (RN) are modelled using two Homogeneous Poisson Point Processes (HPPP). UAVs can hover at a fixed position or move following specific displacement schemes. The Coverage Probability (CP) of a typical user equipment (UE) is derived, either when it communicates via a direct link (from the TBS to the UE) or via a relay link (from the TBS to the UE through a UAV RN). Every link can be in Line-of-Sight (LoS) or Non Line-of-Sight (NLoS), and suffers from Rician fading with distance-dependent parameters. This coverage is calculated by means of both stochastic geometry (SG) and Monte-Carlo (MC) simulations. The benefits of the use of UAV as RNs are analysed depending on their altitude, density, and mobility scheme.

Heterogenous networks are mainly limited by interference. Nowadays, the advances in reconfigurable antennas allow us to implement blind interference alignment (BIA) schemes, which avoid the need for channel state information at the transmitter (CSIT) while providing an increasing multiplexing gain, i.e., the achievable DoF, as the number of users increases. In this work, we propose a downlink transmission scheme based on BIA for managing the inter-tier interference in$K$-tier networks, referred to as tier BIA (tBIA). The tBIA scheme can be implemented considering that each tier employs any BIA scheme for managing the intracell and intercell interference. In this sense, considering proper BIA schemes applied to each tier, tBIA fully cancels all the sources of interference. After that, the DoF outer-bound for$K$-tier networks without CSIT is derived. It is shown that tBIA reaches this outer-bound. Furthermore, it is demonstrated that fully managing the inter-tier interference provides larger DoF in the whole network than turning off any tier with the aim of improving the achievable DoF in the remaining tiers. Simulation results show that the proposed tBIA scheme provides greater DoF and improves the user rates in comparison with other schemes without CSIT in multi-tier networks.

In this paper we analyze the performance of a mobile edge computing (MEC) system in the presence of spatially correlated shadowing. To achieve this goal, obstacles like walls are modelled by a Manhattan Poisson line Process (MPLP). Simultaneous wireless information and power transfer (SWIPT) is used to send command messages as well as to deliver the power to low power devices (LPDs). The energy harvested by the LPDs in the downlink phase is then used to either locally execute the assigned computation task or to offload it to the MEC server. By leveraging stochastic geometry, we derive analytical expressions for the success probability of the system which is defined as the joint probability of SINR downlink coverage and of harvesting enough energy to execute the computation task. Moreover, the impact of different system parameters on the trade-off between the harvested energy and the computational task admission rate is analyzed.

In this paper, we propose an online power allocation (PA) scheme to maximize the time averaged sum rate for multiple downlink receivers with energy harvesting transmitter. The transmitter uses non-orthogonal multiple access (NOMA) to transmit data to multiple users. For fairness, we impose a power order constraint on the power allocation among the users. The decisions of total transmit power and power allocation for different users in a given time slot are obtained with the help of Lyapunov optimization technique. The proposed scheme does not require any statistical information of the channel states and the harvested energy. Furthermore, only one Bisection search is required for the implementation of proposed scheme and hence its computational complexity is small. Simulation results are used to show the efficacy of the proposed scheme.

This paper considers uplink multiple access (MA) transmissions, where the MA technique is adaptively selected between Non Orthogonal Multiple Access (NOMA) and Orthogonal Multiple Access (OMA). Two types of users, namely Internet of Things (IoT) and enhanced mobile broadband (eMBB) coexist with different metrics to be optimized, energy efficiency (EE) for IoT and spectral efficiency (SE) for eMBB. The corresponding multi-objective power allocation problems aiming at maximizing a weighted sum of EE and SE are solved for both NOMA and OMA. Based on the identification of the best MA strategy, a clustering algorithm is then proposed to maximize the multi-objective metric per cluster as well as NOMA use. The proposed clustering, power allocation and MA selection algorithm is shown to outperform other clustering solutions and non-adaptive MA techniques.

In this paper, we study an energy harvesting mobile computing (wireless) communication system in which mobile computing nodes and base stations are distributed according to Poisson point processes. The mobile computing nodes use power splitting protocol to harvest energy from the downlink transmissions while decoding the downlink information. The harvested energy is then used for computing and uplink transmission. In this setting, our target is to minimize the overall energy consumption in the network while satisfying the quality of service constraints on communication and computational aspects of the network. The formulated optimization problem is not a convex optimization problem and is difficult to solve. Therefore, we relax the original problem and propose a computationally efficient solution that can be implemented with Bisection search over a single variable. Finally, numerical results are provided to demonstrate the effectiveness of the proposed solution.

In this paper, a sum inverse energy efficiency (SIEE) minimization problem for multi-link systems is studied. Compared with conventional sum energy efficiency (EE) maximization problems, minimizing SIEE achieves a better fairness. Based on a framework for solving sum-fraction minimization (SFMin) problems, this paper investigates the resource (time fraction and power) allocation problem where links are separated in the time domain. Closed-form solutions are found for the reformulated problem. By using Newton's method for system of equations, iterative algorithms are proposed to find the solution thanks to the closed-form expressions. Numerical results confirm the fast convergence of the algorithm for SFMin problems. Simulation results show that the algorithm convergences fast with practical parameter when each subproblem uses Newton's method. Impacts of system parameters on the resource allocation are also investigated.

This paper studies a cooperative wireless powered communication network system. The communication between uplink users and hybrid access point is supported by energy harvesting relays. In contrast to the exiting works, we assume that the uplink users also harvest energy from the energy signal transmitted by the hybrid access point. Furthermore, it is assumed that the relays employ decode and forward relaying protocol for relaying the users information to the access point. We propose an optimization problem whose aim is to maximize the average sum throughput of the system. It is proved that the proposed optimization problem is convex. Karush Kuhn Tucker (KKT) conditions are used to find the optimal time allocations for the energy signal transmission and information signal transmissions. The proposed scheme for finding the optimal time allocation does not require instantaneous channel state information therefore significant reduction in the feedback information can be achieved by using the proposed scheme. The simulation results show that the proposed time allocation can significantly improve the performance of the system.

This paper investigates device-to-device (D2D) communications where two nearby users are enabled to communicate directly with each other. A network analysis under Rician fading is proposed to account for a strong line-of-sight (LOS) component typical for this technology. Semi closed-form expressions for the cellular (CC) and underlaid D2D communication outage probabilities are derived relying on stochastic geometry theory. Schemes where D2D communications reuse the uplink (UL) or the downlink (DL) CC bands are compared. The choice between them is shown to strongly depend on the base stations (BS) and user equipments (UE) transmit powers.

A sum inverse energy efficiency (SIEE) minimization problem is solved. Compared with conventional sum energy efficiency (EE) maximization problems, minimizing SIEE achieves a better fairness. The paper begins by proposing a framework for solving sum-fraction minimization (SFMin) problems, then uses a novel transform to solve the SIEE minimization problem in a multiple base station (BS) system. After the reformulation into a multi-convex problem, the alternating direction method of multipliers (ADMM) is used to further simplify the problem. Numerical results confirm the efficiency of the transform and the fairness improvement of the SIEE minimization. Simulation results show that the algorithm convergences fast and the ADMM method is efficient.

The integration of simultaneous wireless information and power transfer (SWIPT) and mobile-edge computing (MEC) technologies is emerging as a promising technique to overcome the performance limits of ultra-low power devices (ULPD) due to their low battery capacities and their limited computation capabilities in the Internet of Things (IoT) era. In this paper, we propose an online resource allocation algorithm for multiuser SWIPT-based MEC systems with the aim of maximizing the proportional fairness computational utility function subject to the stability of task and energy queues. Lyapunov optimization framework is used to jointly optimize the amounts of time allocated for energy harvesting, information decoding and offloading, the transmission power for offloading and CPU-cycles frequencies for local computing. Moreover, rigorous performance analysis has been done to prove the asymptotic optimality of our proposed algorithm. Simulation results are also presented to demonstrate the gains of our proposed algorithms over alternative online approaches and the impact of different network parameters on the performance of our algorithm.

This letter analyzes the performances of a simple reconstruction method, namely the Projected Back-Projection (PBP), for estimating the direction of a sparse signal from its phase-only (or amplitude-less) complex Gaussian random measurements, i.e., an extension of one-bit compressive sensing to the complex field. To study the performances of this algorithm, we show that complex Gaussian random matrices respect, with high probability, a variant of the Restricted Isometry Property (RIP) relating to the ℓ1-norm of the sparse signal measurements to their ℓ2-norm. This property allows us to upper-bound the reconstruction error of PBP in the presence of phase noise. Monte Carlo simulations are performed to highlight the performance of our approach in this phase-only acquisition model when compared to error achieved by PBP in classical compressive sensing.

Low-complexity iterative reception of Continuous Phase Modulation (CPM) is addressed using Linear Minimum Mean-Square Error (LMMSE) filtering empowered by Soft Interference Cancellation (SIC). The transmitter emits a convolutionally encoded, true CPM signal with a constant envelope. The receiver exploits Laurent-Mengali-Morelli's (LMM) decomposition to reduce the detection complexity, where the transmitted true CPM signal is approximated as a superposition of a small number of parallel Pulse Amplitude Modulated (PAM) and phase-encoded terms. Pulses and phase-encoded pseudo-symbols arising from the LMM decomposition are treated, respectively, as parallel Inter-Symbol Interference (ISI) channels and Multiple Access Interference (MAI) components. Hence the transmitted signal is regarded to inherently contain controlled ISI and MAI, which are equalized for at the receiver front-end using LMMSE-SIC filters. The receiver back-end comprises a serially concatenated turbo scheme encompassing a Soft Input-Soft Output (SISO) CPM detector and a SISO channel decoder. Simulations conducted on various CPM schemes show that the proposed receiver provides significant complexity reduction for a small performance penalty. Consequently, CPM waveforms with long pulses, which have traditionally been deemed infeasible due to the prohibitive complexity, can now be implemented employing the proposed receiver. Hence substantial spectral side-lobe compaction offered by long CPM pulses can be harnessed.

In this paper, we have considered a simultaneous wireless information and power transfer (SWIPT)-enabled mobile edge computing (MEC) system where a low power device (LPD) has to decide either to perform local computation or offloading. A decision strategy has been proposed and the impact of this strategy on a triple trade-off between energy, local computation and offloading has been evaluated. Moreover, in the local computation case, due to the existence of an uploading phase in which results are sent to the MEC server, another communication-computation trade-off has been analysed. In order to provide a system-level perspective on the performance of such a SWIPT-MEC network, we have employed stochastic geometry to characterise these communication-computation trade-offs of the system and we have investigated joint success probability of local computation and offloading.

In this paper, the problem of subcarrier allocation and power control for uplink orthogonal frequency division multiple access (OFDMA) channels is studied. Each user may have a different strategy of power control due to his/her own limits of battery, quality-of-service (QoS) requirement, and the amount of information to transmit. The problem is first formulated as a minimization problem, and the alternating direction method of multipliers (ADMM) is then introduced to solve the problem in a distributed manner. Necessary conditions of each subproblem are derived to obtain a deeper understanding in the structure of the solutions. Numerical results show that the algorithm converges fast and obtains a near-optimal solution within only a few iterations.

In this paper, we propose the use of simultaneous wireless information and power transfer (SWIPT) to control distributed computation process while delivering power to perform the computation tasks requested. A real-time mobile computing (MC) system is considered, meaning that the trade-off between the information rate and the energy harvested must be carefully chosen to guarantee that the central processing unit (CPU) may perform tasks of given complexity before receiving a new control signal. In order to provide a system-level perspective on the performance of such a SWIPT-MC network, we make use of stochastic geometry to characterise the rate-energy trade-off of the system. The resulting achievable performance region is then put in relation with the CPU energy consumption to investigate the operating conditions of real-time computing systems.

We characterize the degrees of freedom (DoF) of the two-tier heterogeneous networks without channel state information at the transmitters or cooperation among transmitters. We consider conventional transmitters while the users are equipped with a multimode receiver. In contrast to previous works focused on two-tier networks, the derived DoF consider the management of the intracell, the intercell, and intertier interference. The derived bounds define the DoF region for any two-tier network. Furthermore, these bounds are achievable by combining blind interference alignment schemes properly.

Simultaneous wireless information and power transfer (SWIPT) is characterized by the ambiguous role of multi-user interference. In short, the beneficial effect of multi-user interference on RF energy harvesting is obtained at the price of a reduced link capacity, thus originating nontrivial tradeoffs between the achievable information rate and the harvestable energy. Arguably, in indoor environments, this tradeoff might be affected by the propagation loss due to blockage objects like walls. Hence, a couple of fundamental questions arise. How much must the network elements be densified to counteract the blockage attenuation? Is blockage always detrimental on the achievable rate-energy tradeoff? In this paper, we analyze the performance of an indoor multiple-input multiple-output SWIPT-enabled network in the attempt to shed a light of those questions. The effects of the obstacles are examined with the help of a stochastic geometry approach in which the locations of energy sources (also referred to as power heads) are distributed by using a Poisson point process and walls are generated through a Manhattan Poisson line process. The stochastic behavior of the signal attenuation and the multi-user interference is studied to obtain the joint complementary cumulative distribution function of information rate and harvested power. Theoretical results are validated through Monte Carlo simulations. Eventually, the rate-energy tradeoff is presented as a function of the density of walls to emphasize the cross-dependences between the deployment of the network elements and the macro parameters characterizing the topology of the venue.

This paper proposes a novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. With the proposed channel estimation and beamforming approach, we determine the number of cells$N_{c}$that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has a maximum of$L$uncorrelated multipath taps (or correlated multipath taps satisfying modest criteria which is valid in most practical scenarios), it is shown that$N_{c}=L$cells can estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination. The proposed approach can also be applied for general correlated multipath taps, and achieves good performance for this scenario as well. In a typical long term evolution (LTE) channel environment having delay spread$T_{d}=4.69\,\,\mu \text{s}$and channel bandwidth$B=5$MHz, we have found that$L=36$cells can use this band. In practice,$T_{d}$is constant for a particular environment and carrier frequency, and hence$L$increases as the bandwidth increases. All the analytical expressions have been validated, and the superiority of the proposed design over the existing ones is demonstrated using extensive numerical simulations both for correlated and uncorrelated channels. The proposed channel estimation and beamforming design is linear and simple to implement.

The main contribution of this paper consists in integrating a physically correlated shadowing model of the aggregate interference in a stochastic geometry-based approach. The considered shadowing takes place in a Manhattan urban grid and combines both penetration and corner diffraction when modeling signal transmission from base stations to users. A tractable expression for the network coverage probability is obtained thanks to the framework of stochastic geometry. Our results suggest that the diffracted mechanisms are dominant compared to building penetration. It is also shown that the second order diffracted signal have little impact on the coverage compared to the first order signals.

In this paper, we consider a fog computing system consisting of a multi-antenna access point (AP), an ultra-low power (ULP) single antenna device and a fog server. The ULP device is assumed to be capable of both energy harvesting (EH) and information decoding (ID) using a time-switching simultaneous wireless information and power transfer (SWIPT) scheme. The ULP device deploys the harvested energy for ID and either local computing or offloading the computations to the fog server depending on which strategy is most energy efficient. In this scenario, we optimize the time slots devoted to EH, ID and local computation as well as the time slot and power required for the offloading to minimize the energy cost of the ULP device. Numerical results are provided to study the effectiveness of the optimized fog computing system and the relevant challenges.

The use of light-emitting diodes (LEDs) for ambient illumination leads to visible light communications (VLC) as a promising technology for providing both constant lighting and high-speed wireless services in indoor environments. Since multiple LED sources can be transmitted to several users, this scenario naturally forms a multiple-user multiple-input single-output system. In this sense, transmit precoding (TPC) schemes based on channel state information at the transmitter (CSIT) originally devised for radio-frequency (RF) systems have been proposed for their implementation in VLC. However, beyond providing CSIT or the need for cooperation among transmitters, which also result challenging in RF systems, there are several constraints such as the non-negativity of the transmitted signal or providing constant illumination that hamper the performance of TPC schemes in VLC. Considering these constraints, this paper explores the use of blind interference alignment (BIA) for achieving multiplexing gain without CSIT or cooperation among LED lights. To do that, we devise the concept of reconfigurable photodetector that allows switching among distinct and linearly independent channel responses. Simulation results show that the use of BIA in VLC systems schemes based on the proposed reconfigurable photodetector results suitable for VLC systems.

An energy efficiency (EE) maximization problem with multiple transmit antennas (multiple-input-single-output or distributed antennas setups) is considered in this paper. Besides the constraint on the total transmit power, per-antenna transmit power constraints, and a total weighted power constraint are jointly considered. Moreover, a quality-of-service constraint is also considered. Both linear and nonlinear high power amplifier (HPA) cases are studied. Because the original problem for the linear HPA case is a fractional convex problem, Dinkelbach's algorithm is implemented to reformulate the problem. By investigating the Karush-Kuhn-Tucker conditions, the mathematical properties of the globally optimal solution are studied and proved, which provides a deeper understanding of the structure of power allocation among antennas. These properties also lead to a reduction of the complexity of the algorithms proposed to find the global optimum. For the nonlinear HPA cases, the reformulated problem after successive convex approximation is shown to be exactly in the same form as that of the previous problem with linear HPA with different weights of power consumption at each antenna. On the basis of numerical results comparing our EE maximization algorithms against different benchmarks, the efficiency and the superiority of our algorithms can be concluded.

The growing demand for wireless connectivity has turned bandwidth into a scarce resource that has to be carefully managed and fairly distributed to users. However, the variability of the wireless channel can severely degrade the service received by each user. The Double Relay Communication Protocol (DRCP) [1] is a transmission scheme that addresses these problems by exploiting spatial diversity to enhance the fairness of the system without requiring any additional infrastructure (i.e relay nodes or a backhaul connection). Although DRCP has originally been proposed to work without channel state information at the transmitter (CSIT), in this paper we study how the performance of DRCP can be further improved through power control when CSIT is available. Our approach provides the highest fairness and the largest minimum spectral efficiency for most conditions compared to other studied baseline approaches.

Strategies are developed to optimize the downlink performance of a massive MIMO network constrained to a fixed global transmit power and a fixed total number of transmit antennas. Two possible degrees of freedom are analysed : the distribution of the base stations and the beamforming technique. Two different shadowing environments are considered as well. The network performance is evaluated either by means of Monte Carlo simulations, or using analytical expressions derived thanks to stochastic geometry. The results suggest that the coverage probability increases with the numbers of base stations and the cluster size.

Massive MIMO has been proposed as a means of achieving huge spectral efficiency in cellular networks. However, its implementation is usually based on linear precoding schemes using Channel State Information (CSI). For this reason, the use of the Time Division Duplex (TDD) mode is typically assumed since it removes the dependence on the number of antennas at the transmitter to acquire CSI. Unfortunately, most of the cellular network operate in the Frequency Division Duplex (FDD) mode in which the acquisition of CSI depends proportionally to the number of transmit antennas. For this reason, the implementation of Massive MIMO is handicapped to few transmit antennas for the current cellular networks. In this paper we study the use of reconfigurable antennas that can switch among a set of preset modes, i.e., radiation patterns, through Blind Interference Alignment schemes. We show that it is a solution to exploit a very large number of antennas at the transmit side, overcoming the bottleneck that today constitutes the acquisition of CSI in Massive MIMO systems operating in FDD mode.

This paper studies the subcarrier allocation and precoder design problem for downlink multiple-input-multiple-output-orthogonal frequency-division multiple access systems. The criterion is to maximize the energy efficiency (EE) of the system. We adopt the time-sharing concept to allocate each subcarrier to one user, which results in a criterion similar with that of rate maximization. However, this approach does not make it possible to solve the problem for any value of the transmit power. We found that there exist gaps along the direction of total transmit power when the user selection switches for each subcarrier, which leads to a discontinuous EE function, for which quasi-concavity has to be checked. We first show that the sufficient conditions obtained for the subcarrier allocation approach are the optimal ones among all possibilities with the same transmit power. Then, we show that the proposed subcarrier allocation results in a discontinuous and quasi-concave EE function. We also give an upper bound of the EE function when the proposed sufficient conditions are not met. Finally, we propose an algorithm to find the maximal EE and its performance is illustrated by means of numerical results.

This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN) data transmission and detection approach for a single input multiple output system. It is assumed that the signal having a bandwidth B is transmitted through a wireless channel with L multipath components. Under this assumption, this paper provides a novel and simple OFTN transmission and symbol-by-symbol detection approach that exploits the multiplexing gain obtained by the multipath characteristic of wideband wireless channels. It is shown that the proposed design can achieve a higher transmission rate than the existing one [i.e., orthogonal frequency division multiplexing (OFDM)]. Furthermore, the achievable rate gap between the proposed approach and that of the OFDM increases as the number of receiver antennas increases for a fixed value of L. This implies that the performance gain of the proposed approach can be very significant for a large-scale multi-antenna wireless system. The superiority of the proposed approach is shown theoretically and confirmed via numerical simulations. Specifically, we have found upper-bound average rates of 15 and 28 bps/Hz with the OFDM and proposed approaches, respectively, in a Rayleigh fading channel with 32 receive antennas and signal-to-noise ratio of 15.3 dB. The extension of the proposed approach for different system setups and associated research problems is also discussed.

A cognitive radio scenario is considered where the signals transmitted by a secondary user (SU) are relayed by multi-antenna relays using an amplify-and-forward cooperation protocol. In this paper, the optimal power allocation and beamforming scheme is derived for the SU transmitters (SU-TXs), which minimizes the exact outage probability of the SU network with relay selection, under both a transmit power constraint and a constraint on the interference power generated at every primary user receiver. After deriving the optimal structure of the beamforming matrix, several distributed resource allocation algorithms are obtained for different levels of channel state information (CSI) at the SU-TXs: perfect CSI and imperfect CSI are considered, along with the case where only channel distribution information is available. The numerical results show that the multi-antenna relays can significantly improve the performance of the SU network, which would otherwise be severely limited by the harsh interference constraints. Furthermore, we also investigate how the number of relays, the number of antennas, and the level of CSI impact the performance of the SU network. Finally, we point out that the proposed algorithms outperform several algorithms presented in the literature.

This paper proposes a novel and simple orthogonal faster than Nyquist (OFTN) data transmission and detection approach for a single input multiple output (SIMO) system. It is assumed that the signal having a bandwidth is transmitted through a wireless channel having multipath components. Under this assumption, the current paper provides novel OFTN transmission and symbol-by-symbol detection approach that exploits the multiplexing gain obtained by the inherent characteristics of multipath components of wideband channels. In doing so, the proposed design achieves a higher transmission rate than the existing orthogonal frequency division multiplexing (OFDM) approach. It is also shown that the capacity gap between the proposed approach and that of OFDM increases as the number of receiver antennas increases for fixed . The superiority of the proposed approach has been shown theoretically and confirmed via numerical simulations.

A practical Blind Interference Alignment scheme is devised for the broadcast channel where the users are equipped with reconfigurable antennas. The proposed scheme does not require any channel state information at the transmitter other than the signal-to-noise ratio and coherence time. By employing Blind Interference Alignment to transmit to sets of users in an orthogonal fashion, the proposed scheme aims at maximizing the sum-rate at a finite signal-to-noise ratio regime and allows to handle the supersymbol length according to the coherence time limitation. Through computer simulations, it is shown that the proposed scheme improves the sum-rate of the system considerably in comparison with the standard Blind Interference Alignment in practical scenarios.

Equilibrium problems with vector objective functions may arise whenever uncoordinated wireless devices have to consider multiple conflicting requirements. In this paper we propose the use of a competitive optimality criterion to provide a systematic study of the relationship between the theoretical limits of information rate and energy efficiency for a group of transmitter-receiver pairs (TRPs) with local channel state information (CSI) only. To achieve this, we modeled the power control problem in a Gaussian interference channel as a competitive multiobjective game. After having provided the reader with some essential results on multiobjective games, we propose a game scalarisation based on the Quasi Variational Inequality (QVI) framework. This provides the mathematical tools to study the characteristics of the equilibrium points and to derive a power control distributed algorithm. Eventually, the proposed solution is validated by means of numerical results.

This paper investigates the optimal design of multiple-input-multiple-output (MIMO) precoders for orthogonal frequency-division multiplexing (OFDM) systems in the presence of nonlinear distortions due to the high power amplifier (HPA). In traditional approaches, the designer lets the input backoff (IBO) of the HPA be large enough to neglect the unavoidable nonlinear effects of the amplifier. However, this hypothesis may severely hinder the efficiency of the HPA and, consequently, the global energy efficiency of the link. On the other hand, making full use of the available power gives rise to unbearable nonlinear effects with consequent strong rate degradations. In this work, we take advantage of the Bussgang theorem to unveil the impact of the nonlinear distortion noise on the optimal precoding and to derive a power allocation algorithm that achieves the optimal tradeoff between HPA efficiency and rate degradation. We also provide a sufficient condition for the concavity of the information rate objective function in this nonlinear scenario. Finally, numerical results shows that the proposed algorithm outperforms conventional fixed-IBO precoding strategies.

In this paper, we consider the energy efficiency (EE) maximization problem for MIMO-relay channels with relay selection and individual power constraints for each node. We implement Dinkelbach's method for the whole system to iteratively select the relays. Closed-form expressions of the precoding matrix at the source and the beamforming matrix at the selected relay are obtained thanks to the concavity of the objective function. We also give the mathematical property of monotonicity which guarantees that the values of Lagrangian multipliers can always be found. Finally, we give the numerical results illustrating the performance gain due to relay selection.

In this paper, a novel resource allocation (RA) strategy is designed for the downlink of orthogonal frequency division multiple access networks employing practical modulation and coding under quality of service constraints and retransmission techniques. Compared with previous works, two basic concepts are combined together, namely: 1) taking the goodput (GP) as performance metric and 2) ensuring maximum fairness among users. Thus, the resulting RA maximizes the GP of the worst users, optimizing subcarrier allocation (SA), per-subcarrier power allocation (PA), and adaptation of modulation and coding (AMC) of the active users, yielding a nonlinear nonconvex mixed optimization problem (OP). The intrinsic demanding difficulty of the OP is tackled by iteratively and optimally solving the AMC, PA, and SA subproblems, devoting special care to the difficult nonlinear combinatorial SA-OP. First, the optimal (yet computationally complex) solution is found by applying the branch and bound method to the optimal SA solution found in the relaxed domain, and accordingly, it is taken as benchmark. Then, an innovative suboptimal yet efficient solution based on the metaheuristic ant colony optimization (ACO) framework is derived. The proposed RA strategy is corroborated by comprehensive simulations, showing improved performance even at the cost of affordable numerical complexity.

This paper considers hybrid beamforming (HB) for downlink multiuser massive multiple-input multiple-output (MIMO) systems with frequency selective channels. The proposed HB design employs sets of digitally controlled phase (fixed phase) paired phase shifters (PSs) and switches. For this system, first we determine the required number of radio frequency (RF) chains and PSs such that the proposed HB achieves the same performance as that of the digital beamforming (DB) which utilizes N (number of transmitter antennas) RF chains. We show that the performance of the DB can be achieved with our HB just by utilizing rtRF chains and 2rt(N-rt+ 1) PSs, where rt≤ N is the rank of the combined digital precoder matrices of all subcarriers. Second, we provide a simple and novel approach to reduce the number of PSs with only a negligible performance degradation. Numerical results reveal that only 20-40 PSs per RF chain are sufficient for practically relevant parameter settings. Finally, for the scenario where the deployed number of RF chains (Na) is less than rt, we propose a simple user scheduling algorithm to select the best set of users in each subcarrier. Simulation results validate theoretical expressions, and demonstrate the superiority of the proposed HB design over the existing HB designs in both flat fading and frequency selective channels.

This paper proposes novel joint channel estimation and beamforming approach for multicell wideband massive multiple input multiple output (MIMO) systems. Using our channel estimation and beamforming approach, we determine the number of cells Nc that can utilize the same time and frequency resource while mitigating the effect of pilot contamination. The proposed approach exploits the multipath characteristics of wideband channels. Specifically, when the channel has L multipath taps, it is shown that Nc≤ L cells can reliably estimate the channels of their user equipments (UEs) and perform beamforming while mitigating the effect of pilot contamination. For example, in a long term evolution (LTE) channel environment having delay spread Td= 4.69μ second and channel bandwidth B = 2.5MHz, we have found that L = 18 cells can use this band. In practice, Tdis constant for a particular environment and carrier frequency, and hence L increases as the bandwidth increases. The proposed channel estimation and beamforming design is linear, simple to implement and significantly outperforms the existing designs, and is validated by extensive simulations.

We propose a novel resource allocation (RA) strategy for a cognitive radio packet-oriented bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system with decode-and-forward (DF) relays. The aim of the RA is maximizing the goodput (GP) of the source-relay-destination link, which is the number of information bits correctly received at the destination node per unit of time. Therefore, we derive an accurate analytic approximation for this figure of merit, which allows us to find the optimum constellation size, code rate and energy allocation per subcarrier. Further, this expression also serves as a novel relay selection criterion. Finally, we validate the proposed RA method, and compare its performance to capacitymaximizing algorithms through numerical simulations.

This paper studies an energy efficient design of precoders for point-to-point multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. Differently from traditional approaches, the optimal power allocation strategy is studied by modelling the circuit power as a rate-dependent function. We show that if the circuit power is a constant plus an increasing and convex function of the transmission rate, the problem of minimizing the consumed energy per bit received can be reformulated as a convex fractional program and solved by means of a bisection algorithm. The impact of the some system parameters is investigated either analytically or by means of computational results.

This paper considers wide-band spectrum sensing and optimization for cognitive radio (CR) networks with noise variance uncertainty. It is assumed that the considered wide-band contains one or more white sub-bands. Under this assumption, we consider throughput maximization of the CR network while appropriately protecting the primary network. We address this problem as follows. First, we propose novel ratio based test statistics for detecting the edges of each sub-band. Second, we employ simple energy comparison approach to choose one reference white sub-band. Third, we propose novel generalized energy detector (GED) for examining each of the remaining sub-bands by exploiting the noise information of the reference white sub-band. Finally, we optimize the sensing time (To) to maximize the CR network throughput using the detection and false alarm probabilities of the GED. The proposed GED does not suffer from signal to noise ratio (SNR) wall and outperforms the existing signal detectors. Moreover, the relationship between the proposed GED and conventional energy detector (CED) is quantified analytically. We show that the optimal To depends on the noise variance information. In particular, with 10TV bands, SNR = -20 dB and 2s frame duration, we found that the optimal Tois 28.5 ms (50.6 ms) with perfect (imperfect) noise variance scenario.

This paper derives the Ziv-Zakai lower bound (ZZLB) for the time of arrival (TOA) estimation in the presence of one interfering pulse from which no a priori knowledge is available. The bound is obtained by including the interference in the system model but only the transmitted pulse as a candidate for the likelihood ratio (LR) test. A compact ZZLB expression that depends on the time delay and amplitude of the interference is obtained. We compare the performance of the first path maximum likelihood estimation (MLE) with the bound as a function of the relative distance between the first path and the interfering path.

This paper presents the Universal Software Radio Peripheral (USRP) experimental results of the Max-Min signal to noise ratio (SNR) Signal Energy based Spectrum Sensing Algorithms for Cognitive Radio Networks which is recently proposed in [1]. Extensive experiments are performed for different set of parameters. In particular, the effects of SNR, number of samples and roll-off factor on the detection performances of the latter algorithms are examined briefly. We have observed that the experimental results fit well with those of the theory. We also confirm that these algorithms are indeed robust against carrier frequency offset, symbol timing offset and noise variance uncertainty.

We consider two transceivers, the first with perfect clock and the second with imperfect clock. We investigate the joint estimation of the delay between the transceivers and the offset and the drift of the imperfect clock. We propose a protocol for the synchronization of the clocks. We derive some empirical estimators for the delay, the offset and the drift, and compute the Cramer-Rao lower bounds and the joint maximum likelihood estimator of the delay and the drift. We study the impact of the protocol parameters and the time-of-arrival estimation variance on the achieved performances. We validate some theoretical results by simulation.

In this paper we consider a decode-and-forward cooperative network, which is active in the same bandwidth as a primary user network. The cooperative or secondary user network applies a dynamic resource allocation algorithm to maximize its own performance while limiting the interference caused at the primary user receivers. The main contribution of this paper is the proposition of a new accurate approximation for the outage probability, which takes into account that the channel state information available at the transmitter is imperfect and outdated. The accuracy of the approximation and the performance of the resource allocation scheme are validated through numerical simulations.

This paper presents an energy-efficient power allocation for relay-aided heterogeneous networks subject to coupling convex constraints, that make the problem at hand a generalized Nash equilibrium problem. The solution to the resource allocation problem is derived using a sequential penalty approach based on the advanced theory of quasi variational inequality, which allows the network to converge to its generalized Nash equilibrium in a distributed manner. The main feature of the proposed approach is its decomposability, which leads to a two-layer distributed algorithm with provable convergence.

This paper proposes novel spectrum sensing algorithms for cognitive radio networks. By assuming known transmitter pulse shaping filter, synchronous and asynchronous receiver scenarios have been considered. For each of these scenarios, the proposed algorithm is explained as follows: First, by introducing a combiner vector, an over-sampled signal of total duration equal to the symbol period is combined linearly. Second, for this combined signal, the Signal-to-Noise ratio (SNR) maximization and minimization problems are formulated as Rayleigh quotient optimization problems. Third, by using the solutions of these problems, the ratio of the signal energy corresponding to the maximum and minimum SNRs are proposed as a test statistics. For this test statistics, analytical probability of false alarm (Pf) and detection (Pd) expressions are derived for additive white Gaussian noise (AWGN) channel. The proposed algorithms are robust against noise variance uncertainty. The generalization of the proposed algorithms for unknown transmitter pulse shaping filter has also been discussed. Simulation results demonstrate that the proposed algorithms achieve better Pdthan that of the Eigenvalue decomposition and energy detection algorithms in AWGN and Rayleigh fading channels with noise variance uncertainty. The proposed algorithms also guarantee the desired Pf(Pd) in the presence of adjacent channel interference signals.

We consider a system in which two users communicate with a destination with the help of a half-duplex relay. Based on the compute-and-forward scheme, we develop and evaluate the performance of coding strategies that are of network coding spirit. In this framework, instead of decoding the users' information messages, the destination decodes two integer-valued linear combinations that relate the transmitted codewords. Two decoding schemes are considered. In the first one, the relay computes one of the linear combinations and then forwards it to the destination. The destination computes the other linear combination based on the direct transmissions. In the second one, accounting for the side information available at the destination through the direct links, the relay compresses what it gets using lattice-based Wyner-Ziv compression and conveys it to the destination. The destination then computes the two linear combinations, locally. For both coding schemes, we discuss the design criteria, and derive the allowed symmetric-rate. Next, we address the power allocation and the selection of the integer-valued coefficients to maximize the offered symmetric-rate; an iterative coordinate descent method is proposed. The analysis shows that the first scheme can outperform standard relaying techniques in certain regimes, and the second scheme, while relying on feasible structured lattice codes, can at best achieve the same performance as regular compress-and-forward for the multiaccess relay network model that we study. The results are illustrated through some numerical examples.

The aim of this paper is to derive a Ziv-Zakai lower bound (ZZLB) for the time of arrival (TOA) estimation in single-path (SP) additive white Gaussian noise (AWGN) channels and in the presence of multiuser interference (MUI). Time-hopping pulse position modulated (TH-PPM) ultra-wideband (UWB) signals are considered. Following a classical approach and extending it for the scenario under consideration, we compute the ZZLB by converting the related estimation problem into a binary detection one. To obtain the bit error rate (BER) of the corresponding detection problem, we both consider the exact handling of the MUI and the modeling of the MUI by means of a Gaussian approximation (GA).We compare the performance of the single-user maximum likelihood (ML) TOA estimator with the bounds.

In this work, we investigate the power allocation (PA) problem aimed at minimizing the users' packet error rate (PER) over a noncooperative link, i.e., a link where the set of users, employing packet-oriented bit-interleaved coded (BIC) orthogonal frequency division multiplexing (OFDM) systems, compete for the same bandwidth. For these kind of systems, the PER is not available in closed-form, but a very efficient solution is offered by the effective SNR mapping (ESM) technique. This method allows each user to evaluate a single scalar value, the effective SNR (ESNR), accounting for all the SNIRs experienced over the active subcarriers, and to univocally map it into a PER value. Thus, in order to derive a decentralized strategy allowing each user to minimize its own PER, the problem is described as a strategic game, called min-PER game, with the set of player, utilities and strategies represented by the competitive users, the ESNRs and the set of feasible power allocations, respectively. We will show both the existence of at least one Nash Equilibrium (NE) for the min-PER game and its equivalence with a Nonlinear Variational Inequality (NVI) problem. Finally, relying on the theory of contraction mappings, we will derive a distributed algorithm to reach the NE of the game.

We study a system in which two sources communicate with a destination with the help of a half-duplex relay. We consider a decoding strategy, based on the compute-and-forward strategy, in which the destination decodes two integer-valued linear combinations that relate the transmitted codewords. In this strategy, the relay compresses its observation using Wyner-Ziv compression and then forwards it to the destination. The destination appropriately combines what it gets from the direct transmission and the relay. Then, using this combination, it computes two integer-valued linear combinations. We discuss the encoding/decoding strategy, and evaluate the achievable sum-rate. Next, we consider the problem of allocating the powers and selecting the integer-valued coefficients of the recovered linear combinations in order to maximize the sum-rate. For the model under consideration, the optimization problem is NP hard. We propose an iterative algorithm to solve this problem using coordinate descent method. The results are illustrated through some numerical examples.

We investigate the problem of secure transmission over a two-user multi-input multi-output (MIMO) X-channel with noiseless local feedback and delayed channel state information (CSI) available at transmitters. The transmitters are equipped with M antennas each, and the receivers are equipped with N antennas each. For this model, we characterize the optimal sum secure degrees of freedom (SDoF) region. We show that, in presence of local feedback and delayed CSI, the sum SDoF region of the MIMO X-channel is same as the SDoF region of a two-user MIMO BC with 2M antennas at the transmitter and N antennas at each receiver. This result shows that, upon availability of feedback and delayed CSI, there is no performance loss in sum SDoF due to the distributed nature of the transmitters. Next, we show that this result also holds if only global feedback is conveyed to the transmitters. We also study the case in which only local feedback is provided to the transmitters, i.e., without CSI, and derive a lower bound on the sum SDoF for this model. Furthermore, we specialize our results to the case in which there are no security constraints. In particular, similar to the setting with security constraints, we show that the optimal sum degrees of freedom (sum DoF) region of the (M, M, N, N)-MIMO X-channel is same of the DoF region of a two-user MIMO BC with 2M antennas at the transmitter and N antennas at each receiver. We illustrate our results with some numerical examples.

This paper considers a multi-cell OFDMA downlink system with several decode-and-forward (DF) relay stations (RSs) aiding the base station (BS) transmissions. The opportunistic DF protocol proposed in [1] is applied. The problem considered is the maximization of the system sum rate with a total power constraint in each cell. An iterative low-complexity resource allocation (RA) algorithm is proposed to optimize mode selection (decision whether relaying should be used or not and which relay), subcarrier assignment (MSSA) and power allocation (PA) alternatively. During the MSSA stage, instead of the original objective function, a lower bound is maximized so that the problem is decoupled into subproblems which can be solved in linear time. During the PA stage, an algorithm based on single condensation and Lagrange duality PA (SC-LDPA) is designed to optimize PA with the tentative MSSA results. Through numerical experiments, the convergence of the low-complexity algorithm (LCA) as well as its benefit compared with a centralized algorithm (CA) are illustrated.

A novel subcarrier-pair based opportunistic DF protocol is proposed for cooperative downlink OFDMA transmission aided by a decode-and-forward (DF) relay. Specifically, user message bits are transmitted in two consecutive equal-duration time slots. A subcarrier in the first slot can be paired with a subcarrier in the second slot for the DF relay-aided transmission to a user. In particular, the source and the relay can transmit simultaneously to implement beamforming at the subcarrier in the second slot for the relay-aided transmission. Each unpaired subcarrier in either the first or second slot is used by the source for direct transmission to a user without the relay's assistance. The sum rate maximized resource allocation (RA) problem is addressed for this protocol under a total power constraint. It is shown that the novel protocol leads to a maximum sum rate greater than or equal to that for a benchmark one, which does not allow the source to implement beamforming at the subcarrier in the second slot for the relay-aided transmission. Then, a polynomial-complexity RA algorithm is developed to find an (at least approximately) optimum resource allocation (i.e., source/relay power, subcarrier pairing and assignment to users) for either the proposed or benchmark protocol. Numerical experiments illustrate that the novel protocol can lead to a greater sum rate than the benchmark one.

This paper investigates the optimum energy efficiency (EE) and the corresponding spectral efficiency (SE) for a communication link operating over a flat-fading channel. The EE is evaluated by the total energy consumption for transmitting per message bit. Three channel cases are considered, namely static channel with channel state information available at transmitter (CSIT), fast-varying (FV) channel with channel distribution information available at transmitter (CDIT), and FV channel with CSIT. The link's circuit power is modeled as ρ+κφ(R) Watt, where ρ>0 and κ≥0 are two constants and φ(R) is a general increasing and convex function of the transmission rate R≥0. For all the three channel cases, the tradeoff between the EE and SE is studied. It is shown that the EE improves strictly as the SE increases from 0 to the optimum SE, and then strictly degrades as the SE increases beyond the optimum SE. The impact of κ, ρ and other system parameters on the optimum EE and corresponding SE is investigated to obtain insight. Some of the important and interesting results for all the channel cases include: (1) when κ increases the SE corresponding to the optimum EE should keep unchanged if φ(R)=R, but reduced if φ(R) is strictly convex of R; (2) when the rate-independent circuit power ρ increases, the SE corresponding to the optimum EE has to be increased. A polynomial-complexity algorithm is developed with the bisection method to find the optimum SE. The insight is corroborated and the optimum EE for the three cases are compared by simulation results.

We study a special case of Willems's two-user multiaccess channel with partially cooperating encoders from a security perspective. This model differs from Willems's setup in that only one encoder, Encoder 1, is allowed to conference; Encoder 2 does not transmit any message, and there is an additional passive eavesdropper from whom the communication should be kept secret. For the discrete memoryless (DM) case, we establish inner and outer bounds on the capacity-equivocation region. The inner bound is based on a combination of Willems's coding scheme, noise injection, and additional binning that provides randomization for security. For the memoryless Gaussian model, we establish lower and upper bounds on the secrecy capacity. We also show that, under certain conditions, these bounds agree in some extreme cases of cooperation between the encoders. We illustrate our results through some numerical examples.

We investigate the problem of secure transmission over a two-user multi-input multi-output (MIMO) X-channel in which channel state information is provided with one-unit delay to both transmitters (CSIT), and each receiver feeds back its channel output to a different transmitter. We refer to this model as MIMO X-channel with asymmetric output feedback and delayed CSIT. The transmitters are equipped with M antennas each, and the receivers are equipped with N antennas each. For this model, accounting for both messages at each receiver, we characterize the optimal sum secure degrees of freedom (SDoF) region. We show that, in the presence of asymmetric output feedback and delayed CSIT, the sum SDoF region of the MIMO X-channel is the same as the SDoF region of a two-user MIMO BC with 2M antennas at the transmitter, N antennas at each receiver, and delayed CSIT. This result shows that, upon availability of asymmetric output feedback and delayed CSIT, there is no performance loss in terms of sum SDoF due to the distributed nature of the transmitters. Next, we show that this result also holds if only output feedback is conveyed to the transmitters, but in a symmetric manner, i.e., each receiver feeds back its output to both transmitters and no CSIT. We also study the case in which only asymmetric output feedback is provided to the transmitters, i.e., without CSIT, and derive a lower bound on the sum SDoF for this model. Furthermore, we specialize our results to the case in which there are no security constraints. In particular, similar to the setting with security constraints, we show that the optimal sum DoF region of the (M,M,N,N)-MIMO X-channel with asymmetric output feedback and delayed CSIT is the same as the DoF region of a two-user MIMO BC with 2M antennas at the transmitter, N antennas at each receiver, and delayed CSIT. We illustrate our results with some numerical examples.

We consider a three-terminal state-dependent relay channel with the channel state available noncausally at only the source. Such a model may be of interest for node cooperation in the framework of cognition, i.e., collaborative signal transmission involving cognitive and noncognitive radios. We study the capacity of this communication model. One principal problem is caused by the relay's not knowing the channel state. For the discrete memoryless (DM) model, we establish two lower bounds and an upper bound on channel capacity. The first lower bound is obtained by a coding scheme in which the source describes the state of the channel to the relay and destination, which then exploit the gained description for a better communication of the source's information message. The coding scheme for the second lower bound remedies the relay's not knowing the states of the channel by first computing, at the source, the appropriate input that the relay would send had the relay known the states of the channel, and then transmitting this appropriate input to the relay. The relay simply guesses the sent input and sends it in the next block. The upper bound accounts for not knowing the state at the relay and destination. For the general Gaussian model, we derive lower bounds on the channel capacity by exploiting ideas in the spirit of those we use for the DM model; and we show that these bounds are optimal for small and large noise at the relay irrespective to the strength of the interference. Furthermore, we also consider a relay model with orthogonal channels from the source to the relay and from the source and relay to the destination in which the source input component that is heard by the relay does not depend on the channel states. We establish a better upper bound for both DM and Gaussian cases and we also characterize the capacity in a number of special cases.

This paper compares the energy efficiency of some cooperative MIMO schemes in wireless networks. By energy efficiency we denote the spectral efficiency seen at the receiver normalized by the total energy consumption, which includes the circuitry, the efficiency of the power amplifier, and the transmission rate. We focus on transmit antenna selection (TAS) and switch and stay combining (SSC) at the receiver. The performance of TAS+SSC is compared to that of TAS and maximal ratio combining (MRC), and to that of transmit/receive beamforming using a singular value decomposition (SVD) technique. We derive closed-form outage probability expressions, and analyze the effect of selecting the antenna from the source to optimize the communication with the relay or with the destination. Our results show that selecting the antennas with respect to the destination is in general a better option when the energy consumption is accounted. Moreover, some power allocation strategies are described and the comparison of the schemes in terms of energy efficiency reveals a considerable improvement with the use of TAS+SSC for low to moderate spectral efficiency, while beamforming outperforms the other schemes for high spectral efficiency when the number of antennas at each node is small.

This paper considers weighted sum rate maximization constrained with a per base station (BS) antenna power problem for multiuser multiple-input multiple-output (MIMO) systems. For this problem, we propose new downlink-uplink duality based solution. We solve the problem as follows. First, by introducing additional optimization variables, we reformulate our problem into an equivalent problem that incorporates a weighted sum mean-square-error (MSE) term. Second, we establish novel weighted sum MSE duality. The duality is established by modifying the input covariance matrix of the dual uplink problem, and formulating the noise covariance matrix of the uplink channel as a fixed point function. Third, we optimize the introduced variables and powers in the downlink channel by a Geometric Program (GP) method. Fourth, using the duality result and the solution of GP, we apply alternating optimization technique to solve the original downlink problem. In our simulation results, we have observed that the proposed duality based solution utilizes less power than that of existing algorithms.

This work deals with distributed estimation problem in hierarchical wireless sensor networks, where the network is divided into spatially disjoint groups called clusters. The sensors in each cluster observe a separate random source which is correlated with the sources being observed by other clusters. Each cluster has its designated cluster head (CH). The sensors in the clusters forward their observations to the CHs, which in turn communicate with a fusion center (FC). The estimation at the CHs and the FC is done based on the minimum mean square error estimation rule. To minimize the overall estimation distortion, we propose a power scheduling scheme that allocates power to the individual sensors and the CHs subject to constraints on the transmit power of individual clusters and the overall network. The correlation among the underlying sources leads to coupling of the optimization variables and the power allocation solution requires centralized computation, which may be computationally expensive. To this end, we propose an alternative formulation based on an upper-bound on the distortion function, which leads to a solution that exhibits favorable characteristics for distributed implementation. Simulation examples corroborate effectiveness of the proposed power scheduling scheme.

We consider a multiple access relay channel (MARC), in which a relay, based on the recently proposed compute-and-forward protocol, helps two transmitters to communicate with a common destination. The relay decodes a linear combination of the received symbols instead of the individual symbols then forwards the new symbol to the destination. The destination recovers two linear equations from the decoded signals. The two equations relate the transmitted symbols with integer coefficients at different computational rates. We propose an iterative algorithm to optimize the integer coefficients and the power allocation at the transmitters alternatively, so that the sum-rate is maximized. In each iteration, the integer coefficients are updated by solving a mixed-integer quadratic programming (MIQP) problem with quadratic constraints, while the power allocation is updated by solving a series of geometric programs using a successive convex approximation method. The simulation results show that the compute-and-forward strategy and the proposed optimization method can offer substantial gain over the standard amplify-and-forward and decode-and-forward protocols for this model.

This paper contains two parts. The first part presents a novel framework for the successive convex approximation (SCA) method to solve a general optimization problem, as well as its properties. This framework starts with making change of variables (COV), motivated by the fact that it might be easier to construct convex approximations for the problem after making the COV. Furthermore, a general method is proposed to construct a convex upper bound approximation (CUBA) for a nonconvex function that satisfies tightness and differentiation conditions. Moreover, a way is introduced to generalize that CUBA by incorporating a convex function. These methods lead to plenty of degrees of freedom for using the SCA method to solve a problem. The second part revisits state-of-the-art dynamic spectrum management (DSM) algorithms, namely the successive convex approximations for low-complexity (SCALE) algorithm, the convex approximation for distributed spectrum balancing (CA-DSB) algorithm and the difference-of-convex-functions algorithm based DSM (DCA-DSM) method, to show how they can be derived from the SCA and CUBA construction methods. Numerical experiments are shown to compare them.

This paper considers a multi-cell relay aided orthogonal frequency division multiple access (OFDMA) downlink system, in which all stations are coordinated by a central controller for resource allocation (RA). The decode-and-forward (DF) protocol with selection relaying (SR) is applied. The problem considered is the maximization of the weighted sum of per cell min-rate (WSMR) with a total power constraint in each cell. An iterative RA algorithm is proposed to optimize mode selection (decision whether the relay should help or not), subcarrier assignment (MSSA) and power allocation (PA) alternatively. Each iteration is composed of the MSSA stage and the PA stage. During the MSSA stage, instead of the original objective function, a lower bound is maximized leading to lower complexity. The lower complexity problem is decoupled into mixed integer linear programs (MILP) that can easily be solved by typical MILP solvers. During the PA stage, an algorithm based on single condensation and geometric programming PA (SC-GPPA) is designed to optimize PA with the tentative MSSA results. The convergence of the proposed RA algorithm is proven. Finally, the performance of the RA algorithm and the benefit of using SR are illustrated through numerical experiments.

We analyze the energy efficiency of reactive and proactive relay selection algorithms under the incremental decode-and-forward protocol. By taking into account the consumption of the RF circuitry, the transmit power, and a nonlinear model for the battery, we show that a large number of available relays can actually compromise the energy efficiency of the system. Our results show that, depending on the source to destination distance, it may be preferable to consider only a small subset of nodes and select the relay among these nodes.

We investigate the problem of secure communication over parallel relay channel in the presence of a passive eavesdropper. We consider a four-terminal relay-eavesdropper channel which consists of multiple relay-eavesdropper channels as subchannels. For the discrete memoryless model, we establish outer and inner bounds on the rate-equivocation region. The inner bound allows mode selection at the relay. For each subchannel, secure transmission is obtained through one of two coding schemes at the relay: decoding-and-forwarding the source message or confusing the eavesdropper through noise injection. For the Gaussian memoryless channel, we establish lower and upper bounds on the perfect secrecy rate. Furthermore, we study a special case in which the relay does not hear the source and show that under certain conditions the lower and upper bounds coincide. The results established for the parallel Gaussian relay-eavesdropper channel are then applied to study the fading relay-eavesdropper channel. Analytical results are illustrated through some numerical examples.

This paper considers the downlink of a multi- cellular decode-and-forward (DF) relayed OFDMA system, in which multiple base stations (BSs) and relay stations (RSs) are coordinated by a centralized resource allocation (RA) scheme. We consider the problem of maximizing the sum rate of all cells subject to a total power constraint. Three iterative RA schemes are proposed to optimize subcarrier allocation, mode selection (decision whether a relay should help and which one) and power allocation alternatively with the sum rate increasing until convergence. During each iteration, the subcarrier allocation and mode selection (SAMS) is either initialized by a conditioned subcarrier allocation and mode selection (CSAMS) algorithm or updated by a joint subcarrier allocation and mode selection (JSAMS) algorithm with the tentative power allocation result. The power allocation (PA) is updated by either single condensation based geometric programming power allocation (SC-GPPA) or conditioned water filling power allocation (CWFPA). The performances of the three RA schemes are compared by means of numerical experiments and the convergence is also illustrated.

This work addresses the problem of joint quantization and power allocation in wireless sensor networks where sensors observe a source, quantize their observations and transmit to a fusion center (FC) which reconstructs the source using linear minimum mean-squared error (LMMSE) estimation rule. The sensors employ scalar quantizers to quantize the observations. We formulate the reconstruction distortion without imposing any statistical structure on the quantization noise and without making any simplifying assumption about the contribution of the channel errors to the reconstruction distortion. Based on the formulation, we outline a solution to the problem of joint quantization and power allocation based on minimization of the distortion subject to a constraint on the network transmit power. We illustrate the effectiveness of the proposed solution with some numerical examples.

This paper considers the joint precoder design problem for multiple-input single-output (MISO) systems with coordinated base stations (BSs). We consider maximization of the total sum rate with per BS antenna power constraint problem. For this problem, we propose a novel linear iterative algorithm. The problem is solved as follows. First, by introducing additional optimization variables and applying matrix fractional minimization, we reformulate the original problem as a new problem. Second, for the given precoder vectors of all users, we optimize the introduced variables of the latter problem using Geometric Programming (GP) method. Third, keeping the introduced variables constant, the precoder vectors of all users are optimized by using phase rotation technique. The second and third steps are repeated until convergence. We have shown that the proposed algorithm is guaranteed to converge. Moreover, for the total sum power constraint case, simulation results show that the proposed iterative algorithm achieves almost the same average performance as that of the algorithm which utilizes mean-square-error (MSE) uplink-downlink duality approach. We also show that our iterative algorithm can be used to solve sum rate maximization and weighted sum MSE minimization problems for an arbitrary power constraint.

This paper considers transceiver design problem for downlink multiuser multiple-input multiple-output (MIMO) systems. We examine minimization of sum mean-square-error (MSE) constrained with each base station (BS) antenna power problem. The problem is examined for the practically relevant scenario where the noise vector of each mobile station (MS) is a zero-mean circularly symmetric complex Gaussian random variable with arbitrary covariance matrix. We propose a novel downlink-uplink duality based iterative solution to solve the problem. The problem is solved as follows. First, we establish novel sum MSE downlink-uplink duality. Our duality is established by formulating the noise covariance matrix of the uplink channel as a fixed point function. Second, we formulate the power allocation part of each problem in the downlink channel as a Geometric Program (GP). Third, using the duality result and the solution of GP, we utilize alternating optimization technique to solve the original downlink problem. In our simulation results, we have observed that the proposed duality based solution utilizes less power than that of existing algorithm.

Cognitive radios have been introduced as a dynamic way to share the frequency spectrum within wireless networks. After sensing its environment to discover the available frequency resources, a cognitive network allocates the locally available carriers among its nodes, under the constraint of negligible interference on licensed operators. The allocation, based on partial knowledge of the network parameters, must be optimized in order to provide maximum rates in the cognitive network. In addition, having a stable allocation reduces the control traffic inherent in dynamic networks. This paper presents a new and fast iterative way to allocate the available carriers, that reduces the control traffic and provides fairness at the same time. Using the properties of a proportionally fair objective function, we fasten the optimum search in the space of possible allocations, and reach that optimum with no approximation. Numerical results show that the proposed iterative algorithm is less complex than an analytical solution in usual dynamic carrier allocation scenarios.

In relay-aided wireless transmission systems, one of the key issues is how to manage the energy resource at the source and each individual relay, to optimize a certain performance metric. This paper addresses the sum rate maximized resource allocation (RA) problem in an orthogonal frequency division modulation (OFDM) transmission system assisted by multiple decode-and-forward (DF) relays, subject to the individual sum power constraints of the source and the relays. In particular, the transmission at each subcarrier can be in either the direct mode without any relay assisting, or the relay-aided mode with one or several relays assisting. We propose two RA algorithms which optimize the assignment of transmission mode and source power for every subcarrier, as well as the assisting relays and the power allocation to them for every {relay-aided} subcarrier. First, it is shown that the considered RA problem has zero Lagrangian duality gap when there is a big number of subcarriers. In this case, a duality based algorithm that finds a globally optimum RA is developed. Most interestingly, the sensitivity analysis in convex optimization theory is used to derive a closed-form optimum solution to a related convex optimization problem, for which the method based on the Karush-Kuhn-Tucker (KKT) conditions is not applicable. Second, a coordinate-ascent based iterative algorithm, which finds a suboptimum RA but is always applicable regardless of the duality gap of the RA problem, is developed. The effectiveness of these algorithms has been illustrated by numerical experiments.

When a telecommunication system is constrained in terms of delay and complexity, it is usually wise to allow some cross-layer cooperation between the source and channel layers. In this context, the success of joint source-channel turbo techniques has been attested several times in the literature, in particular to transmit variable length code (VLC) streams which are very sensitive to error propagation. Capitalizing on previously developed performance upper bounds, this paper investigates whether the VLC can contribute to the interleaving gain of concatenated codes just as a convolutional code with non-catastrophic encoder would. To this end, the important concept of bounded VLC spectrum is introduced and is proved to be a sufficient condition for the VLC to contribute indeed to the interleaving gain. This concept is also proved to be closely related to non-catastrophic VLCs and, under certain assumptions, to the well known concept of statistically synchronizable VLCs.

The optimization of power allocation in DSL systems is a well studied non-convex problem. In recent years many algorithms have been proposed to solve this problem, but due to its non-convexity, researchers had to rely on heuristic, or exhaustive research methods. In our approach we make use of the similarities of the channel gain between 2 adjacent tones to overcome the non-convexity limitation of gradient methods. This allows the proposition of an efficient and a fast routine that manages to speed up the convergence of existent state of the art algorithms.

This work addresses the bit-wise optimal data detection problem when unknown nuisance parameters influence the observation at the receiver. For an arbitrary communications system, the optimal maximum a-posteriori detection problem is first defined as a marginalization of a joint distribution which statistically models the interaction of available sets of variables/parameters. Then, using a factor graph representation with an accompanying sum-product message passing algorithm, it is shown that the marginalization can be performed iteratively. To alleviate complexity due to the marginalization over continuous natured nuisance parameters, variational Bayesian approximation is introduced and it is shown that, if the nuisance parameters are constant for a period of time, the receiver has linear complexity.

We consider the downlink of a multicell OFDM system where the frequency reuse factor is 1. Base-stations cooperate and precode the symbols intended for the mobile stations (terminals) located in different cells and operating on the same frequency, in order to precompensate the co-channel interferences (CCIs). To design the precoders, the CCI coefficients have to be estimated. We assume that the mobile stations are able to estimate their SINR that they feedback to their base-station. By properly designing a perturbation signal, it is possible for the base-station to estimate the complex valued CCI coefficients from the SINRs fed back. We investigate the maximum likelihood (ML) estimation of co-channel coefficients from SINR measurements. We obtain the associated Cramér-Rao bound and the mean square error of a practical estimator. Finally a two-cells system is considered and we investigate the impact of such a co-channel estimation on the sum rate of the system when precoding is operated based on these estimates.

This paper considers the problem of jointly designing the precoders for the downlink multiuser multiple-input multiple-output (MIMO) systems where imperfect channel state information (CSI) is available at the base station (BS). The multi-antenna users are assumed to employ the linear minimum-mean-square-error (MMSE) receivers. Our objective is to maximize the achievable sum rate under a total BS power constraint and provide robustness against the channel uncertainties. We apply the familiar worst-case performance optimization approach, which in our case turns to be the problem of maximizing the worst-case sum rate constrained with the total BS power. The problem is examined as follows. We first reformulate the expression for the MMSE matrix so that it is conveniently utilized for the worst-case sum rate maximization problem. Then, we solve the resulting robust design problem efficiently by employing the existing mean-square-error (MSE) uplink/downlink duality approach. Computer simulations verify the robustness of the proposed design when compared to the non-robust/naive design.

This paper presents a novel fair scheme for resource sharing between nodes in OFDMA mesh networks. The problem is to maximize the overall system rate, under each user's maximal power and minimum rate constraints. To solve the underlying problem, we propose an approach that combines the merits of the well known Lagrange dual framework and the Lambert-W function. By using the Lambert-W function, resource allocation can not only be expressed in closed form but it can also quickly be determined without resorting to complex algorithms since a number of popular mathematical softwares, including Matlab, contain the Lambert-W function as an optimization component. Simulation results are provided to compare the performance of the proposed scheme with other allocation schemes.

We consider a wireless sensor network deployed to observe a physical phenomenon. The sensors amplify and forward their observations to a remote fusion center via single hop. The objective is to maximize the operational lifetime of the network such that the estimate of the underlying source at FC satisfies a certain fidelity criterion given by the maximum tolerable estimation distortion. Each sensor is powered by a battery which limits its lifetime and consequently of the network also. Recent studies show that the battery discharge behavior is dependent on the load current: higher current leads to higher losses inside the battery due to the non-linearities of the electrochemical reaction in the battery. This work presents a power allocation design where goal is to maximize the network lifetime incorporating the non-linear discharging behavior of the batteries. The design is based on the knowledge of the instantaneous channel gains as well as when we only know the channel statistics. The numerical examples illustrate that the impact of battery-aware power scheduling on the network life is substantial.

Self-localization in ad-hoc sensor networks is becoming a crucial issue for several location-aware applications. This technology implies the combination of absolute anchor locations with relative inter-node information exchanged on a peer-to-peer basis. In this paper we investigate a distributed algorithm and fundamental performance bounds for Bayesian cooperative localization in stochastic networks. Nodes are assumed to be randomly deployed within a finite space according to a prior distribution. Bayesian inference is performed through an iterative local message passing procedure based on belief propagation and particle-filtering message representation. The algorithm performance is analyzed for a simplified scenario in which unknown node positions are randomly scattered along a line segment and anchors are fixed. Global Cramer-Rao bounds are derived and compared to the performance of the distributed algorithm.

This paper considers the downlink of a cellular orthogonal frequency division multi-access (OFDMA) system, in which multiple base stations (BS) are coordinated by a centralized resource allocation algorithm. We address the problem of maximizing the weighted sum min-rate (WSMR) subject to a total power constraint at each BS, in terms of jointly optimizing coordinated BSs' subcarrier and power allocation. In particular, this problem leads to a resource allocation that guarantees similar rates to users in each cell. An iterative algorithm is proposed to optimize subcarrier and power allocation alternatively, so that the WSMR keeps increasing until convergence. In each iteration, the subcarrier allocation is updated by solving a mixed integer linear programming problem for each cell, while the power allocation is updated by solving a successive set of convex optimization problems with an algorithm based on Karush-KuhnTucker conditions. The effectiveness of the algorithm is illustrated by numerical experiments.

We consider a three-terminal state-dependent relay channel with the channel state available non-causally at only the source. Such a model may be of interest for node cooperation in the framework of cognition, i.e., collaborative signal transmission involving cognitive and non-cognitive radios. We study the capacity of this communication model. One principal problem in this setup is caused by the relay's not knowing the channel state. In the discrete memoryless (DM) case, we establish lower bounds on channel capacity. For the Gaussian case, we derive lower and upper bounds on the channel capacity. The upper bound is strictly better than the cut-set upper bound. We show that one of the developed lower bounds comes close to the upper bound, asymptotically, for certain ranges of rates.

Reliability of the communication systems depends hugely on the receiver performance where the synchronization and detection tasks need to be performed. Classically these two tasks are attended separately resulting in simple yet non-optimal receivers. During the last decade, a family of iterative receivers has been introduced to approximate the optimal solution to joint estimation and detection problem by means of the turbo principle. With the help of graph theory and the belief propagation framework these receiver structures are unified and soft information driven schemes emerged, leading to more reliable detection. The essence of these schemes lays in factorization of a global function whose marginal corresponds to the objective function and obtained via simple message passing algorithms. On the other hand, as far as our knowledge, all of the proposed structures pursue a specific factorization while devising their respective schemes. In this work utilizing a different factorization, we introduce a novel iterative receiver for joint equalization/detection problem. With the aid of Variational Bayesian approximation we show that the complexity can be reduced without sacrificing the error performance drastically.

Variable length codes (VLCs), used in data compression, are very sensitive to error propagation in the presence of noisy channels. Addressing this problem with joint source-channel turbo techniques has been proposed in the literature and looks quite promising. But to date, most code-related conclusions are based on simulations. This paper states and proves several theoretical results about the robustness of prefix VLCs concatenated with linear error correcting codes (ECC), assuming a maximum likelihood decoder. Especially, an approximate and asymptotically tight distance spectrum of the concatenated code (VLC+ECC) is rigorously developed. Together with the union bound, it provides upper bounds on the symbol and frame/packet error rates.

In this paper, we consider a three-terminal state-dependent relay channel (RC) with the channel state noncausally available at only the relay. Such a model may be useful for designing cooperative wireless networks with some terminals equipped with cognition capabilities, i.e., the relay in our setup. In the discrete memoryless (DM) case, we establish lower and upper bounds on channel capacity. The lower bound is obtained by a coding scheme at the relay that uses a combination of codeword splitting, Gel'fand-Pinsker binning, and decode-and-forward (DF) relaying. The upper bound improves upon that obtained by assuming that the channel state is available at the source, the relay, and the destination. For the Gaussian case, we also derive lower and upper bounds on the capacity. The lower bound is obtained by a coding scheme at the relay that uses a combination of codeword splitting, generalized dirty paper coding (DPC), and DF relaying; the upper bound is also better than that obtained by assuming that the channel state is available at the source, the relay, and the destination. In the case of degraded Gaussian channels, the lower bound meets with the upper bound for some special cases, and, so, the capacity is obtained for these cases. Furthermore, in the Gaussian case, we also extend the results to the case in which the relay operates in a half-duplex mode.

In this work, we derive a blind equalizer that pursues the maximization of an objective function, consisting of the ratio between the square of the mean signal power and the variance of the signal power. The performance of the addressed equalizers is then investigated by focusing on DS/CDMA communication environments in a downlink scenario. In particular, we have evidenced the effectiveness of the presented equalizer in the numerical examples, in terms of robustness against the effect of interference, as well as in terms of convergence rate, in spite of a small amount of extra processing.

In some fading environments, there may not be a feedback link sufficiently fast to convey the full channel state information (CSI) to the transmitter. This paper considers resource allocation strategies for downlink multiuser mobile WiMAX systems, where the base station knows only the channel distribution information (CDI), but has no knowledge of the instantaneous channel realization. The base station uses CDI to assign subchannels and allocate power to users with the objective to maximize the ergodic weighted sum rate while satisfying minimum rate, long-term fairness and power constraints. We solve the underlying constrained optimization problem using the Lagrange dual decomposition framework. The proposed method has a complexity of O(KM) for K users and M subchannels. Simulation results are provided to compare the performance of this method with other allocation schemes and to illustrate the trade-off between maximized weighted sum rate and the constraints.

In this paper we investigate the tracking performance of the downstream (DS) crosstalk (XT) channel estimation based on the reported signal to noise ratio (SNR), in particular for digital subscriber line (DSL) systems. Aiming to its simplicity, the SNR-assisted XT estimation, has been recognized in ITU as a backward compatible method that does not require any change in the very high speed digital subscriber line 2 (VDSL2) standard. This low complex algorithm can be used for XT channel estimation in dynamic spectrum management (DSM) techniques today. The algorithm as proposed, relies on sending perturbing signals on the victim lines (VLs) and reporting the SNRs by those lines to acquire the crosstalk channel from some disturber line (DL) to the VLs. We generalize this concept to include full startup, tracking and joining scenarios as well as the impact of different perturbation signal choices. Simulation results reveal that starting from no crosstalk precompensation, and updating a precoder matrix based on the DS crosstalk channel estimates, the far-end crosstalk (FEXT) free SNR can be reached in few iterations (36 SNR measurements for the four lines case).

In this paper, we present a new method to estimate the crosstalk channels in VDSL systems, allowing to implement well-known pre-compensation schemes. As opposed to previously presented methods, this estimation only requires minimal changes to the current standard and equipments. It is based on the concept of adding small, controlled, perturbations to the transmitted signal and observing the related changes to the SNR at the receiver. It is shown in this paper that, based on a limited amount of SNR measurements from the receivers, it is possible to accurately estimate the crosstalk channels, both in amplitude and phase.

In this paper we study the impact of the overlapping between neighboring MPCs (multipath component) on the performance of channel estimation. We consider IR-UWB (impulse radio) signals, and the IEEE802.15.3a and IEEE802.15.4a UWB channel models. We show that for a pulse width (PW) sufficiently smaller than the average MPC rate of arrival (ROA) the probability to have more than three overlapping MPCs is relatively small. We derive the CRBs (Cramer Rao bound) for the joint estimation of the MPC gain and TOA (time of arrival) in the case of up to three overlapping MPCs. We compute also the average CRBs. We show that the CRBs obtained by averaging more than 80% of possible cases of the channel, are very close to the bounds obtained under the non-overlapping assumption (NOLA).

We derive the CRBs (Cramer Rao bound) for the joint estimation of the TOA (time of arrival) and the AOA (angle of arrival) in wideband (WB) MISO (multiple input single output) and MIMO (multiple input multiple output) systems. We consider both cases of orthogonal and non-orthogonal transmitted signals. We compare the CRBs obtained in SISO (single input single output), SIMO (single input multiple output), MISO and MIMO systems under the assumption that the total transmitted energy is the same for all systems. We show that SIMO and MIMO are equivalent for TOA estimation, and MISO and SISO as well when the transmitted signals are orthogonal. For non-orthogonal signals, MIMO is better than SIMO, and MISO is better than SISO when the received signals are constructive. For AOA estimation, we show that MIMO is better than SIMO and SIMO is better than MISO when the transmitted signals are orthogonal. For non-orthogonal signals, MIMO is much better when the received signals are constructive. The CRBs obtained for non- orthogonal signals are very sensitive to the angle. Numerical results obtained in a typical scenario are provided.

Compress-and-Forward is a protocol for transmission over relay networks in which the relay forwards a compressed version of the signal it observes. The compression method used by the relay is source coding with side information, i.e. Wyner-Ziv coding, since the destination can use the signal it receives directly from the source as side information. This paper addresses the case of a wireless relay network with orthogonal transmissions from the source and the relay terminals; we show that when the transmitters have no instantaneous channel state information the optimal compression parameters often make Wyner-Ziv coding reduce to conventional source compression, i.e. compression that does not take into account the side information available at the destination. This result simplifies the implementation of the CF protocol in the case we consider, since it shows that in several situations one can use more convenient compression methods without significant performance loss.

An efficient and flexible air interface is the necessary condition for enabling high data rates next generation wireless systems. A practical answer to this need consists in exploiting channel state information at the transmitter for an adaptive and efficient use of the available radio link resources. This paper contributes with a novel strategy for the allocation of the sub-carrier transmit power in the case of a wireless system featuring: i) bit-interleaved coded modulation (BICM); ii) orthogonal frequency division multiplexing (OFDM); iii) multiple antenna profile (MIMO). The proposed power-allocation algorithm aims at maximizing the so-called goodput performance metric for packet transmissions employing automatic repeat request (ARQ) schemes. In addition, it is also proven to be near-optimum in maximizing the input/output mutual information of the MIMO-OFDM subchannels. Numerical simulations over typical wireless indoor scenarios confirm the effectiveness of the procedure when applied in the context of MIMO-BICM-OFDM systems.

We consider an OFDM (orthogonal frequency division multiplexing) point to point transmission scheme improved by a relay. For each carrier, symbols sent by the source may be retransmitted during a second time slot by the relay, which is assumed to be of the decode-and-forward (DF) type. For each relayed carrier the destination implements maximum ratio combining. Assuming perfect CSI (channel state information) knowledge the paper investigates the power allocation problem in order to maximize the rate offered by the scheme. Compared to, the second time slot is better used. The source is allowed to transmit a new symbol during this second time slot when the relay is inactive. For this improved protocol, the optimization has been conducted for a sum power constraint and reported in. The present paper is devoted to the case of individual power constraints at the source and at the relay. The theoretical analysis is illustrated by numerical results.

A relay interferer channel consists of the classic relay channel with an additional source of interference. A three- terminal full-duplex Gaussian relay interferer channel with a cognitive source is analyzed. Each of the relay node and the destination node experiences on its link an additive Gaussian outside interference, in addition to additive noise. Only the source node, referred to as being the cognitive encoder, knows the interferences, in a non-causal manner. We first focus on the case in which the links to the relay and to the destination are corrupted by the same interference; and then we focus on the case of independent interferences. For each of these two models, we establish a lower bound on the channel capacity. The coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decode-and-forward relaying. The results reveal that, by opposition to carbon copying onto dirty paper and its root Costa's initial dirty paper coding (DPC), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn.

We consider a two-user state-dependent multiaccess channel in which only one of the encoders is informed, non-causally, of the channel states. Two independent messages are transmitted: a common message transmitted by both the informed and uninformed encoders, and an individual message transmitted by only the uninformed encoder. We derive inner and outer bounds on the capacity region of this model in the discrete memoryless case as well as the Gaussian case. Further, we show that the bounds for the Gaussian case are tight in some special cases.

We consider the problem of transmission over a relay version of the carbon-copying onto dirty paper. In this setup, additive Gaussian outside interferences corrupt both transmissions to the relay and to the destination; and only the source knows the interferences (in a noncausal manner). We first focus on the case of one interference corrupting both links; and then we focus on the case of two independent interferences. For each of these two models, we establish a lower bound on the channel capacity. The coding schemes for the lower bounds use techniques of dirty paper coding or carbon copying onto dirty paper, interference reduction at the source and decodeand-forward relaying. The results reveal that, by opposition to carbon copying onto dirty paper and its root Costa's initial dirty paper coding (DPC), it may be beneficial in our setup that the informed source uses a part of its power to partially cancel the effect of the interference so that the uninformed relay benefits from this cancellation, and so the source benefits in turn. The established results may be of importance for the emerging field of cooperation in presence of some cognitive radios that might be aware of some of other users messages intended to a common receiver.

Coded multi-antenna and multi-carrier techniques combined together with link resources adaptation algorithms are the key technologies toward efficient high-data-rate communications over wireless fading channels. The practicability of this concept, however, requires that the transmitter can perform accurate and simple evaluation of the actual link performance. This paper contributes with a novel method specifically developed to predict the link performance of bit-interleaved coded MIMO- OFDM links, which offers improved accuracy at the price of lower complexity when compared with conventional techniques. Its effectiveness is confirmed through extensive simulation results obtained over typical wireless channel environments.

We consider an OFDM (orthogonal frequency division multiplexing) point to point transmission scheme improved by means of multiple relays. For each carrier, symbols sent by the source during a first time slot, may be retransmitted during a second time slot by the relays, which are assumed to be of the decode-and-forward (DF) type. For each relayed carrier the destination implements maximum ratio combining. Assuming perfect CSI (channel state information) knowledge the paper investigates the power allocation problem in order to maximize the rate offered by the scheme. Similarly to the protocol proposed in, the source is allowed to transmit a new symbol during the second time slot when none of the relay is assisting. The constraints of decodability at the relays are properly handled. The optimization is conducted for a constraint on the sum of powers at the source and at the relays. Next to the optimized solution, a suboptimum method based on relay selection is proposed and discussed. The theoretical analysis is illustrated by numerical results.

Cooperative information embedding deals with the problem of embedding unperceived information into some cover signal by different users or partners, cooperatively. It models applications in which embedded signals, or watermarks, transmitted over wireless networks need to be reinforced in order to withstand channel impairments. In cooperative information embedding, each embedder that can reinforce the embedded signal may or may not know the original cover signal. In this paper, we concentrate on the two user cases: (1) an initial embedder and (2) an assisting embedder or helper collaborate to embed some watermark into given digital media content which is transmitted over a wireless network. One important application is that of infrastructure-aided information embedding, a case in which the network provider plays the role of a helper and contributes to securing the distribution of the media, not only by blocking unauthorized signals but also by reinforcing the watermarks in legitimate signals. We investigate the two scenarios in which the helper does or does not know the cover signal. For each scenario, we derive lower and upper bounds on channel capacity. Furthermore, we also design implementable coding schemes and derive the embedding rates practically allowed by these schemes, for both scenarios. Among others, the performance characterization shows that for cooperative information embedding to be effective, careful code design is required at the initial embedder and the helper. The careful design concerns the joint conception of the embedded codes and the exploitation of the knowledge of the cover signal, if any.

Interest in distributed source coding (DSC) has increased in recent years due to the development of wireless networks. In this paper we propose a solution based on a new rateless class of codes, the Raptor codes. In real applications (where the data source length and the correlation between the sources may vary), rateless codes can be naturally adapted by generating just a single codeword with suitable length. Raptor codes were already considered by Caire et al. (2005) for the lossless compression of a single source.

The optimization of power allocation in DSL systems is a well studied non-convex problem. In recent years many algorithms have been proposed to solve this problem, but due to the non-convexity, researchers had to rely on heuristic, or exhaustive search algorithms. Iterative spectrum balancing (ISB) is one of these algorithms, that relies on iterative exhaustive search over individual power to achieve the optimization. In this paper we propose to take advantage of an approximate gradient model to reduce the complexity of ISB. Furthermore techniques such as the additional starting point (ASP) and successive optimization are used to bring the result closer to the global optimum.

In this paper we consider an OFDM (orthogonal frequency division multiplexing) transmission scheme with a relay, working in decode-and-forward (DF) mode. Assuming perfect CSI (channel state information) the paper investigates the power allocation problem for rate maximization of the scheme with individual power constraints at the source and at the relay. The theoretical analysis provides a deep understanding of the structure of the solution. Based on this, an efficient iterative algorithm is proposed that exhibits a quicker convergence than classical methods. In addition, it enables to solve the convergence issues observed in some situations.

Cooperation in wireless systems can achieve spatial diversity gains as well as coverage enhancement. In the usual decode-and-forward (DF) strategy, a relay cooperates only when it can decode successfully the signal received from the source. This paper presents instead a DF strategy in which the receiver manages to take advantage of forwarded signals containing errors too. This increases the level of cooperation and is shown to offer significant gains in bit error rate.

Adaptive resource allocation algorithms based on perfect channel state information at the transmitter (CSIT) improve the performance of OFDMA systems. However, perfect CSIT is rarely possible due to channel estimation errors and channel feedback delay. In this paper, we consider practical subchannel assignment and power allocation strategies for downlink multiuser OFDMA systems, where the base station has imperfect CSI. The goal is to maximize the expected weighted sum rate while satisfying users' minimum data rate and system fairness requirements under total power constraint. We use the Lagrange dual decomposition framework to derive an algorithm that efficiently finds the optimal allocation. Simulation results show the impact of the channel estimation error on the performance of the system and illustrate the trade-off between maximized expected weighted sum rate and the constraints.

This paper deals with the power allocation problem for coded multicarrier transmission. Specifically, we focus on a bit interleaved coded modulation (BICM) packet transmission implemented with orthogonal frequency division multiplexing (OFDM) and in the presence of automatic repeat request (ARQ) protocol. Capitalizing on the binary-input output-symmetric (BIOS) nature of the BICM channel it is provided a simple upper-bound of the rate of information bits received without any error, the so called goodput. Based on this theoretical characterization, we develop a power allocation strategy among the different subcarriers so that the system goodput performance metric is maximized. The effectiveness of the proposed method is numerically testified for BICM-OFDM transmission in the context of the typical WLAN scenario.

We consider OFDM (orthogonal frequency division multiplexing) transmission helped by a relay. Symbols sent by the source may or may not be retransmitted by a relay during a second time slot. The relay is supposed to operate in Decode-and-Forward (DF) mode. For each carrier the destination implements maximum ratio combining. Assuming perfect CSI (channel state information) knowledge the paper investigates the power allocation problem for rate maximization of the scheme. Both cases of a sum power constraint, and of individual power constraints at the source and at the relay are tackled. The theoretical analysis is illustrated by numerical results for both types of constraints.

We consider a state-dependent full-duplex relay channel with the state of the channel non-causally available at only the relay. In the framework of cooperative wireless networks, some specific terminals can be equipped with cognition capabilities, i.e, the relay in our model. In the discrete memoryless (DM) case, we derive lower and upper bounds on channel capacity. The lower bound is obtained by a coding scheme at the relay that consists in a combination of codeword splitting, Gelpsilafand-Pinsker binning, and a decode-and-forward scheme. The upper bound is better than that obtained by assuming the availability of state at the source, the relay, and the destination. For the Gaussian case, we also derive lower and upper bounds on channel capacity. The lower bound, obtained by a coding scheme based on combination of codeword splitting and generalized dirty paper coding, is tight in some cases if the channel is physically degraded. The upper bound is also better than that obtained by assuming that the channel state is available at the source, the relay, and the destination.

This paper contributes with an adaptive modulation scheme intended for bit interleaved coded (BIC) orthogonal frequency division multiplexing (OFDM) packet transmission in the presence of automatic repeat request (ARQ) protocol. The basic idea consists in properly combining the power allocation strategy with a bit-loading procedure among the different subcarriers so that the rate of information bits received without any error is maximized. Numerical simulations corroborate the effectiveness of the proposed scheme when operating over typical wireless environments.

Variable length codes (VLCs), used in data compression, are very sensitive to error propagation in the presence of noisy channels. To address this problem, several joint source channel turbo techniques have been proposed in the literature. In this paper, we focus on pairs of source/VLC of low redundancy, i.e., when there is a good match between the source statistics and the length distribution of the VLC. It is a case not considered extensively in the literature so far and the classical concatenation of a VLC and a convolutional code is not satisfying. Through EXIT chart and interleaving gain analysis, we show that the introduction of a repetition code between the VLC and the convolutional code considerably improves global performance. In particular, excellent symbol error rates are obtained with reversible VLCs which are used in recent source codecs.

This paper applies the concept of balanced capacity, a fair trade-off between individual and global performance, to the uplink of a Gaussian frequency-selective multiuser channel with K users, where K can be much larger than 2. Individual power constraints are applied to each transmitter, which makes the computation of the balanced capacity very complex. The concept of 'equivalent channel' is used to derive an explicit expression of the optimal power allocation, that remains compatible with the individual power constraints. The computation of the balanced capacity is then formulated as a set of 2K nonlinear equations. An iterative algorithm providing the exact solution is firstly introduced. A suboptimal solution, based on the Iterative Multiuser Water-Filling (IMWF) algorithm, is then proposed and shown to be very close to the optimal solution. The idea of this alternative method, called 'balanced water-filling', is to modify the power allocation obtained with the IMWF algorithm in order to get balanced data rates. Results are provided for a wireline access network with 20 users.

This contribution deals with code-aided hypothesis testing for wireless digital receivers. We provide a theoretical justification for a hypothesis testing algorithm that was previously introduced in (Wymeersch et al., 2006) based on ad-hoc arguments. Contrary to conventional hypothesis testing methods, the algorithm from Wymeersch et al. exploits the code structure within the received signal and does not require any pilot symbols. By doing so, it allows to improve the bandwidth-efficiency of the transmission. The present contribution shows that, under mild conditions, the performance of the algorithm from Wymeersch et al. coincides with the performance of the optimal Maximum A Posteriori (MAP) hypothesis test. Computer simulations support this result.

In this paper the problem of distributed source coding (DSC) of binary sources with side information at the decoder is addressed. We propose a scheme based on Raptor codes which are a new class of rateless codes. We adapt the decoding scheme to this problem by implementing the message passing strategy between the constituent decoders of Raptor codes at each decoding iteration. The proposed approach enables to achieve better performances than those achieved by the solutions based on turbo codes, and by the solutions based on regular low density parity check codes (LDPC) codes.

In this paper, we investigate diversity gain in coding for a 2-user multiple-access-channel (MAC) with cooperating transmitters-the MAC with relaying. We propose a simple distributed space-time-frequency block coding (D-STFBC) scheme and analyze the offered diversity gain. In particular, we show that full diversity (order 3) is possible if collaboration is well enough and rigorous signal processing is assumed both at the transmitters and the receiver. Bit-error-rate (BER) analysis and curves are provided for illustrative purposes.

This paper proposes iterative estimators of quasi static frequency selective channels. Their properties (in terms of expectation and mean-squared estimation error) as well as complexity are discussed. Their average performance is also analytically approached. For the sake of low complexity, the derived estimators are either linear or affine in the vector of observations at the channel output. Such estimators are referred to as iterative because they use soft information on data symbols fed back by the soft-in/soft-out (SISO) channel decoder of a turbo equalizer. Because involved in this iterative process, they perform better at low signal-to-noise ratios (SNRs) than standard (i.e. non iterative) channel estimators using the same number of pilot symbols. Conversely, iterative estimators require a smaller number of pilot symbols to achieve the same performance as standard estimators.

This paper addresses the design of the linear precoders and decoders of the complex Gaussian broadcast channel in which both the base station and the remote station are equipped with arrays of multiple antennas. An imperfect channel knowledge is assumed at the base station and the minimization of the sum of the mean square errors (MMSE) of the system's substreams is chosen as optimization criterion. A stochastic approach is taken to make the design robust against the channel estimation errors. The solution is based on an iterative algorithm whose convergence is guaranteed. Simulations results emphasize the benefit of the proposed design.

This paper aims at characterising the (mean) speed of convergence of the EM algorithm. We derive, under some simplifying assumptions, a relation between the EM algorithm mean convergence rate (MCR) and Cramer-Rao bounds (CRBs) associated to the so-called incomplete and complete data sets defined within the EM algorithm framework. We illustrate our derivations in the ease of carrier-phase estimation based on the EM algorithm, As far as our simulation setups are concerned, we show that the (mean) EM-algorithm behavior may be well predicted by means of the proposed CRB-based impression.

This paper investigates the sensitivity of the achievables rates for the full-duplex relay channel to small additive disturbances on channel links. The focus is on two relaying strategies - the decode-and-forward (DF) mode and the compress-and-forward (CF) mode. We use Fisher Information and De-Bruijn's identity to assess the decrease in the corresponding rates due to small additive contaminating noise. Analysis sheds light on the respective sensitivity levels of these schemes and hence, provides insights onto the choice of appropriate relaying strategies in the situations where some trade-off between transmission rate and sensitivity is needed. Next, we show that these results can be used to emphasize the effect of channel estimation error on relaying transmissions. An important (somehow intuitive) observation at this stage is that transmission through the direct link (i.e., relay is off) may improve upon both decode-and-forward and compress-and-forward schemes, when the channel is "bad enough". Finally, a lower bound on the capacity of a relay channel under channel estimation error is obtained by combining well known relaying strategies, each over the appropriate SNR range. Analysis is supported by some examples.

This paper deals with code-aided (CA) maximum-likelihood (ML) phase and timing ambiguity resolution. We propose a methodology based on the sum-product algorithm (SPA) to exactly solve this problem with a tractable complexity. In particular, we emphasize that the proposed ML ambiguity-resolution algorithm has a complexity which is at most equal to the complexity of recently-proposed powerful ML-like ambiguity-resolution methods. Finally, we compare through simulation results the ability of CA and conventional data-aided methods to resolve phase ambiguities.

This paper investigates a fair resource allocation method in crosstalk limited DSL (digital subscriber line) systems. As a measure of fairness, the concept of balanced capacity (BC), introduced in T. Sartenaer et al. (2005), is used. BC corresponds to a point on the boundary of the capacity region where each user experiences the same relative loss with respect to his maximum capacity. This is especially useful in near-far situations where some users can experience a huge capacity loss if the allocation is performed according to the sum-rate criterion (or any similar criterion). Our goal is to propose efficient algorithms to compute the BC point in DSL systems for constraints on individual power spectrum densities. Results are reported for typical crosstalk limited cases and are compared to a resource allocation optimized for the sum rate. The proposed algorithm is shown to be of low complexity.

In this paper we consider UWB (ultra wide band) based positioning. We derive the CRBs (Cramer Rao bound) for AOA (angle of arrival) and for hybrid method using both AOA and TOA (time of arrival) information. Both non modulated and modulated IR-UWB (impulse-radio) waveforms are considered. The UWB channel is supposed to be of the multipath type. The AOA technique is investigated without NB (narrow band) approximation usually made. The analytical results obtained for the CRBs are illustrated by numerical results for typical scenarios.

This paper addresses soft estimation of time-varying frequency selective channels using Kalman smoothing. The proposed estimator uses soft extrinsic information provided by a channel decoder. It is intended to improve the performance of an already existing Kalman filtering-based estimator by exploiting all - rather than part of - the data at the receiver disposal. It is the linear estimator exhibiting for the case of interest the minimum mean-squared estimation error. Its complexity is shown to be quite low. An approximated analytical calculation of the mean- squared estimation error (MSEE), both for Kalman filtering and Kalman smoothing, is also proposed. Simulation results illustrate the performance gain of smoothing over filtering and validate our calculation of the MSEE.

We address the problem of distributed source coding of binary sources with side information at the decoder. We propose a compression scheme using irregular turbo codes. We optimize them by maximizing the distance between the two curves of their EXIT charts for given statistics and a compression rate close to the Slepian-Wolf limit in order to increase the robustness of the scheme. This optimized irregular code enables us to achieve compression rates superior to the ones achieved by previously proposed turbo schemes without increasing the decoding complexity.

In this work, coding for the relay channel (RC) and the cooperative relay broadcast channel (RBC) controlled by random parameters are studied. In the first channel, the RC, information is transferred from the transmitter to the receiver through a multiplicity of nodes which all "simply" act as relays. In the second channel, the cooperative RBC, each intermediate node also acts as a receiver, i.e., it decodes a "private message". For each of these two channels, we consider the situation when side information (SI) Snon the random parameters is non- causally provided to the transmitter and all the intermediate nodes but not the final receiver, and derive an achievable rate region based on the relays using the decode-and-forward scheme. In the special case when the channels are degraded Gaussian and the side information (SI) is additive i.i.d. Gaussian, we show that 1) the rate regions are tight and provide the corresponding capacity regions and 2) the state Sndoes not affect these capacity regions, even though the final receiver has no knowledge of the state. For the degraded Gaussian RC, the results in this paper can be seen as an extension of those by Kim et al. to the case of more than one relay.

In this work, we consider a partially cooperative relay broadcast channel (PC-RBC) controlled by random parameters. We provide rate regions for two different situations: (1) when side information (SI) Snon the random parameters is non-causally known at both the source and the relay and, (2) when side information Snis non-causally known at the source only. These achievable regions are derived for the general discrete memoryless case first and then extended to the case when the channel is degraded Gaussian and the SI is additive i.i.d. Gaussian. In this case, the source uses generalized dirty paper coding (GDPC), i.e., DPC combined with partial state cancellation, when only the source is informed, and DPC alone when both the source and the relay are informed. It appears that, even though it can not completely eliminate the effect of the SI (in contrast to the case of source and relay being informed), GDPC is particularly useful when only the source is informed.

The introduction of turbo and low-density parity-check (LDPC) codes with iterative decoding that almost attain Shannon capacity challenges the synchronization subsystems of a data modem. Fast and accurate signal synchronization has to be performed at a much lower value of signal-to-noise ratio (SNR) than in previous less efficiently coded systems. The solution to this issue is developing specific synchronization techniques that take advantage of the presence of the channel code and of the iterative nature of decoding: the so-calledturbo-synchronizationalgorithms. The aim of this paper within this special issue devoted to the turbo principle is twofold: on the one hand, it shows how the many turbo-synchronization algorithms that have already appeared in the literature can be cast into a simple and rigorous theoretical framework. On the other hand, it shows the application of such techniques in a few simple cases, and evaluates improvement that can be obtained from them, especially in the low-SNR regime.

The principles which have been prevailing so far for designing communication systems rely on Shannon's source and channel coding separation theorem. This theorem states that source and channel optimum performance bounds can be approached as close as desired by designing independently the source and channel coding strategies. However, this theorem holds only under asymptotic conditions, where both codes are allowed infinite length and complexity. If the design of the system is constrained in terms of delay and complexity, if the sources are not stationary, or if the channels are nonergodic, separate design and optimization of the source and channel coders can be largely suboptimal. For practical systems, joint source–channel (de)coding may reduce the end-to-end distortion. It is one of the aspects covered by the term cross-layer design, meaning a rethinking of the layer separation principle. This article focuses on recent developments of joint source–channel turbo coding and decoding techniques, which are described in the framework of normal factor graphs. The scope is restricted to lossless compression and discrete-valued sources. The presented techniques can be applied to the quantized values of a lossy source codec but the quantizer itself and its impact are not considered.

Space-time code (STC) designs classically rely on the assumption of independent and identically distributed (i.i.d.) Rayleigh channels. However, poor scattering conditions may have detrimental effects on the performance of STCs. In this letter, we derive code-design criteria leading to robust STCs in a large variety of slow-fading propagation conditions. No channel knowledge is assumed at the transmitter. Codes satisfying these criteria are shown to perform much better on real-world channels than codes designed only for i.i.d. channels. As examples, the robustness of various spatial multiplexing schemes, linear dispersion codes, and space-time trellis codes is discussed based on those criteria

In this paper, we address the issue of symbol timing recovery for a coded burst transmission system. As direct maximum-likelihood (ML) estimation is intractable, we resort to the expectation-maximization (EM) algorithm in order to derive a receiver that iterates between data detection and synchronization. Conventional data-aided (DA) and decision-directed (DD) synchronizers can be interpreted as special cases of the proposed algorithm. The EM-based technique takes into account code properties and is especially well suited to scenarios where conventional schemes fail to provide the detector with a reliable timing estimate. The performance of the proposed algorithm is compared with conventional techniques through computer simulations, both in terms of mean-square estimation error (MSEE) and bit error rate (BER).

Iterative channel estimation can improve the channel- state information (CSI) with respect to noniterative estimation. New iterative channel estimators based on the expectation-maximization (EM) algorithm are proposed in this paper. A first estimator, called the unbiased EM (UEM), is designed to unbias the EM estimates. A second estimator is then put forward, which is based on the expectation-conditional-maximization (ECM) algorithm, and its complexity is lower than that of the EM. An unbiased ECM (UECM) estimator is also proposed. Although the unbiasedness of the UEM and UECM estimators is not rigorously proved, the use of these names is explained in the paper. The new estimators are compared with well-known ones, such as the EM, the decision-directed (DD), and the data-aided (DA) estimators. Simulations are reported for a turbo receiver operating over frequency-selective multiple-input multiple-output channels. It is shown that the UEM channel estimator outperforms the EM, and that the ECM-based estimators are very close to the EM-based ones.

We focus on resource allocation in a coded orthogonal frequency division multiplexing system. A frame-oriented transmission with convolutional coding and Viterbi decoding is considered. We suppose that only error-free frames are kept by the receiver, other frames are thrown away and have to be retransmitted. As a consequence, the only meaningful criterion for evaluating the performance of such a system is the error-free rate, or goodput. This criterion is a good compromise between the rate and bit error probability criterions. We here present a formulation for the goodput of the system and propose a bit and power allocation algorithm maximizing it. The proposed algorithm is then compared with other existing resource allocation strategies. Simulation results show that the proposed algorithm significantly improves the performance

This paper deals with iterative maximum-likelihood synchronization of a scalar parameter. An efficient implementation of the Newton-Raphson (NR) maximum-search method is proposed. Considering the latter implementation, the NR approach is shown to be an attractive alternative to synchronization methods based on the expectation-maximization (EM) algorithm. Simulation results for the case of phase-offset synchronization show that NR method usually increases the speed of convergence of the synchronization algorithm

This paper analytically calculates the expectation and the variance of a soft-information-based best linear unbiased estimator of amplitude and carrier phase offset. Long data frames are considered. The calculation includes the impact on the performance of the presence of training symbols as well as non-Gaussianity of the log-likelihood ratios (LLRs) fed to the estimator input. It is also analyzed how the properties of the estimator are affected when the ratio between the mean and variance of the LLRs is not equal to 1/2

This paper addresses the issue of code-aided hypothesis testing in communication systems, i.e., the estimation of discrete-valued nuisance parameters. A hypothesis testing procedure optimal in the sense of the minimization of the frame-error rate (FER) is derived. Its complexity is shown to be comparable to other recently-proposed code-aided hypothesis procedures. Moreover, when a conditional maximum a posteriori decision rule is used to make the decisions about the transmitted sequence, it is shown that the proposed hypothesis testing procedure combined with sequence detection reduces, in a good approximation, to a joint maximum-likelihood problem. Finally, as an illustrative example, we show the case of phase ambiguity resolution for a convolutionally-coded transmission.

This paper proposes a semi-analytical method for predicting the performance degradation of a turbo-equalization scheme due to signal-to-noise ratio (SNR) estimation errors. In other words, sensitivity of turbo-equalization to an imperfect knowledge of the SNR (or, equivalently, channel noise variance) is analyzed. The considered turbo-equalizer uses the Wang and Poor's soft-in/soft-out (SISO) Minimum Mean Square Error (MMSE) / Interference Cancellation (IC) equalizer and a SISO convolutional decoder. The proposed method is applied to BPSK data modulation and single-user context but may be extended to the multi-user case. This paper shows that the equalizer behavior may be very reliably predicted totally by calculations (no simulations are needed) in the presence of imperfectly known SNR at the receiver. As far as the prediction of the decoder behavior is concerned, it requires simulations for only one independent input parameter. Long frames and perfect channel knowledge at the receiver are assumed in the paper.

A multi-user downlink MIMO-OFDM scheme is considered. Perfect channel knowledge is assumed at the base station and linear processing is used at both the transmit and receive sides. The objective is to optimize the mean BER of the system while satisfying a transmit power constraint and fulfilling each user's rate. FDMA and SDMA are investigated. We show how the multi-user interference induced by SDMA can be annihilated and exhibit that this multiple access technique should be preferred to FDMA.

Recently, we proposed a joint source-channel (JSC) turbo (de)coder combining a variable length code (VLC) and a turbo code, and applied it to image transfer (Jaspar, X. and Vandendorpe, L., SCC Conf., p.279-86, 2004; ICC Conf., p.2606-10, 2004). Simulation results showed that this scheme gave better performance and lower decoding complexity than previous ones. The paper assesses the performance of such a scheme at all signal-to-noise ratios on the channel. Analytical tools are provided for the understanding and optimization of a wide variety of similar schemes currently explored in the literature. More precisely, the bit, symbol and frame distance spectra are developed for VLCs and for VLCs turbo-concatenated with an error correcting code (ECC), in order to get bounds on the corresponding error rates. Also EXIT charts are extended to three dimensions in order to analyze the turbo-convergence of the scheme.

This paper proposes a simple and time non-consuming method to predict, at any iteration, the performance of a turbo equalization scheme using a soft-in/soft-out (SISO) minimum mean square error (MMSE)/interference cancellation (IC) equalizer and a SISO decoder. Gaussianity of the extrinsic log-likelihood ratios (LLRs) output by the equalizer as well as the decoder is assumed. This paper shows that the equalizer behavior may then be very reliably predicted only by calculations (no simulations are needed) whereas that of the decoder requires simulations for only one independent input parameter. Comparison between the proposed prediction method and plain simulations of the overall turbo equalization scheme shows that our method accurately determines the system performance at any iteration.

The goal of this paper is to assess the performance of turbo-equalization (TE), considering at the transmitter bit-interleaved coded modulation (BICM) with a turbo-code as error-correcting code. The bounding techniques that we have recently proposed in Dejonghe et al. (2004) are extended to this particular problem. Simulation results show the relevance of the proposed bounds. By the way, this leads to analytical tools for the understanding and optimization of such turbo-systems.

This paper deals with a multi-user downlink MIMO-OFDM scheme with perfect channel knowledge at both the transmit and receive sides. The objective is to optimize the average BER while fulfilling each user's rate and satisfying a global transmit power constraint. Space Division Multiple Access (SDMA) is investigated and three new iterative schemes are proposed to compute the linear pre/decoders. The results exhibit, inter alia, that orthogonalizing the channels does not lead to the best results. © 2005 IEEE.

We proposed in Jaspar et al. (2004) a joint source-channel (JSC) turbo-(de)coder combining a variable length code (VLC) with a turbo-code. The simulation results showed the better performance and the lower decoding complexity of this new scheme over the previous ones. In this paper, we provide tools for the analysis and the performance prediction of this scheme. The bit, symbol and frame distance spectra are developed for VLC and for the more general case of VLC turbo-concatenated with an error correcting code (ECC). These spectra are then used to get the union bounds on the bit, symbol and frame error probabilities, and to shed some light on previous simulation-based results. These tools are also valid for a wide variety of other similar schemes currently explored in the literature and, hence, can be used to analyze and to compare them.

Noncoherent techniques can be adopted for pseudonoise code synchronization in the presence of random phase. Differentially coherent methods conversely operate with linear phase shifts, such as when a systematic frequency error occurs. This letter presents a method exploiting local phase coherence (inspired by the Pisarenko estimation), allowing global frequency estimation in the presence of random phase noise. Its accuracy is numerically compared with noncoherent and differential techniques for the initial stage of wideband code-division multiple-access code synchronization.

This paper analyzes the multiuser capacity of Gaussian frequency-selective wireline multiaccess channels. Both the uplink (multiple-access channel) and downlink (broadcast channel) capacity regions are considered. The concept of balanced capacity is introduced to characterize the multiuser channel performance. Algorithms for the computation of the balanced multiuser capacity (and the associated power allocations) are proposed for an arbitrary number of users. The optimal power allocation in a K-user memoryless Gaussian channel is analyzed in detail, and an extension to intersymbol interference channels is given with various kinds of power constraints. Results are provided for a wireline access network with 20 users.

The current paper addresses the issue of estimating the user propagation delays, received carrier phase offsets and received amplitudes in an asynchronous DS-CDMA environment with frequency non-selective propagation channels. The proposed synchronizer is based on the expectation-maximization (EM) algorithm and takes benefit from the soft information delivered by the receiver which is of the turbo type. The performance of the proposed synchronizer is illustrated by simulation results. In particular, the mean and the mean squared error of the estimator, as well as the bit error rate reached by the synchronized system, are reported.

Space-time codes designs commonly rely on the assumption of independent and identically distributed Rayleigh channels. However it has been shown that poor scattering conditions can have detrimental effects on the performance of space-time codes. In this communication, we derive a code design criterion leading to robust space-time codes in the presence of a large variety of propagation conditions. No channel knowledge is assumed at the transmitter. Codes satisfying this criterion are shown to perform much better on real-world channels than codes only designed for iid channels. As an example, new Spatial Multiplexing schemes and Linear Dispersion Codes are derived based on this criterion.

Space-time codes designs commonly rely on the assumption of a high SNR. In this communication, we investigate the impact of this assumption when the channel is correlated. Therefore, we discuss the impact of transmit and receive correlations on the performance of space-time codes as a function of the SNR and the diversity achieved by the codes on independent and identically distributed channels. Full diversity codes are shown not to interact with the channel at high SNRs while at realistic SNRs, interactions occur and affect the coding gain. For non-full diversity codes, interactions with the channel occur whatever the SNR. At realistic SNRs, every space-time code interacts with the channel. While it might be reasonable on independent and identically distributed channels, we show that on correlated channels, the 'high SNR' assumption is totally unrealistic and may lead to bad code designs.

This paper provides bounds on the error-floor of turbo-equalization (TE), considering transmission over quasi-static frequency-selective (FS) Rayleigh fading channels, and assuming bit-interleaved coded modulation (BICM) at the transmitter. The expressions of the corresponding asymptotic coding gain and diversity order are also provided. More generally, this leads to a framework enabling to assess the asymptotic performance of similar BICM-based turbo systems.

A new joint source-channel (JSC) turbo-decoding scheme, with three soft-in/soft-out (SISO) modules, is presented for variable length coded sources protected by a turbo-code. This new scheme offers the advantage to combine the powerfulness of the used turbo-code with the robustness of the reversible variable length codes (VLC), and moreover with a decoding complexity close (or less) to the one of the turbo-code alone. The performance due to the turbo-code alone leads to an increased freedom in the VLC design depending on the application -, and suggests to revisit the VLC distance criteria investigated in R. Bauer and J. Hagenauer (March 2001). The decoding algorithm for this three SISO modules scheme is briefly presented in the framework of the Bayesian networks. Compared with previous JSC turbo-decoders and with a classical turbo-code, simulation results show the relevance and the superior performance of the proposed scheme.

The purpose is to assess the performance of bit-interleaved turbo equalization (TE) over static frequency-selective channels. The asymptotic performance is therefore first pointed out, emphasizing the fundamental role played by the constellation mapping. This specific feature is then further analyzed using the extrinsic information-transfer chart technique, leading to an efficient optimization tool. This finally enables showing that bit-interleaved TE can outperform its symbol-interleaved counterpart.

In order to select error-correcting codes for various applications, their performances have to be determined. However, when targeting error-rate computations for block error-correcting codes, many required results are missing in the coding literature. Even in the simple case of binary codes and bounded-distance decoding, classical texts do not provide a bit-error rate (BER) expression taking into account both decoding errors and failures. In the case of nonbinary codes used to protect binary symbols, such as Reed-Solomon codes in many applications, there is no available result making realistic channel assumptions in order to derive BERs. Finally, for the more complex case of complete decoding, only some bounds are available, such as the union one. This paper presents new approximations of error rates for block error-correcting codes as a function of the channel BER (crossover probability). We extend an existing approximation in order to consider not only bounded-distance decoding, but also complete "nearest-neighbor" decoding. We also develop approximations able to deal with nonbinary codes. Combined with state-of-the-art approximations, these new results enable the computation of bit-, symbol-, and word-error rates in various decoding situations. They can consider separately errors related to erroneously decoded words and decoding failures, and they provide accurate estimates of error rates. As they do not require detailed information about the structure of codes, they are general enough to be used in simple comparisons between different codes, avoiding the need for simulations.

This paper considers the uplink of a multiuser direct-sequence code-division multiple-access communication system based on burst transmission over frequency-selective channels. A new precoding method is presented that is able to take benefit from the space diversity introduced at the mobile transmitters and at the common receiver. User-specific spreading codes are designed so that filters matched to the total impulse responses can remove completely the interference and maximize the signal-and-interference-plus-noise ratios. It is analytically proved that an infinite number of solutions is available to orthogonalize the system. Three particular solutions are considered. A progressive solution is firstly proposed to provide orthogonality in a simple way. Then a near-optimum solution is proposed to orthogonalize the system while attempting to reduce the total transmitted power. The minimization of the total transmitted power is a complex problem of nonlinear optimization that can only be solved using an iterative algorithm. The third solution proposed is based on an iterative algorithm. Those three solutions are analyzed in term of their different performance for a varying number of transmit and receive antennas. A comparison is also provided with a system using a conventional set of binary codes and linear or decision-feedback minimum mean-square error joint detection. It is shown that the near-optimum and iterative solutions are the only ones that are able to fully benefit from the space diversity.

The paper addresses the issue of estimating the sampling instant in turbo receivers. The proposed synchronizer is based on the expectation-maximization (EM) algorithm and takes benefit from the soft information delivered by the turbo system. Performance of the proposed synchronizer is illustrated by simulation results. In particular, the mean and the variance of the estimator as well as the bit error rate reached by the synchronized system are reported.

Spatial multiplexing is employed in MIMO communication systems to increase spectral efficiency. The performance of spatial multiplexing is highly dependent on the propagation conditions such as the richness of scattering, the presence of dominant components and the inter-element spacings. In this paper, new robust signal constellations for use in spatial multiplexing over real fading propagation channels are developed. It is shown that these new constellations are by far more robust against fading correlations and high Rice factor than the classical PSK and QAM constellations. With these new constellations, spatial multiplexing presents excellent symbol error rate performance whatever the propagation environment and the inter-element distance.

The channel capacity and the performance of MIMO systems in the presence of fading correlation and antenna coupling are investigated. Simulation results demonstrate that mutual coupling can improve the performance depending on the inter-element spacing and the richness of scattering. It is shown the bit error rate performance of spatial multiplexing is particularly influenced by the decorrelation/correlation effect caused by mutual coupling. On the other hand, the bit error rate performance of transmit diversity is mainly affected by the resulting modification of antenna gain and received power.

The purpose of this paper is to compare bit and symbol interleaving in turbo-equalization (TE) schemes. Considering a single binary encoder and memoryless mapper, the corresponding transmission schemes are respectively bit-interleaved coded modulation (BICM) and trellis-coded modulation (TCM) over a static frequency selective channel. Appropriate turbo processing at the receiver is ensured in both cases. For the sake of tractability, efficient low-complexity MMSE-based implementations are proposed. The asymptotic performance of the resulting bit- and symbol-interleaved TE schemes is then linked with that of the underlying coded modulation schemes. As an extension to [X. Li, J. Ritcey, 1999], this enables to show that bit-interleaved TE with carefully chosen constellation mapping and proper implementation can outperform its symbol-interleaved counterpart.

This paper is devoted to turbo synchronization, that is to say the use of soft information to estimate parameters like carrier phase, frequency offset or timing within a turbo receiver. It is shown how maximum-likelihood estimation of those synchronization parameters can be implemented by means of the iterative expectation-maximization (EM) algorithm [A.P. Dempster, et al., 1977]. Then we show that the EM algorithm iterations can be combined with those of a turbo receiver. This leads to a general theoretical framework for turbo synchronization. The soft decision-directed ad-hoc algorithm proposed in V. Lottici and M. Luise, [2002] for carrier phase recovery turns out to be a particular instance of this implementation. The proposed mathematical framework is illustrated by simulations reported for the particular case of carrier phase estimation combined with iterative demodulation and decoding [S. ten Brink, et al., 1998].

Testing for statistical distribution has received increasing attention in signal processing for communications. Noncoherent receivers, based on correlation magnitude, are employed when the actual carrier phase of the received samples is unknown. This paper presents a new test, based on high-order statistics, to decide whether a real positive white series is a realization of a Rayleigh-distributed random process. Such a "Rayleigh-ness" test is based on a testing variable that measures the "Ricianity" of the series under investigation. That is, it estimates the possible presence of the mean of the complex Gaussian model generating both Rayleigh and Rice distributions. The asymptotic testing statistics have been derived as explicit functions of the higher order moments of the noise-plus-interference distribution. The performance of the Rayleigh-ness test has been analyzed in comparison with a conventional power detector. The devised test has application to noncoherent initial synchronization of the chip offset (code acquisition) in a symbol-length spreading sequence of direct-sequence code-division multiple-access systems. In such a case, the noise-plus-interference variance under the out-of-sync condition is much larger than the effective variance in the in-sync case. The obtained results evidence the robustness of the Rayleighness test, avoiding the severe performance degradation in the presence of large Gaussian and non-Gaussian noise, as well as multiuser interference in a downlink scenario.

This paper proposes a precoding technique for the complete elimination of both multiple-access interference and intersymbol interference in the uplink of a code-division multiple-access system based on burst transmission, with reduction of the minimum mean-square error joint detector to a simple filter matched to the total impulse responses. If the received power is fixed, this system minimizes the variance of the symbol estimation error. An infinity of solutions exists to orthogonalize the system. Two objectives are added: a possible progression in the number of users and a minimization of the average emitted power. In an ideal progressive system, users can enter or leave the system easily without recomputing the codes of the other users. The minimization of the emitted power is a complex optimization problem. An approximate solution is proposed. It is shown that the system introduced in this paper outperforms burst systems using a conventional set of codes.

This paper is devoted to the design and the steady-state performance analysis of a data-aided or decision-directed timing recovery scheme for filter bank-based multicarrier transmission with equalization. The symbol synchronizer is obtained from a Mueller and Muller approach extended to multiband transmission. A simple synchronizer is first proposed which can be derived from an approximate likelihood function. Then, possible improvements are discussed. Timing jitter variances are computed and discussed for high bit-rate transmission over copper wires.

This paper addresses the problem of iterative equalization and decoding (turbo-equalization) when bit-interleaved multilevel modulations are considered. The goal is to propose an efficient low-complexity solution in this context, where optimal turbo-equalization is totally untractable. Therefore, we generalize reduced-complexity soft-in/soft-out (SISO) equalizers based on the minimum mean square error (MMSE) criterion (originally proposed in a BPSK context) to this particular scheme. Performances are illustrated through simulations. We show the influence of the mapping on the signal-to-noise ratio (SNR) threshold and on asymptotic performances, and link the obtained results to iterative demodulation and decoding on an additive white Gaussian noise (AWGN) channel.

We investigate the performance of three multiuser tap weight estimators for multipath channels in data aided (DA) and decision directed (DD) modes for a BPSK DS-CDMA reverse link. The tap weights are estimated using different algorithms working separately or jointly in order to obtain good estimates as required for coherent detection or synchronization purposes. The performance of these algorithms and their sensitivity to the observation window, to the delay estimation error and to the difference between successive delays are investigated. A comparison between Hadamard and Gold codes is also included. The mean squared estimation error (MSEE) is computed and compared to the Cramer-Rao lower bound (CRLB).

This paper studies the impact of timing errors in the receivers for baseband filter bank (FB) modulation techniques, including DMT and multicode modulations. Matched filtering detectors are first investigated, followed by MMSE linear and DF detectors.

We investigate the behavior knowledge space method (see Xu, L. et al., IEEE Transactions SMC, vol.22, no.3, p.418-35, 1992) and decision templates method (see Kuncheva, L. et al., Pattern Recognition, vol.34, p.299-314, 2001) of classifier fusion in the context of face verification. The study involves six experts which are not only correlated, but also their performance levels differ by as much as a factor of three. Through extensive experiments on the XM2VTS database using the Lausanne protocol, we found that the behavior knowledge space fusion strategy achieved consistently better results than the decision templates method. Most importantly, it exhibited quasi monotonic behavior as the number of experts combined increased. This is a very important conclusion, as it means that the performance of the multimodal system is not degraded by adding experts.

Ikonomou (see Ph.D. Dissertation, UCL, Belgium, June 2002) and Ikonomou and Vandendorpe (see European Transactions on Telecommunications (ETT) Journal, vol.10, no.4, p.407-415, July/August 1999) proposed two fractionally spaced (FS) decision feedback equalising (DFE) receivers performing single user detection (SUD) or joint detection (JD) used in non-cyclic prefixed (NCP) multicarrier-CDMA (MC-CDMA) schemes. The objective of this paper is to compare the performance of the above two equalising schemes, against a simpler receiver structure consisting by a single-tap filter bank used in a cyclic prefixed (CP) MC-CDMA scheme. In the context of the latter, two different banks of single-tap filters are presented: one designed to perform classical zero forcing (ZF) detection and one designed for the minimum mean square error (MMSE) criterion. A comparison is finally made in terms of the bit error rate (BER) between NCP MC-CDMA schemes that use equalising receivers and schemes that use the CP extension technique.

In this paper, we investigate the performances of Gaussian modeling and linear prediction tools for error detection and concealment in the transmission of still images. We consider the transmission of subband encoded images through two types of channels. We model the residual correlation between subband coefficients by considering them as jointly Gaussian variables. The first transmission medium considered is a packet-oriented channel, where some packets are lost during transmission. The problem is to estimate the values of missing coefficients. In this case, particular care must be taken while evaluating correlation matrices from incomplete data. The other system considered is based on a discrete memoryless noisy channel affecting the data being transmitted. The challenge is here first to determine the locations of the errors--which is done through hypotheses tests--and then to replace them by estimates based on their neighbors. The reconstruction via linear prediction is shown to give better results than median filtering based reconstruction. Error detection through this Gaussian model also shows promising results, in particular when channel statistics are taken into account in a joint source-channel decoding framework.

We investigate timing recovery structures for a DS-CDMA multiuser uplink using codes with a period of several symbols named long codes and operating over frequency selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference (ISI) and the multiple access interference (MAI) present in the signal. We first propose a multirate description of the long code DS-CDMA uplink. Then based on this formalism we revisit the optimum data-aided (DA) maximum likelihood (ML) delay estimation structure and the suboptimum early-late implementation. The sensitivity of the synchronizers to imperfect knowledge of path gains to the period of the long codes and to near-far situations is also investigated.

This paper considers the uplink and the downlink of a DS-CDMA multiuser communication system based on burst transmission over frequency selective channels. The purpose is to evaluate the performance gain obtained if space diversity is introduced at the base station with an optimized set of codes. The codes are designed in order to minimize the emitted power at the mobile stations (in case of uplink transmission) or at the base station (in case of downlink transmission) while allowing the complete elimination of the intersymbol interference (ISI) and multiple-access interference (MAI) if filters matched to the total impulse responses are used at the receiver. An iterative algorithm is used to generate the codes. The comparison is made with the performances reached when a conventional set of codes is used. It is shown that the precoding scheme based on channel adapted codes significantly outperforms a system based on a conventional set of codes.

We investigate detection structures for a DS-CDMA. multiuser uplink using codes with a period of several symbols, named long codes. We first propose a multirate description of the uplink. Then based on this formalism we revisit a number of popular receiver structures: RAKE receivers, minimum mean square error linear and decision feedback fractionally spaced detectors.

We consider a direct sequence code division multiple access (DS-CDMA) system operating over frequency selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference (ISI) and the multiple access interference (MAI) present in the signal. Starting from the maximum likelihood (ML) approach we derive a decision-directed (DD) early-late synchronizer and its tracking performance is studied. The advantage of the interference mitigating synchronizer is illustrated. The sensitivity of the synchronizer to near-far situations is also investigated.

A new precoding scheme is designed that allows the complete orthogonalization of the users in the uplink of a multiuser CDMA system based on burst transmission. With this channel adapted precoding, a simple filter matched to the total user specific impulse responses is able to eliminate all the inter-symbol and the multiple-access interferences present in the received signal. It is shown that an infinity of codes is available to orthogonalize the system. Two objectives are added: a possible recursion in the number of users and a minimization of the average emitted power. The last optimization problem is a complex one. An approximate solution is proposed. It is shown that the system introduced in this paper outperforms the burst system based on a conventional set of codes.

We investigate detection structures for a DS-CDMA multiuser uplink using codes with a period of several symbols, named long codes. We first propose a multirate description of the uplink. Then based on this formalism we revisit a number of popular receiver structures: RAKE receivers, minimum mean square error linear and decision feedback detectors.

We address the problem of non-data aided frequency offset estimation for non-circular transmissions over frequency-selective channels in a downlink DS-CDMA system or an OFDM communications context. We observe that twice the frequency offset is a cyclic frequency of the received signal. We thus introduce an estimator relying on the maximisation of the empirical cyclocorrelations. We analyse its asymptotic behaviour and obtain a closed-form expression for the asymptotic covariance. This enables us to design relevant system parameters. Simulations are provided and confirm our assertions.

We consider the downlink of a Universal Mobile Telecommunication System terrestrial radio access-wideband code division multiple access (UTRA-WCDMA) system and we investigate the performance of the conventional RAKE receiver. A multipath slowly Rayleigh fading channel is assumed. For the purpose of channel tap weight estimation, a common control physical channel, that is either serial or parallel multiplexed with the dedicated physical channels, is used. The receiver sensitivity to imperfect knowledge of the path delays, to the number of pilot symbols, and to the power ratio of pilot to data channels is also investigated. The system performance is evaluated by means of bit-error rates (BERs) derived using quadratic forms and characteristic functions for a BPSK modulation. The mean-squared estimation error (MSEE) of the channel tap weights is also computed and compared to the classical Cramer-Rao lower bound (CRLB). The mutual interference between pilot and data symbols is taken into account.

We consider a direct-sequence code-division multiple-access system operating over frequency-selective multipath and slowly Rayleigh fading channels. In order to implement RAKE reception, the delays of the different paths have to be estimated and the estimates have to be updated. We extend interference mitigation to this estimation problem and design timing recovery schemes accounting for the intersymbol interference and the multiple-access interference present in the signal. Starting from the maximum likelihood approach, we derive data-aided and decision-directed early-late synchronizers and study their tracking performance. The advantage of the interference mitigating synchronizer is illustrated. The sensitivity of the synchronizer to imperfect knowledge of path gains and to near-far situations is also investigated.

The performance degradation of filter-bank-based multicarrier transmission due to timing errors is investigated. The receiver is made of a fractionally spaced linear or decision-feedback equalizer designed for some sampling phase. The actual sampling phase is different and the impact of the difference on the performance is investigated. Sampling phase offset and jitter are considered. Besides, assuming the sampling phase error can be estimated the efficiency of various types of interpolation is investigated.

This paper deals with the performance evaluation of an asynchronous UTRA-WCDMA uplink using a sequential algorithm for channel estimation and multiuser detection. A multipath slowly Rayleigh fading channel is considered. Both perfect and non-perfect channel estimations are studied with the pilot-to-data amplitude ratio as a parameter, when pilot symbols are transmitted in parallel with data. For channel estimation we use expectation maximization (EM) and spaced alternating generalized expectation maximization (SAGE) algorithms; for symbol detection we use interference cancellation. Bit Error Probabilities (BER) are derived using Monte Carlo simulations for binary phase shift keying (BPSK). The users may have different bit rates. In addition the mean squared estimation error (MSEE) of channel gains is computed and compared to the classical Cramer-Rao lower bound (CRLB).

This paper compares two multiuser transmission techniques in the context of wideband upstream powerline communications. The first one is based on the combination of CAP (carrierless/amplitude phase modulation) and CDMA, the second one is based on DMT (discrete multitone) and relies on a share of the different carriers among the users. The issue of reception under ideal synchronisation assumptions and a simplified noise environment is addressed. Fractional FIR linear and decision feedback joint detectors are derived. A simple resource (code/tone) allocation method is proposed.

This paper deals with the synthesis and the performance analysis of multiuser delay estimators of multipath channels according to the maximum likelihood (ML) criterion in data aided (DA) mode for a BPSK DS-CDMA uplink. We suppose the channel tap weights are known perfectly, and we are interested in the estimation of the path delays. We perform open-loop (S-curve) and closed loop mean squared estimated error (MSEE) analysis in tracking mode and we compare the results to the classical Cramer-Rao lower bound (CRLB).

This paper examines a decision-directed timing recovery scheme for filter-bank-based multicarrier transmission. The symbol synchronizer is obtained from a maximum-likelihood approach and uses the digital equalization filters. The algorithm is first derived, the performances of the scheme (timing offset and timing jitter) are then computed, and computational results are provided for high bit-rate transmission over copper wires. Finally, different improvements are discussed.

In this paper we propose an original study of the reconstruction of subband compressed images impaired by channel transmission errors. The method proceeds in two steps:first a detection scheme is applied to determine which coefficients of the subband decomposition have been affected by transmission, and then an estimation step tries to evaluate the erroneous coefficients. In our model, subband coefficients are considered to be drawn from jointly Gaussian random processes. Based on this assumption, conditional statistics can be computed which enable to test the likelihood of a given set of received coefficients with respect to the rest of the image. The detection and estimation processes are derived from these statistics. The method is validated through simulation and visual results are provided. The drawbacks of the method are outlined and explained through the discrepancies between the Gaussian assumption and real world images, namely around image edges.

This paper is devoted to a decision-directed timing recovery scheme for filter bank based multicarrier transmission. The symbol synchronizer is obtained from a maximum-likelihood approach and uses the equalizer outputs. The algorithm is first derived and computational results for the resulting timing error are provided for high bit rate transmission over copper wires. Finally, different improvements are discussed.

In this paper, we extend structures and factorizations for paraunitary filter banks yielding linear phase filters to the oversampled case. We derive minimal factorizations for a subset of these banks, and propose some design examples.

We investigate the asymptotic performance of a multi-input multi-output decision-feedback (DF) equalizer used to detect a multicarrier (MC) signal based on a filter-bank and transmitted over a linear dispersive channel. We derive the optimum DF structure for a minimum-mean square-error criterion. We basically show that with infinite length forward and feedback filters and at high signal-to-noise ratio, the geometrical mean of prediction errors does not depend on the paraunitary filter-bank used in the transmitter. Hence, it appears that uncoded filter-bank based MC transmission and single carrier transmission, both used over the same channel and with optimum DF, lead to the same achievable bit rate.

In this paper, we investigate the statistical properties of interlaced and progressive image sequences in order to determine what is the most efficient format from a coding point of view. Intra- and inter-coding modes are both considered. The main result is that, for both intra- and inter-images, the coding of progressive images outperforms the coding of interlaced ones for low bit rates and large motion vectors. Particular attention is paid to inter-coding with subpel accuracy, where the effects of nonideal interpolation filters and finite precision of the motion vector are taken into account.

We investigate detectors for transmultiplexer-based high bit rate transmission over dispersive channels like telephone wires. The transmitter is based on a synthesis stage. At the receiver side, we design, for an MMSE criterion, multiple-input/multiple-output (MIMO) linear detectors applied after an analysis stage and upgraded with a MIMO decision-feedback (DF) section. The performance of the system is investigated for filter banks over copper wires with different noises (AWGN, FEXT and RFI). The influence of the forward section rate is investigated. The potential of these detectors is clearly demonstrated. Besides, reduced complexity solutions are also put forward.

We investigate the asymptotic performance of a multiple input/multiple output (MIMO) decision-feedback equalizer (DFE) used to detect a multicarrier signal transmitted without guard time over a linear dispersive channel. We design the MIMO DFE for a minimum mean square error criterion (MMSE) and compare its performance to that of a single carrier system also using an infinite length MMSE DFE equalizer. We demonstrate that both uncoded systems achieve the same capacity.

In the present letter, we investigate the asymptotic performance of causal multiple-input/multiple-output (MIMO) linear prediction of subband signals obtained by means of an orthogonal filterbank. The prediction filters are designed for a minimum mean squared error criterion. It is demonstrated that the geometrical mean of the prediction errors in the subbands is asymptotically equal to the prediction error in the fullband, which is in turn related to the spectral flatness measure of the input process. As a consequence, the maximum performance of a hybrid subband coding system with MIMO prediction is independent of the filter bank used for the subband decomposition.

This correspondence addresses the problem of human visual weighted quantization for transform/subband coding of interlaced pictures. Merged field coding is assumed. The criterion proposed for the optimization of the quantizer is the distortion measured on the deinterlaced and decoded image. This criterion and the associated weighting factors are shown to be dependent on the motion between two successive fields.

In this paper we investigate the design of finite length linear and decision-feedback symbol-spaced equalizers for transmultiplexers, or multiband transmission schemes based on filter banks. The channel is assumed to be linear and noisy. MMSE finite length detectors are derived. The solution corresponding to infinite length detectors is also investigated.

We consider a fractionally spaced decision feedback joint detector (FS-DFJD) for multitone code division multiple access (CDMA) systems. We first derive the structure of the receiver for an minimum mean-squared error (MMSE) criterion. Then we investigate the bit-error rate (BER) performance achieved by this detector for binary phase-shift keying (BPSK) modulation in steady-state conditions. We consider an asynchronous scenario where the signal of each user propagates over a two-path channel. The resistance of the detector against timing errors is studied, and the resistance against a near-far scenario is also demonstrated.

This paper presents a theoretical analysis of the coding efficiency of interlaced and progressive formats for intra and prediction error images. It shows that progressive coding is more effective for lower bitrates and larger motion vectors than interlaced coding.

The combination of multitone modulation with direct sequence spectrum spreading (DS/SS) has been introduced in the past. The performance of a correlation receiver has been evaluated for a multipath channel and in the presence of an additional multiple access interference. We analyze the problem of decision feedback equalization (DFE) for such a system. In order to understand the potential of the system with equalization, we first study the steady-state behavior of the equalizer for a minimum mean square error (MMSE) criterion. The investigation is carried out for a receiver made of a bank of filters matched to both the symbol shape and the channel, and for a two path channel. Assuming transmission of binary phase shift keying (BPSK) symbols, an exact expression of the bit error probability is obtained in the form of an integral. Then adaptive least mean square (LMS) and recursive least square (RLS) structures are derived. The performance of the adaptive RLS algorithm is demonstrated by means of computer simulations.

The generalized sampling theorem states that any analogue signal whose spectrum is limited to 1/T can be exactly recovered from N sequences of samples taken at a rate 2/NT and all having a different sampling phase. When N=2, the exact interpolation formula can be derived quite easily. The ideal interpolation filters have infinite impulse responses. This paper addresses the theoretical question of recovering from the 2 initial sequences, any other sequence taken at the some rate 1/T and with a different sampling phase. FIR filters are derived for a least square interpolation error. Moreover, an adaptive implementation is proposed and formulated as a Kalman algorithm. Simulation results obtained for AR processes show the effectiveness of the solution compared to static solutions.

Delogne et al. (see IEEE Transactions on Image Processing, vol.3, no.5, p.482-91, 1994) have shown how the motion estimation and compensation have to be carried out when interlaced images are processed under the assumption of a translational motion. Due to the finite accuracy of the motion vectors, the prediction error is nonzero after motion compensation. We therefore investigate the influence of quantizing the motion vectors on the statistical properties of the prediction error signal. The power spectral density and the variance of the prediction error are also computed.

Several television standards exist for TV and for HDTV signals. The worldwide interchange of programs makes the conversion between them of critical importance. Conventional transcoders use a static interpolation filter which is not able to deal with incorrectly bandlimited television signals. Motion compensation has been introduced in order to adapt interpolation to the signal. This approach proposes movement-oriented filtering and has been shown to give significant improvement. However, the known algorithms do not offer a perfect reconstruction step when the desired pixels have to be interpolated. A new system is proposed for the conversion between the popular interlaced TV standards (625 lines, 50 fields/s or 525 lines, 60 fields/s). The key feature is the use of generalized interpolators that are based on nonuniform sampling theory. The performance is compared with alternative interpolation techniques. In addition, the attached motion estimation algorithm relies on segmentation in the target field (i.e. the unknown 60 Hz field) to avoid assignment problems.

In this paper, multi-h continuous-phase modulation (CPM) is combined with a direct-sequence spread spectrum system and the performance is assessed in a multipath channel in the presence of multi-user interference. An analytical model for the evaluation of spread spectrum multi-h (SSMH) in a Rayleigh indoor channel with multi-user interference is presented. This study is performed considering a coherent receiver structure which is optimum for AWGN. Also the use of diversity techniques is inspected in order to obtain improved performance in the receiver. Three different types of diversity are considered: selection diversity, equal gain combining and maximal ratio combining.

We analyze the problem of joint equalization and cancellation of the multipath and multiple access interference for multitone CDMA introduced by Vandendorpe (see IEEE Transactions on Vehicular Technology, vol.44, no. 2, p.327, 1995). A linear structure is investigated for an MMSE criterion. In order to understand the potential of the system we first study the steady-state behaviour of the joint equalizer-canceller. The investigation is carried out for a joint device following a receiver made of a bank of matched filters and assuming perfect carrier phase and timing recovery. The scenario is asynchronous. An exact expression in the form of an integral is obtained for the bit error probability of the BPSK symbols before and after cancellation, by means of the characteristic function method. The performance of different systems is obtained for a constrained comparison and the near-far resistance of the detector is demonstrated.

The generalized sampling theorem states that any analogue signal whose spectrum is limited to 1/T can be exactly recovered from N sequences of samples taken at a rate 2/NT and all having a different sampling phase. When N=2, the exact interpolation formula can be derived quite easily. The ideal interpolation filters have infinite impulse responses. This paper addresses the question of recovering from the 2 initial sequences, any other sequence taken at the same rate 1/T and with a different sampling phase. The design problem is dealt with for finite length filters and the criterion is the minimization of the mean squared interpolation error.>

The paper addresses the problem of human visual weighted quantization for transform/subband coding of interlaced pictures. This problem has been correctly solved for progressively scanned pictures [Vandendorpe 1991]. When interlaced pictures are coded, the problem can be solved easily for field coding. However, if the coding of merged fields (known as frame coding) is preferred, the quantizer optimization becomes more difficult. In the paper, the authors show how to solve the problem for merged field coding by using the motion information which exists between 2 successive fields. The weighting factors required to determine the quantization step sizes of the subbands are shown to be dependent on this motion information. In addition, the variances of the subbands produced after held merging are also dependent on the motion. Their exact expression is derived.>

This paper investigates a coding method for interlaced image sequences which uses deinterlaced images as an intermediate format. The purpose of this method is threefold: firstly, to achieve a higher coding gain, as the processing of progressive pictures raises much less difficulty than the processing of interlaced ones; secondly, to provide an intermediate step toward the development of a fully progressive production and transmission chain; and finally to open the way to efficient solutions for important image processing issues such as frame rate conversion and compatibility. In previous work by the authors (1994), an interlace-to-progressive converter was proposed. It was based on theoretically correct generalized interpolation formulas, working under the assumption of a uniform translational motion. The scheme proposed here makes use of this converter to produce the progressive images from the interlaced source, which are coded and then re-interlaced. Another solution is considered, with the purpose of improving the coding efficiency alone. It is based on an intermediate progressive format at half the original temporal sampling rate. However, in that case, some additional information needs to be transmitted in order to accurately recover the full rate interlaced signal. The two methods mentioned above are described in some detail and tested on actual sequences. The picture quality is assessed, both objectively and subjectively, and conclusions are drawn.>

Multi-h continuous-phase modulation (CPM) is combined with a direct-sequence spread spectrum system and its performance is assessed in several indoor environments (line-of-sight (LOS), non-LOS and factories). The study is performed for two different multi-h codes considering a coherent receiver structure which is optimum for AWGN. Improvements in the performance are obtained with the use of diversity in the receiver. Two different types of diversity are considered, selection diversity and a post-detection diversity scheme implemented by means of two Viterbi receivers. Results show that CDMA multi-h CPM can achieve a good performance when used in indoor environments for relatively high bit rates but specially for factories the use of diversity techniques, further coding or interleaving is needed to achieve a given BER for realistic values of E/sub b//N/sub 0/.

The combination of multitone transmission (also known as orthogonal frequency division multiplexing (OFDM)) with direct sequence spread spectrum (DS/SS) is suitable for the design of a multiuser system robust against channel impairments. For high bit rate applications in indoor channels, the need for equalization is high, because guard intervals would lead to poor spectral efficiency. This paper presents a comparison between a recursive least square (RLS) scheme and a least mean square (LMS) algorithm, both extended for the linear equalization of OFDM/DS systems.

The increasing number of users of mobile communication systems and the corresponding need for increased capacity show the importance of using a modulation scheme both power and spectrally efficient. In this paper, multi-h continuous-phase modulation (CPM) is combined with a direct-sequence spread spectrum system and its performance is assessed in several indoor environments (line-of-sight (LOS), non-LOS and factories). This study is performed for two different multi-h codes considering a coherent receiver structure which is optimum for AWGN. Results show that multi-h CPM can achieve a good performance when used in indoor environments for relatively high bit rates but specially for factories the use of diversity techniques, further coding or interleaving will be needed to achieve a given BER for realistic values of E/sub b//N/sub o/.>

This paper investigates the performance of a hybrid system based on the combination of slow frequency hopping (SFH) with multitone direct sequence (DS) spreading as originally proposed by Vandendorpe (see International Zurich Seminar on Digital Communications, 1994). The coherent receiver structure considered in the paper is optimum for AWGN only but its performance is analyzed for a multipath slowly Rician fading channel, in the presence of it multiple access interference. Selection diversity and Rake reception are considered.>

This paper introduces a new method for the interpolation that has to be performed when motion estimation and compensation are applied to interlaced sequences with subpel accuracy. It is based on the assumption that a uniform motion exists between two successive frames. The exact formulas for the estimation are derived. They show that in order to obtain a correct interpolation of each field of one frame, it is necessary to use the information of both fields of this frame. Because the ideal filters have infinite impulse responses, the filter design is discussed, and the efficiency is measured for typical sequences.

This paper deals with the question of optimizing the filters in the upsampling stage of a TV/HDTV compatible pyramidal coder. From a coding gain point of view, both the decimation and upsampling filters should be optimized. In the frame of compatible coding, not only the coding efficiency influences the choice of the decimation filter but also the compatible image quality. Therefore, assuming this filter has been fixed, we analyze the question of optimizing the upsampling filter in order to obtain the highest coding gain. This question is addressed for a mean squared error (MSE) criterion. In addition, assuming the base layer (TV) signal can be quantized, the influence on the quantization noise on the optimal interpolation filter is investigated and the problem is handled for the MSE criterion. As the statistical properties of pictures are required in the optimization, a model is then developed to compute these properties when there is motion. The model takes into account the processing of progressive sources and, concerning interlaced sequences, the independent processing of fields or the processing of merged fields. Results are then derived for the three types of processing.

This paper deals with the problem of motion estimation and compensation with sub-pixel accuracy when interlaced moving sequences are processed. Provided a translational motion exists between consecutive frames (or that the image can be partitioned into sets of points with such a motion) the exact formulas for the prediction of pixels are derived. It is shown that in order to obtain a correct prediction of any pixel in one frame, it is required to use the information of both fields of the previous frame. The ideal interpolation filters are of infinite length. Therefore, the question of designing finite length filters is addressed and alternative design methods are proposed. The efficiency of the method is then measured on typical sequences.

A compatible coding scheme for interlaced HDTV (high-definition television) is proposed. This scheme provides a standard definition signal and a second channel containing the additional information required to reach the HD resolution. The global scheme is of the pyramidal type: the standard TV is obtained by downsampling the HDTV signal by means of a field-based operation. The standard TV signal is coded, decoded, and upsampled. It is used as a prediction of the HD signal and the prediction error is coded in a second channel. In both branches, motion-compensated hybrid DCT coding is used. In addition, the DCT is taken within the frame.>

Subband Coding of images, which can be seen as an extension of orthogonal transformations, has been introduced by Woods and O’Neil [8]. In [8], the subbands are further encoded by DPCM. In this study, it is proposed to use subband coding as a stand alone coding technique. The emphasis is put on the question of subband quantization. A methology is proposed where the quantization step of the subbands is taken so as to minimize a quantization noise power weighted by a sensitivity function of the eye.