In this paper, we propose a new data-aided (DA) joint angle and delay (JADE) maximum likelihood (ML) estimator. The latter consists of a substantially modified and, hence, significantly improved grey wolves optimization (GWO) technique by fully integrating and embedding within it the powerful importance sampling (IS) concept. This new approach, referred to hereafter as GWOEIS (for "GWO embedding IS"), guarantess global optimality and offers higher resolution capabilities over multi-carrier and multi-path single-input multiple-output (SIMO) channels. Traditional GWO initializes randomly the wolfs' positions (angles and delays) and, hence, requires larger packs and longer hunting (iterations) to catch the preys, i.e., find the correct AoAs (angles of arrival) and TDs (time delays), thereby affecting its search efficiency. Whereas GWOEIS ensures faster convergence by providing initial estimates based on a simplified IS function. More importantly, and beyond simple initialization of GWO with IS (coined as IS-GWO hereafter), we modify and dynamically update the conventional simple expression for the convergence factor of the GWO algorithm that entirely drives its hunting and tracking mechanisms by accounting for new cumulative distribution functions (CDFs) derived from the IS technique. Simulations unequivocally confirm these significant benefits in terms of increased accuracy and speed. Moreover, GWOEIS reaches the Cramér-Rao lower bound (CRLB) even at low SNR levels.

We propose a comprehensive evaluation of ETSI/DECT-2020 New Radio (NR) as an IMT-2020 candidate technology for the mMTC (connection density) and URLLC (reliability) use cases. Several independent evaluation groups assessed DECT-2020 NR performance against the IMT-2020 requirements and INRS played a key role within the Canadian Evaluation Group (CEG) in evaluating the technology via simulation. In order to develop 5G link- and system-level simulators, it is necessary to identify and understand all key characteristics of DECT technology. Nevertheless, the mMTC use case offers D2D communications, which made simulation analysis extremely cumbersome. In this paper, we also explain the different maneuvers in order to fasten the simulations and reduce complexity while respecting all DECT specifications. Simulation results provided from link- and system-level simulations for both URLLC and mMTC use cases show that DECT-2020 component RIT meets the IMT-2020 requirements.

propose a new distributed collaborative beam-forming (DCB) solution that is robust (i.e., RDCB) against major channel estimation impairments over dual-hop transmissions through a wireless sensor network (WSN) of K nodes with a nominally deterministic geometry, presumably rectangular (or a fortiori square). The source S first sends its signal to the WSN. Then, each node forwards its received signal to the destination D after multiplying it by a properly selected beamforming weight. The latter aims to minimize the received noise power while maintaining the desired one equal to unity at the destination D. These weights depend on some channel state information (CSI) parameters. Hence, they have to be estimated locally at each node or fed back to it; resulting in either case in channel parameter estimation or feedback errors that could severely hinder DCB performance. Due to lack of space, we only account here for nodes location placement errors which would always amount to some additional phase error. Accounting for the massive connectivity characterizing new 5G and future 5G+/6G wireless technologies and the Internet of things (IoT), we develop alternative RDCB solutions that properly adapt both to monochromatic [i.e., line-of-sight (LoS)] and bichromatic (i.e., slightly to moderately scattered) propagation scenarios over the first hop while always assuming a LoS link over the second; referred to hereafter as MM-RDCB and BM-RDCB, respectively. We do so by exploiting i) very efficient asymptotic approximations at large numbers K of the WSN nodes and ii) the nominal geometric symmetries of their deterministic (rectangular or square) grid shapes. Furthermore, our new MM-RDCB and BM-RDCB solutions are distributed since their weights can be locally computed at every terminal, thereby dramatically improving both spectral and power efficiencies of the WSN. Simulation results show considerable gains and robustness of the proposed techniques in terms of achieved signal-to-noise ratio (SNR) against nodes location placement errors.

In this paper, we tackle the problem of joint angles and time delays estimation (JADE) in a non-data aided (NDA) scenario where no pilot symbols are available at the receiver. A differential evolution (DE) technique is proposed in the context of maximum likelihood (ML) estimation is proposed to solve the resulting multi-dimensional optimization problem. DE is a metaheuristic global optimization algorithm-based on population, that finds the optimum iteratively by trying to improve a candidate solution based on an evolutionary process. We introduce the improved DE using a pseudo-pdf for easier generation of individuals. Simulations results show that the proposed solution is significantly more efficient in terms of global convergence than the classic differential evolution algorithm (CDEA) as well in terms of RMSE. Moreover, due to a very useful approximation, we are able to reduce even further the computational complexity of the proposed technique without any significant performance loss. Computer simulations also show the distinct advantage of the new NDA-DE approach over the existing techniques. Most remarkably, it also approaches the Cramér-Rao lower bound (CRLB) at medium and high SNR levels.

In this paper, we develop an innovative approach to quantitatively characterize the performance of ultra-dense wireless networks in a plethora of propagation environments. The proposed framework has the potential of simplifying the cumbersome procedure of analyzing the coverage probability and allowing the unification of single- and multi-antenna networks through compact analytical representations. By harnessing this key feature, we develop a novel statistical machinery to study the scaling laws of wireless networks densification considering general channel power distributions including small-scale fading and shadowing as well as associated beamforming and array gains due to the use of multiple antenna. We further formulate the relationship between network density, antenna height, antenna array seize and carrier frequency showing how the coverage probability can be maintained with ultra-densification. From a system design perspective, we show that, if multiple antenna base stations are deployed at higher frequencies, monotonically increasing the coverage probability by means of ultra-densification is possible, and this without lowering the antenna height. Simulation results substantiate performance trends leveraging network densification and antenna deployment and configuration against path loss models and signal-to-noise plus interference thresholds.

In this paper, we consider multi-aperture multiuser dual-hop amplify-and-forward (AF) free-space optical/radio frequency (FSO/RF) communication systems. The FSO-RF channels are assumed to follow Málaga- M/shadowed κ-μ fading models with pointing errors on the FSO links. Under the assumption of transmit aperture selection at the source and opportunistic user scheduling at the destination, we derive exact closed-form expressions for the outage probability and average symbol error probability (SEP). Additionally, the system performance is studied at the high signal-to-noise ratio (SNR) regime where an approximate expression for the system outage probability is derived, in addition to deriving the system diversity order and coding gain.

In this paper, we propose a novel joint estimation scheme for the range, path-loss exponent (PLE), and inter-node distances based on the received signal strength (RSS) and the network's information of an anchor-less (i.e., without anchor nodes) curvilinear wireless sensor network (CLWSN). Assuming a random node distribution along a one-dimensional curve (e.g., in deployments over gas/oil/water pipelines, railway tracks, underground mine tunnels, subway networks, city sewage networks, street/road lights, etc.), and adopting a propagation model that combines both large-scale PLE and log-Normal shadowing, we derive new analytical expressions for the node's communication range as a function of the network's connectivity and density and for the PLE as a function of the node's range and both the network's connectivity and density. Once we calculate the node's range and the PLE, we estimate all distances between nodes using an RSS-based method. We illustrate by simulations the superior accuracy of our new joint range, PLE, and distance estimation technique against state-of-the-art benchmarks in terms of the normalized mean absolute error (NMAE). We thereby highlight the major contributions of this work by demonstrating both: i) the ability of our new solution to jointly estimate the node's range, the PLE, and all inter-node distances with relatively high accuracy using solely the RSS and network's connectivity and density; and ii) its significant potential for enabling very cost-effective yet highly accurate positioning over anchor-less (e.g., in GPS-denied harsh environments) wireless sensor networks (WSN)s.

This paper embodies the Fox's H-transform theory into a unifying modeling and analysis of HetNets. The proposed framework has the potential, due to the Fox's N-functions versatility, of significantly simplifying the cumbersome analysis and representation of cellular coverage, while subsuming those previously derived for all known simple and composite fading models. The paper reveals important insights into the practice of densification in conjunction with signal-to-noise plus interference (SINR) thresholds and path-loss models.

In this paper, amplify-and-forward beamforming (AFB) is considered to establish a communication, through wireless sensor networks (WSNs) of K sensor nodes, from a source to a receiver in the presence of both scattering and interference. All sources send their data to the WSN during the first time slot, while the nodes forward a properly weighted version of their received signals during the second slot. These weights are properly selected to maximize the desired power while completely canceling the interference signals. We show, however, that they depend on information locally unavailable at each node, making the zero-forcing beamformer (ZFB) unsuitable for WSNs, due to the prohibitive data exchange overhead and the power depletion it would require. To address this issue, we exploit the asymptotic expression at large K of the ZFB weights that is locally computable at every node and, further, well-approximates their original counterparts. The performance of the resulting new distributed ZFB (DZFB) version is analyzed and compared with the conventional ZFB and two other distributed AFB benchmarks: the monochromatic (i.e., single-ray) AFB whose design neglects the presence of scattering and the bichromatic AFB which relies on an efficient two-ray channel approximation valid only for low angular spread (AS). We show that the proposed DZFB outperforms its monochromatic and bichromate counterparts while incurring much less overhead and power depletion than ZFB. We show also that it is able to provide optimal performance even in highly scattered environments as in the latter.

In this paper, we consider a hybrid terrestrial and underwater RF wireless cooperative communication system. We improve the energy awareness of the system by employing simultaneous wireless information and power transfer (SWIPT) technique. The impact of the system performance parameters, such as signal-noise-to-ratio, bit error rate, outage probability and throughput are extensively investigated. All theoretical results are validated by numerical results. Furthermore, the impact of the time allocation in time-switching protocol is investigated. Simulation results, which are based on theoretical analysis and underwater experimental data, verifies that SWIPT integrated proposed system improve the overall energy awareness while maintaining the system performance.

This paper investigates the problem of fast time-varying multipath channel estimation over single-input multiple-output orthogonal frequency-division multiplexing (SIMO OFDM)-type transmissions. We do so by tracking the variations of each complex gain coefficient using a polynomial-in-time expansion. To that end, we derive the log-likelihood function (LLF) in both the data-aided (DA) and non-data-aided (NDA) case. The DA ML estimates are found in closed-form expressions and then used to initialize the expectation maximization (EM) algorithm that is used to iteratively maximize the LLF in the NDA case. We also introduce an alternative initialization procedure that requires less pilot symbols as compared to the DA ML-based solution without incurring a significant performance loss. Simulation results show that the proposed EM-based estimator converges within few iterations providing accurate estimates for all multipath gains, thereby resulting in significant BER gain as compared to the DA least square (LS) technique.

In this paper, we investigate the problem of fast time-varying multipath channel estimation over orthogonal frequency-division multiplexing (OFDM)-type transmissions. We do so by tracking each complex gain variation using a polynomial-in-time expansion. To that end, we derive the log-likelihood function (LLF) in the non-data-aided (NDA) case. Since the LLF is extremely nonlinear, we opt for the expectation maximization (EM) concept to find its global maximum. Simulation results show that the new estimator is able to converge to the global maximum within few iterations only and to provide accurate estimates for all multipath gains, thereby resulting in significant BER and link-level throughput gains.

In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization in multi-node decode-and-forward (DF) cooperative relaying systems operating over time-varying channels (TVCs). This new synchronization scheme is embedded into a distributed multiple input multiple output (MIMO)-relay beamforming transceiver structure to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. The new technique can be jointly implemented with any Doppler spread estimator in an iterative scheme using a time-constant channel (TCC) based synchronization method at the initialization step. The resulting TD and CFO estimates along with the channel estimates are then fed into a distributed MIMO-relay beamforming transceiver of K single-antenna nodes, for pre-compensation at each node of the transmitted signals, to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming TCCs. The latter translates into noticeable gains in terms of useful link-level throughput, more so at higher Doppler or with more relaying nodes.

In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization in multi-node decode-and-forward cooperative relaying systems operating over time-varying channels. This new synchronization scheme is embedded into a distributed multiple input multiple output (MIMO)-relay beamforming transceiver structure to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. By accounting for a perfect Doppler spread value, the new synchronization solution delivers accurate TD and CFO estimates. For real-world operation, however, this new technique can be jointly implemented with any Doppler spread estimator in a new iterative scheme using a time-constant channel (TCC)-based synchronization method at the initialization step. The resulting TD and CFO estimates along with the channel estimates are then fed into a distributed MIMO-relay beamforming transceiver of K single-antenna nodes, for pre-compensation at each node of the transmitted signals, to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming TCCs. The latter translates into noticeable gains in terms of useful link-level throughput, more so at higher Doppler or with more relaying nodes.

This paper develops an innovative approach to the modeling and analysis of downlink cellular networks with device-to-device (D2D) transmissions. The analytical embodiment of the signal-to-noise and-interference ratio analysis in general fading channels is unified due to the H-transform theory, a taxonomy never considered before in stochastic geometry-based cellular network modeling and analysis. The proposed framework has the potential, due to versatility of the Fox's H functions, of significantly simplifying the cumbersome analysis procedure and representation of D2D and cellular coverage, while subsuming those previously derived for all the known simple and composite fading models. By harnessing its tractability, the developed statistical machinery is employed to launch an investigation into the optimal design of coexisting D2D and cellular communications. We propose novel coverage-aware power control combined with opportunistic access control to maximize the area spectral efficiency (ASE) of D2D communications. Simulation results substantiate performance gains achieved by the proposed optimization framework in terms of cellular communication coverage probability, average D2D transmit power, and the ASE of D2D communications under different fading models and link- and network-level dynamics.

We investigate the performance of mixed free-space optical (FSO)/millimeter-wave (mmWave) relay networks with interference at the destination. The FSO/mmWave channels are assumed to follow Málaga-M/generalized-K fading models with pointing errors in the FSO link. The H-transform theory, wherein integral transforms involve Fox's H-functions as kernels, is embodied to unifying the performance analysis framework that encompasses closed-form expressions for the outage probability, the average bit error rate (BER), and the average capacity. By virtue of some H-transform asymptotic expansions, the high signal-to-interference-plus-noise ratio (SINR) analysis reduces to easy-to-compute expressions for the outage probability and BER, which reveals inside information for the system design. We finally investigate the optimal power allocation strategy that minimizes the outage probability.

User-centric wireless access virtualization (WAV) allows each user to be served by a set of carefully selected transmission points (TPs) forming a user-specific virtual base station (uVBS) adapted to its environment and quality-of-service (QoS) requirement. In this way, this new concept breaks away from the conventional cell-centric architecture to provide boundaryless communications in future fifth-generation (5G) networks. This fundamental structural 5G evolution and the ultra-dense multi-tier heterogeneous context foreseen in such networks require an inevitable rethinking of efficient scalable TP clustering. As such, this paper proposes three innovative low-cost clustering approaches that enable the user-centric WAV and provide dynamic, adaptive, and overlapping TP clusters while requiring not only negligible overhead cost but also minimum signaling changes at both network and user sides. Contrary to existing clustering techniques, the new ones we propose better leverage the 5G features such as extreme densification and massive connectivity as well as new concepts such as millimeter wave (mmWave) spectrum and massive multiple-input-multiple-output (MIMO). The simulations show that they may achieve until 154% and 282% of throughput and coverage gains, respectively. Furthermore, these approaches are flexible enough to be adapted to different network dimensions (i.e., space and time), thereby paving the way for achieving the dramatic performance improvements required by the 5G networks to cope with the upcoming mobile data deluge.

In this paper, we tackle the problem of joint angle and delays estimation (JADE) of multiple reflections of a known signal impinging on multiple receiving antennae. Based on the importance sampling (IS) concept, we propose a new non-iterative maximum likelihood (ML) estimator that enjoys guaranteed global optimality and enhanced high-resolution capabilities for both single- and multi-carrier models. The new ML approach succeeds in transforming the original multi-dimensional optimization problem into multiple two-dimensional ones thereby resulting in huge computational savings. Moreover, it does not suffer from the off-grid problems that are inherent to most existing JADE techniques. By exploiting the sparsity feature of a carefully designed pseudo-pdf that is intrinsic to the new estimator, we also propose a novel approach that enables the accurate detection of the unknown number of paths over a wide range of practical signal-to-noise ratios (SNRs). Computer simulations show the distinct advantage of the new ML estimator over state-of-the art JADE techniques both in the single- and multi-carrier scenarios. Most remarkably, they suggest that the proposed IS-based ML JADE is statistically efficient as it almost reaches the Camér-Rao lower bound (CRLB) even in the adverse conditions of low SNR levels. Using real-world channel measurements collected from four access points (APs) with IEEE 802.11ac standard's setup parameters in an indoor environment, we also show that the proposed ML estimator achieves a localization performance below 15 cm accuracy.

In this paper, we investigate maximum likelihood (ML) time delay (TD) and carrier frequency offset (CFO) synchronization (i.e., estimation and pre- compensation) in decode-and-forward (DF) cooperative systems operating over time-varying channels (TVCs). The new technique is embedded at each relay node in order to avoid the drawbacks of multidimensional ML estimation at the destination and to minimize the overhead cost. By accounting for a perfect Doppler spread value, the new synchronization solution delivers accurate TD and CFO estimates at each relay. The resulting TD and CFO estimates along with the channel estimates are then exploited by the MIMO relay for precompensation at each node of the distributed transmit beamforming signals to ensure constructive maximum ratio combining (MRC) at the destination. Simulation results show significant synchronization accuracy improvement over previous distributed multi-node synchronization techniques assuming time-constant channels (TCCs). The latter translates into noticeable gains in terms of useful (i.e., after accounting for incurred overhead) link-level throughput, more so at higher Doppler.

We propose a new collaborative beamforming (CB) solution robust against major implementation impairments over dual-hop transmissions from a source to a destination communicating through a wireless sensor network (WSN) of K nodes. In the first time slot, the source sends its signal to the WSN while, in the second, each node forwards its received signal after multiplying it by a properly selected beamforming weight. The latter aims to minimize the received noise power while maintaining the desired power equal to unity. These weights depend a priori on some channel state information (CSI) parameters. Hence, the latter have to be estimated locally at each node thereby resulting in implementation errors that could severely hinder CB performance. Exploiting an efficient asymptotic approximation at large K, we develop alternative CB solutions that not only account for estimation errors, but also adapt to different implementation scenarios and wireless propagation environments ranging from monochromatic (i.e., scattering-free) to polychromatic (i.e., P-DCB) ones. Besides, in contrast to existing techniques, our new CB solutions are distributed (i.e., DCB) in that they do not require any information exchange among nodes, thereby dramatically improving both WSN spectral and power efficiencies. Simulation results confirm that the proposed DCB techniques are much more robust against implementations errors than their benchmarks at much lower complexity.

This paper develops an innovative scalable and low-cost QoS-based user equipment (UE) virtualization (UEV) scheme that capitalizes on the massive connectivity and the enhanced resources of the new UE generation in terms of connectivity, computing, battery/power, etc. Exploiting the need/excess duality and the heterogeneity in such resources at the UE plan, we form virtual UEs (VUE)s, dynamically, owing to a carefully-designed time-adjusting scheme for the selection of the proper cooperative UE sets. The new UEV scheme is able to adapt to each target UE (TUE) environment, meet its demands, and scale with its needs, offers a reliable and efficient yet low-cost inter-UE cooperation, reduces the overhead and power consumption with respect to conventional approaches, and substantially reduces the number of communication links and, hence, incurs much less interference. System-level simulation results show that the proposed QoS-based UEV scheme largely outperforms the “dummy UEs” approach.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CAPEX and OPEX costs, QoS or QoE, multi-tier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield “turnkey” WAV strategies.

This paper presents two new implementations of the maximum likelihood (ML) time delay estimation (TDE) from multi-carrier (MC) Direct-Sequence Spread Spectrum (DSSS) in multipath MIMO transmissions that will characterize future 5G radio interface technologies (RITs). The first TDE, based on expectation maximization (EM), provides accurate estimates of the delays when a good initialisation of the parameters is available. The second TDE returns the global maximum of the compressed likelihood function (CLF) using the importance sampling (IS) technique without requiring any initialization. Interestingly, in the non-data-aided (NDA) case, temporal, spatial (transmit and receive), and frequency samples have the same impact on estimation accuracy and performance bound which depends on the product of these dimensions regardless of the channel correlation type. Furthermore, we cope with such channel correlations that arise in practice and, hence, become very challenging both in estimation and CRLB derivation in the data-aided (DA) case, but that have been so far overlooked in previous works.

We propose a novel range-free localization algorithm for wireless sensor networks (WSN)s that is robust against the anisotropic signal attenuation induced by fading, shadowing, and interference, etc., present in any wireless channel, and hereby develop a new distance estimation (DE) approach able to efficiently derive distances' estimates in closed form. Exploiting artificial neural networks (ANN)s, we also develop a power-efficient DE correction mechanism that properly accounts for anisotropic signal attenuation. Simulation results show that the proposed algorithm significantly outperforms most representative range-free localization algorithms, not only in accuracy, but also in robustness against anisotropic attenuation.

In this paper, we propose a new code-aided (CA) maximum likelihood (ML) approach for time synchronization in turbo-coded systems. The time delay estimate is refined at each turbo iteration owing to the increasingly accurate estimates for the log-likelihood ratios (LLRs) of the coded bits. The refined time delay estimate is then used by the matched filter (MF) in order to provide the soft-input soft-output (SISO) decoders with more reliable symbol-rate samples for the next turbo iteration. Simulation results show the remarkable performance improvements of CA estimation against the traditional non-data-aided (NDA) estimation scheme. Moreover, the new CA ML estimator (MLE) enjoys significant advantage in computational complexity over existing ML CA solutions.

In this paper, we unify the performance analysis for the outage probability (OP) and the bit-error rate (ABER) of relay-assisted dual-hop free-space optics (FSO) transmission under heterodyne detection and intensity modulation/direct detection (IM/DD). The FSO link experiences the generalized Malaga-m distribution with pointing errors. under the assumption of fixed and variable gain relaying schemes, we derive the analytical closedform expressions for the performance metrics in terms of bivariate Fox-H function (FHF). Finally, we present some Monte-carlo simulation results to corroborate the new derived expressions.

Wireless sensor networks (WSNs) have recently enabled many new applications often dubbed ”smart” as a result of it. And researchers are currently giving much attention to localization in WSNs for the increasing number its use cases in real life. Two main localization categories prevail in the literature: range-based and range-free. The latter exploit the networks connectivity information in order to approximate the nodes locations, while the former accomplishes that by measuring actual distances. One of the widely investigated range-free WSN localization techniques is the DV-Hop. In this paper, we will develop and analyze the performance of a new enhanced version of this reference technique using a novel weighted hop-size expression. The simulation results indicate an improvement of the performance in terms of accuracy.

Code-domain non-orthogonal multiple access (NOMA), a much more sophisticated and efficient generalization of code division multiple access (CDMA), is a promising candidate for future 5G transceivers. Precisely, the CDMA Spatio-Temporal Array-Receiver (STAR) transceiver lends itself to very flexible reconfiguration and adaptation to most NOMA-type radio access technologies. It also possesses among other assets extremely high temporal synchronization capabilities. In this paper, we tackle the hardware feasibility of STAR and provide a proof of concept for a STAR-based time-delay estimator (TDE) through an FPGA-based real-time operational prototype running on a MiniBee Software-Defined-Radio (SDR) platform. We propose a modular, versatile, and reconfigurable architecture for the most basic and simplest “canonic” version of STAR at very low usage of FPGA resources, thereby paving the way for the quick implementation of extended and more complex configurations of this powerful transceiver. The real-time performances of the new prototype in terms of time-delay tracking accuracy compared to the original reference MATLAB version confirm the high precision and robustness of our new design to quantization errors and to all other hardware implementation imperfections.

A novel MIMO cognitive transceiver (CTR) for LTE-downlink communication system is devised in this work. We consider the cognition concept from the perspective of providing a highly reliable communication to the mobile user anytime anywhere. Rather than handling spectrum allocation (the common perspective of cognitive radio), we consider the channel estimation as the reconfiguration parameter of the proposed CTR. The developed cognitive transceiver is capable of selecting the best channel identification scheme between the conventional least squares (LS) estimator and the recently proposed maximum likelihood (ML) estimator. the proposed CTR is also able to toggle between the conventional pilot-assisted or data-aided (DA) mode and the non-data-aided with pilot (NDA with pilot) mode that relies on both reference and data symbols to track the channel variations. The decision rules of the new CTR that identify the best combination couple of pilot-use and channel-identification modes are drawn after running extensive and exhaustive LTE-downlink link-level simulations. The proposed CTR outperforms all static transceivers, in terms of link-level performance, for any given operating conditions such as SNR, mobile speed, channel type, and channel quality indicator (CQI). The new proposed CTR offers significant link-level throughput gains against the LS channel estimator working in a pilot-assisted mode in most operating conditions and the improvement gains can reach as much as 100% at low SNR and high mobility!

This paper presents the measurements results of a 60 GHz wireless channel in underground mine galleries at depths of 40 m and 70 m. Different antenna polarizations and configurations were considered in this study. Results show that the rough surface scattering and the gallery dimensions of the underground mine significantly impact on the time dispersion characteristics. Particularly, a vertical antenna configuration provides a larger number of multipath than a horizontal one. Due to the fact of gallery dimension and surface roughness characteristics, the 70 m-depth gallery provides a lower value of delay spread and more time variation phenomenon than the 40 m-depth. Omnidirectional antenna configurations are also shown to be not feasible for point to point link. The characteristics of the power delay profile of the scattered channel based on the antenna radiation pattern and impact on its time dispersion are discussed.

Statistical characterization of the signal-to-interference-plus-noise ratio (SINR) via its cumulative distribution function (CDF) is ubiquitous in a vast majority of technical contributions in the area of cellular networks since it boils down to averaging the Laplace transform of the aggregate interference, a benefit accorded at the expense of confinement to the simplistic Rayleigh fading. In this work, to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios, we tackle the problem differently. By exploting the moment generating function (MGF) of the SINR, we succeed in analytically assessing cellular networks performance, namely the achievable rate and and the bit error probability (BEP), over the shadowed κ-μ, κ-μ and η-μ fading models. These models offer higher flexibility to capture diverse and more realistic fading environments than the classical Rayleigh, Nakagami-m, and Rician ones.

This paper investigates the impact of radio frequency (RF) cochannel interference (CCI) on the performance of dual-hop free-space optics (FSO)/RF relay network. The considered FSO/RF system operates over mixed Malaga-M/composite fading/shadowing generalized-K (GK) channels with pointing errors. The H-transform theory, wherein integral transforms involve Fox's H-functions as kernels, is embodied into a unifying performance analysis framework that encompasses closed-form expressions for the outage probability, the average bit error rate (BER), and the ergodic capacity. By virtue of some H-transform asymptotic expansions, the high signal-to-interference-plus-noise ratio (SINR) analysis culminates in easy-to-compute expressions of the outage probability and BER.

This paper provides an analytically tractable framework for investigating a fading model-free statistical distribution of the signal-to-interference-plus-noise power ratio (SINR) in Poison distributed cellular networks subject to device-to-device (D2D) transmissions. Our main finding show that a closed-form SINR distribution may be obtained for any fading scenario in which the per-link power gain follows the product of two Fox's H-function probability density function thereby subsuming most of the coverage probability expressions previously presented for all the known simple and composite fading models.

In this paper, we develop a new dynamic utility for wireless access virtualization (WAV) optimization embodying highly-dimensional time-varying multi-criteria metrics (i.e., CaPeX and OPEX costs, QoS or QoE, multitier and/or multi-RAT HetNets, etc.) that gauge the best deployment and viability scenarios of cloud (C)- and fog (F)-RANs within legacy networks. Exploiting the powerful tool of graph theory, we devise a progressive greyfield WAV strategy that optimizes our dynamic utility through an efficient combination of C- and F-RANs. This strategy is able to readjust very quickly to any changes in existing or new constraints as they evolve or occur in time, respectively. The resulting optimized hybrid RAN deployment outperforms both the greenfield and the pre-planed greyfield ”turnkey” WAV strategies.

In this paper, amplify-and-forward beamforming (AFB) is considered to establish a reliable communication between devices in networked smart cities. All sources send their data during the first time slot while the cooperative terminals forward a properly weighted version of their received signals during the second. These zero-forcing AFB (ZFB) weights are properly selected to maximize the desired power while completely canceling the interference signals. We show, however, that their implementation requires a huge terminals' information exchange, making ZFB unsuitable for smart cities where the overhead and power restrictions are very stringent. To address this issue, we exploit the asymptotic expression at large K of the ZFB weights whose computation requires much less information exchange and, further, well-approximate their original counterparts. The performance of the proposed beamforming is analyzed and compared to ZFB and monochromatic (i.e., single-ray) AFB (MB) whose design neglects the presence of scattering.

This paper addresses the problem of Doppler spread and carrier frequency offset (CFO) estimation under flat-fading Rayleigh channels. We develop a new low-cost and robust approximate maximum likelihood (ML) estimator for these two key parameters that builds upon an elegant two-ray approximation model of the channel's covariance matrix. The latter is then inverted analytically thereby yielding a closed-form expression for the underlying log-likelihood function that is prone to easy evaluation by the fast Fourier transform. Computer simulations show that the new estimator is accurate over wide ranges of the Doppler spread and CFO parameters. Moreover, it outperforms many state-of-the-art techniques under the adverse conditions of short data records and/or low SNR thresholds. Most prominently, it exhibits an unprecedented robustness to the Doppler spectrum shape of the channel since it does not require its a priori knowledge.

Statistical characterization of the signal-tointerference-plus-noise ratio (SINR) via its cumulative distribution function is ubiquitous in a vast majority of technical contributions in the area of cellular networks, since it boils down to averaging the Laplace transform of the aggregate interference, a benefit accorded at the expense of confinement to the simplistic Rayleigh fading. In this paper, to capture diverse fading channels that arise in realistic outdoor/indoor wireless communication scenarios, we tackle the problem differently. By exploiting the moment generating function of the SINR, we succeed in analytically assessing cellular networks performance over the shadowed κ-μ, κ-μ, and η-μ fading models. These channel models offer high flexibility by capturing diverse fading channels, including Rayleigh, Nakagami-m, Rician, and Rician shadow fading distributions. These channel models have been recently promoted for their capability to accurately model dense urban environments, future femtocells, and device-to-device shadowed channels. In addition to unifying the analysis for different channel models, this paper integrates the coverage, the achievable rate, and the bit error probability, which are largely treated separately in the literature. The developed model and analysis are validated over a broad range of simulation setups and parameters.

In this paper, we address the problem of direction of arrival (DOA) estimation from turbo-coded square-QAM-modulated transmissions. We devise a new code-aware direction finding concept, derived from maximum likelihood (ML) theory, wherein the soft information provided by the soft-input soft-output decoder, in the form of log-likelihood ratios, is exploited to assist the estimation process. At each turbo iteration, the decoder output is used to refine the ML DOA estimate. The latter is in turn used to perform a more focused receiving beamforming thereby providing more reliable information-bearing sequences for the next turbo iteration. In order to benchmark the new estimator, we also derive the analytical expressions for the exact Cramer-Rao lower bounds (CRLBs) of code-aided (CA) DOA estimates. Simulation results will show that the new CA direction finding scheme lies between the two traditional schemes of completely non-data-aided and data-aided (DA) estimations. Huge performance improvements are achieved by embedding the direction finding and receive beamforming tasks into the turbo iteration loop. Moreover, the new CA DOA estimator reaches the new CA CRLBs over a wide range of practical SNRs thereby confirming its statistical efficiency. As expected intuitively, its performance further improves at higher coding rates and/or lower modulation orders.

In this paper, we address the problem of time delay estimation (TDE) from single-carrier (SC) or multi-carrier (MC) direct-sequence spread spectrum (DSSS) multipath transmissions in the presence of multiple transmit and/or receive antennas that will characterize future 5G radio interface technologies (RITs), such as coded-domain nonorthogonal multiple access. We derive for the first time a closed-form expression for the Cramer-Rao lower bound (CRLB) and develop two maximum likelihood (ML) multipath TDEs for SC DSSS single-input multiple-output (SIMO) in the non-data-aided (NDA) case. The first TDE, based on iterative expectation maximization (EM), provides accurate estimates whenever a good initial guess of the parameters is available at the receiver. The second TDE implements the ML criterion in a non-iterative way and finds the global maximum of the compressed likelihood function using the importance sampling (IS) technique without requiring any initialization. We also extend both the SC DSSS SIMO CRLB and the two new SC DSSS SIMO ML NDA TDEs to MC DSSS RITs and to multiple-input multiple-output structures with any diversity versus multiplexing pre-coding type before generalizing them all to the data-aided (DA) case. Simulations suggest that the EM TDE is suitable for large observation in space, time, and/or frequency, whereas the IS TDE is preferred in the opposite case of very short data records. Moreover, we show in the NDA case, both analytically and by simulations, that spatial (transmit and receive), temporal, and frequency samples interchangeably have the same impact on estimation accuracy and performance bound regardless of the channel correlation type and amount present in each dimension. Furthermore, we are able to properly cope with such channel correlations that do indeed arise in practice and, hence, become very challenging both in estimation and CRLB derivation in the DA case, but that have been so far overlooked in previous works.

In this paper, we consider the problem of signal-to-noise ratio (SNR) estimation from turbo-coded (TC) PAM and rectangular-QAM (RQAM) modulated signals over flat-fading channels. We derive for the first time closed-form expressions for the Cramer-Rao lower bounds (CRLBs) of the SNR estimates. We exploit the structure of the binary-reflected-Gray-code (BRGC) for bits-to-symbols mapping, so that the likelihood function (LF) becomes factorized into a sum of two simple terms. This factorization allows the linearization of the log-likelihood function (LLF), which allowed us to carry the derivation of the Fisher Information Matrix (FIM) elementsanalytically, and derive the code aided (CA) SNR CRLB in closed-form (CF). These new CF expressions corroborate the CA bounds established previously in the particular case of square-QAM constellations. They finally tackle the new problem never addressed until now of CA SNR estimation from PAM/RQAM signals. In the low-to-medium SNR level, the new CRLBs for the CA estimates of the SNR range between their respective CRLBs in the non-data-aided (NDA) and data-aided (DA) scenarios, thereby highlighting and quantifying the advantage of CA estimation against the NDA. In high SNR, they coincide with the DA CRLB. These bounds also confirm the increase in estimation accuracy achievable by decreasing the coding rate.

We derive for the first time closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the joint channel phase, and carrier frequency offset (CFO) estimates from turbo-coded (TC) Pulse-amplitude modulation (PAM) and rectangular-QAM (RQAM) modulated signals over flat-fading channels. After wisely exploiting the properties of Gray mapping, we are able to simplify the log-likelihood function (LLF) to enable the CRLBs derivation in closed form. We show that the phase and the CFO can be decoupled if the set of sampling indices is centered on zero. These new bounds generalize those previously derived in closed form in the special case of TC square-QAM constellations or established empirically in the case of phase and CFO code-aided (CA) estimation, respectively. Numerical results suggest that the new CRLBs range between their respective CRLBs in the non-data-aided (NDA) and data-aided (DA) scenarios, thereby showcasing the expected advantage of CA estimation against both NDA and DA in terms of accuracy improvement or overhead reduction, respectively. They also illustrate the potential increase in estimation accuracy achievable by decreasing, as expected, the coding rate.

Simultaneous bidirectional transmission and reception of signals on a single channel in a full duplex (FD) system is gaining increased attention from both academia and industry. Recent advances in radio transceiver design have been able to minimize the self interference (SI) to a great extent making realization of a FD transceiver possible. For FD deployment in a multi-cell environment, minimizing SI is not sufficient due to the presence of a complex array of network-wide interference. This paper investigates the critical deployment challenges for a dense urban FD multi- cell network and provides solutions for successful deployment of FD cellular networks. Extensive simulation results show that the proposed user selection and power control algorithms are able to increase the FD performance gain by more than 80% when compared to the traditional half duplex (HD) counterpart.

In this paper, we develop a novel optimal anchors placement strategy tailored for anisotropic WSNs. By resorting to the well-known particle swarm optimization (PSO), we derive the optimal anchors' positions that minimize the average location estimation error (LEE). We show that our placement strategy provides substantial accuracy gains if used instead of the conventional ones and that it is able to reduce not only the average LEE but also the LEE itself and, hence, guarantees high accuracy for any WSN configuration.

In this paper, the asymptotic performance of multiuser multiple-antenna (MU-MIMO) relay networks employing opportunistic scheduling and operating in the presence of Rayleigh fading and co-channel interference is investigated. Notwithstanding the system complexity, due to the newly found complementary moment generating function (CMGF) transform, an exact expression for the capacity, when the antenna counts at the source and the user number are allowed to grow unbound, is obtained. The large scale analysis embodies popular observations, so far intuitively or empirically disclosed, through analytically insightful new formulas. An interesting aspect of this analysis comes from an altered view of multiuser diversity in the context of cellular systems. Previously, multiuser diversity capacity gain has been known to grow as 0(ln ln(K)), from selecting the maximum of K exponentially-distributed powers. Because interference aware scheduling is considered, we find instead that the gain is 0(ln(K1/Q)) where Q is the number of interferers. Simulation results indicate a rather fast convergence to the asymptotic limits with the system's size, thereby demonstrating the practical importance of the scaling results.

In this paper, we propose a novel range-free localization algorithm tailored for mobile ad hoc networks (MANET)s. In contrast to most existing range-free techniques, we take into account the nodes mobility and hence enable the nodes to estimate their positions using solely their locally-available information, thereby avoiding any unnecessary costs in overhead and power that would have been incurred if information exchange between nodes were required. Furthermore, we show that the proposed algorithm outperforms in accuracy the best representative range-free algorithms. In contrast to the latter, it is able to compensate the nodes mobility effects when the nodes' speeds are moderate.

To localize multi-hop wireless sensor networks (WSN) nodes, only the hop-based information (i.e., hops' number, average hop size, etc.) have been so far exploited by rangefree techniques, with poor-accuracy, however. In this paper, we show that localization accuracy may greatly benefit from joint exploitation, at no cost, of the information already provided by the forwarding nodes between each anchor (i.e., position-aware) and sensor nodes pair. As such, we develop a novel rangefree localization algorithm, derive its average location estimation error (LEE) in closed-form, and compare it in LEE performance with the best representative algorithms in the literature. We show that the proposed algorithm outperforms in accuracy all its counterparts. In contrast to the latter, we further prove that it is able to achieve a LEE average and variance of about 0 when the number of sensors is large enough, thereby achieving an unprecedented accuracy performance among rangefree techniques.

In this paper, we consider a collaborative beam-former (CB) design that achieves a dual-hop communication from a source to a receiver in highly-scattered environments, through a wireless network comprised of K independent terminals. The weights of the considered CB design at these terminals, derived to maximize the received signal-to-noise ratio (SNR) subject to constraint over the terminals' total transmit power, have expressions that inevitably depend on some form of the channel state information (CSI). Only those requiring the local CSI (LCSI) available at their respective terminals lend themselves to a truly distributed implementation. The latter has the colossal advantage of significantly minimizing the huge overhead resulting otherwise from non-local CSI (NLCSI) exchange required between terminals, which becomes prohibitive for large K and/or high Doppler. We derive the closed-form expression of the SNR-optimal CB (OCB) and verify that it is a NLCSI-based design. Exploiting, however, the polychromatic (i.e., multi-ray) structure of scattered channels as a superposition of L impinging rays or chromatics, we propose a novel LCSI-based distributed CB (DCB) design that requires a minimum overhead cost and, further, performs nearly as well as its NLCSI-based OCB counterpart. Furthermore, we prove that the proposed LCSI-based DCB outperforms two other DCB benchmarks: the monochromatic (i.e., single-ray) DCB (M-DCB) whose design ignores the presence of scattering and the bichromatic (i.e., two-ray) DCB (B-DCB) which relies on an efficient polychromatic-channel approximation by two rays when the angular spread is relatively small.

The ergodic capacity of multiuser multiple-antenna amplify and forward relay networks with co-channel interference is investigated. Notwithstanding the system complexity, the proposed capacity analysis framework was made possible owing to the newly found complementary moment generating function transform. First, the exact expression for the ergodic capacity, under interference-aware opportunistic scheduling and Rayleigh fading, is derived for finite antenna and user counts. In addition, using extreme value theory, closed-form expressions for the asymptotic ergodic rates are derived for an unlimited number of users or/and antennas at the source. The large-scale analysis embodies, through new insightful formulas, common popular observations so far disclosed intuitively or empirically. Capitalizing on these novel scaling laws, we have been able to derive new closed-form expressions for capacity losses due to intercell interference at the relay and all users. Simulation results suggest a rather fast convergence of the capacity gains to the new asymptotic limits, thereby demonstrating the practical importance of our novel scaling results.

To localize the wireless sensor networks nodes, only the hop-based information (i.e., hops' number, average hop size, and so on) has been, so far, exploited by range-free techniques, with poor-accuracy, however. In this paper, we show that localization accuracy may greatly benefit from joint exploitation, at no cost, of the information already provided by the forwarding nodes (i.e., relays) between each anchor (i.e., position aware) and sensor nodes pair. As such, we develop a novel range-free localization algorithm, derive its average location estimation error (LEE) in closed-form, and compare it in LEE performance with the best representative algorithms in the literature. We show that the proposed algorithm outperforms them in accuracy. In contrast to the latter, we further prove that it is able to achieve an LEE average and variance of about 0 when the number of sensors is large enough, thereby achieving an unprecedented accuracy performance among range-free techniques.

In this paper, we propose a novel low-cost localization algorithm tailored for multihop heterogeneous wireless sensor networks (HWSNs) where nodes' transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes' transmission capabilities, we develop two different approaches to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism, which complies with the heterogeneous nature of wireless sensor networks (WSNs) to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outperforms in accuracy the most representative WSN localization algorithms.

Wireless access virtualization is an emerging avenue for research for future 5G networks. For its ability to augment network sharing and its subsequent impact on reducing network setup and operational costs, network virtualization is greatly sought after by telecommunications operators all over the world. This paper classifies virtual wireless access into three possible PHY-MAC models that differ in terms of the degree of segregation of baseband signal processing and radio access units. One of the models uses special purpose hardware while another leverages software defined networking (SDN) and cloud computing technologies for implementing virtual wireless access using general purpose hardware. The proposed models differ in terms of their associated network operational cost as well as in terms of the level of QoS they can provide. A new multi-criteria utility function is hence proposed in order to assess the tradeoffs between network cost & QoS of these models from a PHY-MAC layer perspective. The new utility function provides guidelines for a network designer to choose the optimal virtualization model that best fits an operator's budget constraint as well as the QoS requirement of the intended service. Analytical results show that a novel hybrid model that properly combines both special purpose and SDN & cloud computing technologies maximizes the newly introduced utility function by attaining the best balance between overall network cost and QoS. This occurs in most expected practical cases where precisely, one of the two does not relatively outweigh the other and viceversa.

Abstract In this paper, we design a new single‐input multiple‐output context‐aware cognitive transceiver (CTR) that is able to switch to the best performing modem in terms of link‐level throughput. On the top of conventional adaptive modulation and coding, we allow the proposed CTR to make best selection between three different pilot‐utilization modes: conventional data‐aided (DA) or pilot‐assisted, non‐DA (NDA) or blind, and NDA with pilots, which is a newly proposed hybrid version between the DA and NDA modes. We also enable the CTR to make best selection between two different channel identification schemes: conventional least‐squares (LS) and newly developed maximum‐likelihood estimators. Depending on whether pilot symbols can be exploited or not at the receiver, we further enable the CTR to make the best selection among two data detection modes: coherent or differential. Owing to exhaustive link‐level simulations on the downlink of a long‐term evolution system, we draw out the optimal decision rules in terms of the best combination triplet of pilot‐use, channel‐identification, and data‐detection modes that yield the best link‐level throughput as function of channel type, mobile speed, signal‐to‐noise ratio, and channel quality indicator. The proposed CTR offers a link‐level throughput gains improvement as high as 700%compared with DA LS for VehB channel type at a mobile speed of 100 km/h in the low signal‐to‐noise ratio region. For VehA channels, its throughput gain improvements can reach 114%. For PedA and PedB channels, the proposed CTR provides throughput enhancements of about 66%and 330%, respectively. Moreover, realistic simulations at the system‐level of the long‐term evolution‐HetNet network suggest that the new context‐aware CTR outperforms the conventional transceiver (i.e., pilot‐assisted LS‐type channel estimation with coherent detection) by as much as 50% and 60% gains in average and cell‐edge (i.e., five percentile) throughputs, respectively, in the high‐clustering case with type‐B channels. In the low clustering scenario, the average and cell‐edge throughput gain improvements offered by the proposed CTR exceed 80% and 90% for type‐B channels. Copyright © 2016 John Wiley & Sons, Ltd.

Abstract In a heterogeneous network (HetNet), small cells such as femtocells considered in this work are deployed jointly with macrocells. This new cells' layer, when added to the network, generates interference, which could hamper neighboring macro‐user equipment (MUE) and femto‐user equipment (FUE) transmissions. In fact, this interference results in degradation of the network performance. In this paper, we propose a downlink interference cancelation (DL‐IC) strategy for spectrum‐sharing Long Term Evolution (LTE) HetNet. This DL‐IC strategy aims to reduce the interference impact on users by optimizing their received signal to interference plus noise ratio (SINR) using new utility functions for both FUEs and MUEs. These utility functions allow relaxation of the cancelation ratios in order to reduce implementation complexity while maximizing SINR, QoS, and throughput. We support by different system‐level simulations that both global network performance and user experience in terms of total throughput and received SNR or link‐level throughput, respectively, are significantly enhanced. Throughput gains achievable by the new DL‐IC strategy can reach as much as 200%against a homogeneous LTE network without IC along with an extra 48%per additional femtocell base station against a basic spectrum‐sharing LTE HetNet without IC. These performance figures are shown to surpass those achieved by interference avoidance techniques using either power or frequency resource allocation. Copyright © 2014 John Wiley & Sons, Ltd.

This paper tackles the problem of code-aided (CA) timing recovery in turbo-coded square-QAM transmissions. Owing to a simple recursive construction process, some hidden properties of Gray-coded (GC) square-QAM constellations are demystified and the code bits' a priori log- likelihood ratios (LLRs) are explicitly incorporated in the log-likelihood function (LLF). Then, by splitting the underlying LLF into the sum of two analogous terms, we derive for the very first time the closed-form expressions for the exact Cramer-Rao lower bounds (CRLBs) of the underlying turbo synchronization problem. Computer simulations will show that the new closed-form CRLBs coincide exactly with their empirical counterparts evaluated previously using exhaustive Monte-Carlo simulations. They will also show unambiguously the remarkable performance improvements of the CA scheme against the traditional non-data-aided (NDA) one. Over a wide range of practical SNRs, the new CA CRLBs reach those of the completely data-aided (DA) scheme in which all the transmitted symbols are perfectly known to the receiver.

In this paper, we consider a collaborative beamforming (CB) technique to achieve a dual-hop communication from a source surrounded by MIinterferences to a receiver, through a wireless network comprised of K independent terminals. The CB weights are designed so as to minimize the interferences plus noises' powers while maintaining the received power from the source to a constant level. We show, however, that they are intractable in closed-form due to the complexity of the polychromatic channels arising from the presence of scattering in real-world environments. By recurring to a two-ray channel approximation proved valid at relatively low angular spread (AS) values, we are able to derive the new optimum weights and prove that they could be locally computed at each terminal, thereby complying with the distributed feature of the network of interest. The so-obtained bichromatic distributed collaborative beamforming (B-DCB) is then analyzed and compared in performance to the monochromatic CB (MCB), whose design does not account for scattering, and the optimal CSI-based CB (OCB). It is shown that the proposed B-DCB outperforms its counterparts in real-world environments.

This paper tackles the problem of the direction of arrival (DOA) estimation in turbo-coded systems. We derive for the first time the closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the code-aided (CA) DOA estimates from arbitrary square-QAM modulated signals. We succeed in factorizing the likelihood function of the system into two analogous terms linearizing thereby all the derivation steps of the Fisher information (FI) element. Simulation results demonstrate that the CRLB for the CA DOA estimates lies between its counterparts in non-data-aided (NDA) and data-aided (DA) estimation schemes. Moreover, the DOA CA CRLB improves by decreasing the coding rate highlighting thereby the potential gain in estimation performance stemming from the proper exploitation of the decoder output.

In this paper, we propose a novel low-cost localization algorithm tailored for multi-hop heterogeneous wireless sensor networks (HWSNs) where nodes' transmission capabilities are different. This characteristic, if not taken into account when designing the localization algorithm, may severely hinder its accuracy. Assuming different nodes' transmission capabilities, we develop a novel approach to derive the expected hop progress (EHP). Exploiting the latter, we propose a localization algorithm that is able to accurately locate the sensor nodes owing to a new low-cost implementation. Furthermore, we develop a correction mechanism which complies with the heterogeneous nature of WSNs to further improve localization accuracy without incurring any additional costs. Simulations results show that the proposed algorithm, whether applied with or without correction, outper-forms in accuracy the most representative WSN localization algorithms.

In this paper, we analyze the ergodic capacity of a two-hop multiple-antenna amplify and forward (AF) system, where the relay is subject to co-channel interference (CCI) while the destination is corrupted by additive white Gaussian noise (AWGN) only. A novel integral transform, called the complementary moment generating function transform (CMGF), is proposed as a unified tool to compute the ergodic capacity. When both the relay and destination perform maximum ratio combining (MRC), we derive a new analytical exact expression for the ergodic capacity. It is shown that the ergodic capacity is better improved by increasing the number of antennas at the relay Nrthan that at destination Nd. Unfortunately, the system shows an incapability of canceling interference even if Nrand/or Ndgrows large.

This paper investigates spectrum-sharing cognitive amplify-and-forward (AF) relay networks employing the maximum ratio transmission/maximum ratio combining (MRT/MRC) scheme at the multiple-antenna source-destination pair. It derives closed-from expressions for the ergodic capacity as well as for the symbol error rate (SER) lower bound and its asymptotic value when considering Nakagami-m fading and interference constraints on N primary receivers.

In this paper, we design a new single-input multiple-output (SIMO) context-aware cognitive transceiver (CTR) that is able to switch to the best performing modem in terms of link-level throughput. On the top of conventional adaptive modulation and coding (AMC), we allow the context-aware CTR to make best selection among three different pilot-utilization modes: conventional decision-aided (DA) or pilot-assisted, non-DA (NDA) or blind, and NDA with pilot which is a newly proposed hybrid version between the DA and NDA modes. We also enable the CTR to make best selection between two different channel identification schemes: conventional least-square (LS) and newly developed maximum-likelihood (ML) estimators. Depending on whether pilot symbols can be properly exploited or not at the receiver, we further enable the CTR to make best selection among two data detection modes: coherent or differential. Owing to extensive and exhaustive simulations on the downlink (DL) of a long-term evolution (LTE) heterogeneous network (HetNet), we are able draw out the decision rules of the new CTR that identify the best combination triplet of pilot-use, channel-identification, and data-detection modes to achieve the best link-level throughput at any operating condition in terms of channel type, mobile speed, signal-to-noise ratio (SNR), and channel quality indicator (CQI). Realistic extensive simulations at the system level suggest that the new context-aware CTR outperforms the conventional transceiver (i.e., pilot-assisted LS-type channel estimation with coherent detection) by as much as 40 and 45% gains in average and cell-edge (i.e., 5-percentile) total throughput per macro-area with 10 pico-cells each, respectively.

Virtualization is seen as a killer application of software defined networking (SDN). Virtual radio access network (RAN) is an emerging concept for 5G and beyond 5G networks and it is gaining increased attention from both academia and industry alike. Moreover, due to the current telecommunication trend of increasing network traffic and decreasing revenue, telecom operators all over the world are looking for network function virtualization (NFV) to reduce network deployment and running cost by maximizing resource sharing. In this paper, we classify virtual RAN into three possible PHY-MAC models that leverage SDN for virtualizing the underlying RAN substrate. A novel multi-criteria utility function is also proposed to evaluate the trade-offs between network cost and achievable QoS from PHY-MAC layers perspectives of these virtual RAN models. Analytical results show that a hybrid virtualization model attains the optimal balance between network cost and QoS and hence is the best virtual RAN model.

In this paper, we consider a dual-hop communication from a source surrounded by MIinterferences to a receiver, through a wireless network comprised of K independent terminals. In the first time slot, all sources send their signals to the network, whereas in the second time slot, the terminals multiply the received signal by their respective beamforming weights and forward the resulting signals to the receiver. We design these weights so as to minimize the interferences plus noises' powers while maintaining the received power from the source to a constant level. We show, however, that they are intractable in closed form due to the complexity of the polychromatic channels arising from the presence of scattering. By resorting to a two-ray channel approximation proved valid at relatively low angular spread (AS) values, we are able to derive the new optimum weights and prove that they could be locally computed at each terminal, thereby complying with the distributed feature of the network of interest. The so-obtained bichromatic distributed collaborative beamforming (B-DCB) is then analyzed and compared in performance to the monochromatic CB (MCB), whose design does not account for scattering, and the optimal CSI-based CB (OCB). Comparisons are made under both ideal and real-world conditions where we account for implementation errors and the overhead incurred by each CB solution. They reveal that the proposed B-DCB always outperforms MCB in practice; and that it approaches OCB in lightly to moderately scattered environments under ideal conditions and outperforms it under real-world conditions even in highly scattered environments. In such conditions, indeed, the B-DCB operational regions in terms of AS values over, which it is favored against OCB could reach until 50° and hence cover about the entire span of AS values.

In this paper, we consider the problem of joint phase and carrier frequency offset (CFO) estimation for turbo-coded systems. We derive for the first time the closed-form expressions for the exact Cramér-Rao lower bounds (CRLBs) of these estimators over turbo-coded square-QAM-modulated single- or multi-carrier transmissions. In the latter case, the derived bounds remain valid in the general case of adaptive modulation and coding (AMC) where the coding rate and modulation order vary from one subcarrier to another depending on the corresponding channel quality information (CQI). In particular, we introduce a new recursive process that enables the construction of arbitrary Gray-coded square-QAM constellations. Some hidden properties of such constellations will be revealed, owing to this recursive process, and carefully handled to decompose the system's likelihood function (LF) into the sum of two analogous terms. This decomposition makes it possible to carry out analytically all the statistical expectations involved in the Fisher information matrix (FIM). The new analytical CRLB expressions corroborate the previous attempts to evaluate the underlying bounds empirically. In the low-to-medium signal-to-noise ratio (SNR) region, the CRLB for code-aided (CA) estimation lies between the bounds for completely blind [non-data-aided (NDA)] and completely data-aided (DA) estimation schemes, thereby highlighting the effect of the coding gain. Most interestingly, in contrast to the NDA case, the CA CRLBs start to decay rapidly and reach the DA bounds at relatively small SNR thresholds. It will also be shown that contrary to the CRLB of the phase shift, the CRLB of the CFO improves in a multi-carrier system as compared to its counterpart in a single-carrier system. The derived bounds are also valid for LDPC-coded systems and they can be evaluated in the same way when the latter are decoded using the turbo principal.

In this contribution, we derive for the first time the closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of the signal-to-noise ratio (SNR) estimates from turbo-coded square-QAM transmissions. By exploiting the structure of the Gray mapping, we are able to factorize the likelihood function thereby linearizing all the derivation steps for the FIM elements. The analytical CRLBs coincide exactly with their empirical counterparts validating thereby our new analytical expressions. Numerical results suggest that the CLRBs for code-aided (CA) SNR estimates range between the CRLBs for non-data-aided (NDA) SNR estimates and those for data-aided (DA) ones, thereby highlighting the effect of the coding gain. At sufficiently high SNR levels, the three CRLBs coincide. The derived bounds are also valid for LDPC-coded systems and they can be evaluated in the same way when the latter are decoded using the turbo principal.

We consider the problem of joint phase and carrier frequency offset (CFO) estimation from turbo-coded square-QAM modulated signals. We derive for the first time the closed-form expressions for the exact Cramér-Rao lower bounds (CRLBs) of this estimation problem. In particular, we introduce a new recursive process that enables the construction of arbitrary Gray-coded square-QAM constellations. Some hidden properties of such constellations will be revealed and carefully handled in order to decompose the likelihood function (LF) into the sum of two analogous terms. This decomposition makes it possible to carry out analytically all the statistical expectations involved in the Fisher information matrix (FIM). The new analytical CRLB expressions corroborate the previous attempts to evaluate the underlying perfromance bounds empirically. In the low-to-medium signal-to-noise ratio (SNR) region, the CRLB for code-aided (CA) estimation lies between the bounds for completely blind [non-data-aided (NDA)] and completely data-aided (DA) estimation schemes, thereby highlighting the coding gain potential in CFO and phase estimation. Most interestingly, in contrast to the NDA case, the CA CRLBs start to decay rapidly and reach the DA bounds at relatively small SNR thresholds. The derived bounds are also valid for LDPC-coded systems and they can be evaluated in the same way when the latter are decoded using the turbo principal.

In this paper, the importance sampling (IS) concept is exploited for the first time in the context of maximum likelihood (ML) estimation of both the time delays and angles of arrival (AoAs) in multipath propagation environments. The global maximum of the compressed likelihood function (CLF) is found empirically with a low computational cost. Simulations suggest that the new IS-based ML-type estimator outperforms, in terms of accuracy, the main state-of-the-art techniques published on the topic. It is also able to reach the Cramér-Rao-lower bound (CRLB) [13] with few received samples.

In this paper, we propose a new signal-to-noise-ratio (SNR) maximum likelihood (ML) estimator over time-varying single-input multiple-output (SIMO) channels, for both data-aided (DA) and non-data-aided (NDA) cases. Unlike the classical techniques which assume the channel to be slowly time-varying and, therefore, considered as constant during the observation period, we address the more challenging problem of instantaneous SNR estimation over fast time-varying channels. The channel variations are locally tracked using a polynomial-in-time expansion. In the DA scenario, the ML estimator is developed in closed-form expression. In the NDA scenario, however, the ML estimates of the per-antenna SNRs are obtained iteratively, with very few iterations, using the expectation-maximization (EM) procedure. Our estimator is able to accurately estimate the instantaneous SNRs over a wide range of average SNR. We show through extensive Monte-Carlo simulations that the new estimator outperforms previously developed solutions.

This paper presents reflection coefficient measurements in order to analyze the scattering effect of rough walls and floor on mm-Wave propagation at 60 GHz in an underground mine. A 60 GHz frequency domain measurement system with directional antennas is considered. Reflection coefficients are obtained by individual reflected signals and line of sight (LOS) signals with a particular reflective angle then compared with theoretical models. Results suggest a distinguishable reflection and scattering characteristics between mine wall and floor. In specular directions, the path loss difference between the LOS and the reflected signal lies between 11 dB to 18 dB. In both surfaces, strong reflections on specular directions and scattering on non specular directions have been observed. Moreover, wall surface of the mine produces more scattering with strong reflections than floor surface. These reflection coefficient parameters are useful to estimate multipath signal strength in channel modelling for propagation prediction in underground mine.

In this paper, we propose a novel range-free localization algorithm tailored for anisotropic wireless sensors networks (WSN)s. Using the proposed algorithm, each regular or positionunaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. Indeed, simulations suggest that it outperforms the best representative range- free localization algorithms currently available in the literature in terms of accuracy.

In this paper, we consider distributed beamforming for spectrum sharing networks comprising two secondary transceivers, multiple secondary relays and multiple primary transceivers. The aim of this work is to improve the secondary system performance. We assume that the relays that reliably decode the secondary signals participate in the beamforming process. We also assume the presence of mutual interference between the primary and secondary systems, while beamforming is used to suppress the interference inflicted on the primary system. However, the interference inflicted on the secondary system is not mitigated. To examine the impact of this interference on the performance of the secondary system, we derive closed-form expressions for the outage probability and bit error rate (BER) over independent and identically distributed Rayleigh fading channels. Numerical results demonstrate the efficacy of beamforming in making the secondary system performance resilient against the interference caused by the primary system.

In this paper, we propose a novel range-free localization algorithm tailored for heterogeneous wireless sensor networks (WSNs), where nodes have different transmission capabilities. Two different approaches are developed to accurately derive the expected hop progress (EHP). It is shown that the obtained EHP depends solely on the information locally available at each node and, hence, can be computed in a localized manner. Furthermore, a localization correction mechanism which accounts for the heterogeneous nature of WSNs is developed. Simulations results show that the proposed algorithm, whether with or without correction, outperforms in accuracy the most representative range-free localization algorithms in the literature.

This paper evaluates the ergodic capacity of secondary dual-hop cognitive amplify-and-forward (AF) relay networks (CRNs) subject to arbitrary Nakagami-m fading. Considering a spectrum-sharing environment, we assume that the transmit power of secondary users is solely governed by the interference power constraint at N primary users. A closed-form expression for the ergodic capacity of the secondary AF CRN is derived for the first time and shown to be affected by the distance ratio of the interference link (from the secondary transmitter to the closest primary receiver) to the relaying link (between the secondary transmitter and the secondary receiver). This new ergodic capacity expression is validated and assessed by insightful simulations against different key CRN parameters.

Relay deployment performance, such as site planing and dimensioning, highly depends on the capacity of the wireless relay link. However, latter's performance can be severely harmed due to cochannel interference (CCI), particularly with the current aggressive reuse of the available radio spectrum. In this paper, we present an analytical framework for amplify-and-forward (AF) relay capacity that can be used for the deployment of two-hop cellular relay networks operating over generalized fading channels in the presence of cochannel interference. Nakagami-m and generalized-K distributions are used to model the relay and interference links in multipath and composite multipath/shadowing environments, respectively. Multiple antenna AF relaying systems employing transmit beamforming and maximum ratio combining (TB/MRC) are also investigated in the presence of CCI. The derived analytical results provide an efficient mathematical tool for the fast evaluation of the ergodic capacity of the system as well as for the investigation of the impact of key parameters such as fading, shadowing, number of antennas and CCI on the system's ergodic capacity.

In this paper, we use joint distributed beamforming and cooperative relaying in cognitive radio relay networks in an effort to enhance the spectrum efficiency and improve the performance of the cognitive (secondary) system. In particular, we consider a spectrum sharing system where a set of potential relays are employed to help a pair of secondary users in the presence of a licensed (primary) user. Among the available relays, only the reliable ones participate in the beamforming process, where the beamformer weights are obtained based on a linear optimization method. We investigate two well-known strategies, namely, selection decode-and-forward (SDF) and amplify-and-forward (AF) relaying in conjunction with distributed optimal beamforming. However, given the complexity of the performance analysis with optimal beamforming, we use zero forcing beamforming (ZFB), and compare both approaches through simulations. In this context, for SDF, we derive expressions for the probability density function (PDF) of the received signal-to-interference noise ratio (SINR) at the relays as well as at the secondary destination. As for the AF scheme, we obtain the exact expression for the cumulative distribution function (CDF) and the moment generating function (MGF) of the equivalent end-to-end SNR at the secondary destination. For both schemes, we derive closed-form expressions for the outage probability and bit error rate (BER) over independent and identically distributed Rayleigh fading channels for binary phase shift keying (BPSK) and M-ary quadrature amplitude modulation (M-QAM) schemes. Numerical results demonstrate the efficacy of the proposed scheme in improving the outage and BER performance of the secondary system while limiting the interference to the primary system. In addition, the results show the effectiveness of the combination of the cooperative diversity and distributed beamforming in compensating for the loss in the secondary system's performance due to the primary user's co-channel interference (CCI).

In this paper, a collaborative beamformer (CB) is considered to achieve a dual-hop communication from a source to a receiver, through a wireless network comprised of K independent terminals. Whereas previous works neglect the scattering effect to assume a plane-wave single-ray propagation channel termed here as monochromatic (with reference to its angular distribution), a multi-ray channel termed as polychromatic due to the presence of scattering is considered, thereby broadening the range of applications in real-world environments. Taking into account the scattering effects, the weights of the so-called polychromatic CB (P-CB) are designed so as to minimize the received noise power while maintaining the desired power equal to unity. Unfortunately, their derivation in closed-form is analytically intractable due to the complex nature of polychromatic channels. However, when the angular spread (AS) is relatively small to moderate, it is proven that a polychromatic channel may be properly approximated by two rays and hence considered as bichromatic. Exploiting this fact, we introduce a new bichromatic CB (B-CB) whose weights can be derived in closed-form and, further, accurately approximate the P-CB's weights. Yet these weights, which turn out to be locally uncomputable at every terminal, are unsuitable for a distributed implementation. In order to circumvent this shortcoming, we exploit the asymptotic expression at large K of the B-CB whose weights could be locally computed at every terminal and, further, well-approximate their original counterparts. The performances of the so-obtained bichromatic distributed CB (B-DCB) and its advantages against the monochromatic DCB (M-DCB), which is designed without accounting for scattering, are analytically proved and further verified by simulations at practical values of K.

In this paper, we propose a novel range-free localization algorithm able to reduce errors due to mapping the hops into distance units. Using the proposed algorithm, the mean hop size h̅sis locally derived at each regular or position-unaware node, thereby avoiding its broadcast by anchors (i.e., a few nodes aware of their exact position) as usually required in current state-of-the-art solutions and, hence, resulting in less battery power depletion. The analytical expression of h̅sis derived for different node distributions. Furthermore, it is shown that it is possible to locally compute h̅sat each regular node with or even without prior knowledge of the node distribution. Simulations results show that the proposed scheme outperforms the most representative range-free localization schemes in terms of accuracy.

This paper addresses the problem of Doppler spread estimation in Rayleigh flat fading channels using a new low-cost and robust maximum likelihood (ML) technique. Relying on a an elegant approximation of the channel covariance matrix by a two-ray model, we are able to invert the overall approximate covariance matrix analytically thereby obtaining a low-cost closed-form approximation of the likelihood function. We show by computer simulations that the new estimator is accurate over a wide Doppler spread range and that it outperforms many state-of-the-art techniques. In contrast to the latter, it exhibits an unprecedented robustness to the Doppler spectrum shape of the channel since it does not require its a priori knowledge.

In a heterogeneous network (HetNet), femtocells are deployed jointly with macrocells. This new cells' layer added to the network generates interference which would hamper neighboring macro user equipment (MUE) and femto user equipment (FUE) transmissions. In fact, this interference results in degradation of the network performance. In this paper, we propose a downlink interference cancellation (DL-IC) strategy for shared-spectrum LTE (Long Term Evolution) HetNet. This DL-IC strategy aims to reduce the interference impact on users by optimizing their received signal to interference plus noise ratio (SINR) using new utility functions for both FUEs and MUEs. These utility functions allow relaxation of the cancellation ratios in order to reduce implementation complexity while maximizing SINR, QoS and throughput. We support by different system-level simulations that both global network performance and user experience in terms of total throughput and received SNR or link-level throughout, respectively, are significantly enhanced. Throughput gains achievable by the new DL-IC strategy can reach as much as 200% against a homogeneous LTE network without IC along with an extra 48% per additional femtocell base station in a basic shared-spectrum LTE HetNet without IC.

In this paper, we consider collaborative beamforming for spectrum-sharing two-way relay networks in an effort to improve the performance of the cognitive system and enhance the spectrum efficiency. In such a joint relaying/spectrum-sharing setting, a pair of secondary transceivers communicates via a set of secondary decode-and-forward (DF) relays in the presence of multiple primary transceivers. Among the available relays, only those that receive the signals reliably participate in the cooperative beamforming process to nullify the interference inflicted on primary receivers. Furthermore, the received signals at relays and at secondary transceivers are unavoidably interfered by the signals from primary transmitters. To study the performance of the cognitive system under the effects of these co-channel interferences (CCIs) from the primary transmitters, we derive closed-form expressions for the outage probability and bit error rate (BER) over independent and identically distributed (i.i.d.) Rayleigh fading channels. Numerical results demonstrate the effectiveness of beamforming in compensating the cognitive system performance loss due to the CCIs in addition to mitigating the interference to the primary users.

We consider in this paper distributed beamforming for two-way cognitive radio networks in an effort to improve the spectrum efficiency and enhance the performance of the cognitive (secondary) system. In particular, we consider a spectrum sharing system where a set of decode-and-forward (DF) relays are employed to help a pair of secondary transceivers in the presence of multiple licensed (primary) users. Among the available relays, only those that receive the signals reliably participate in the beamforming process, where the optimal beamformer weights are obtained via a linear optimization method. We derive closed-form expression for the probability distribution function (PDF) of the total end-to-end signal-to-noise ratio (SNR) at the secondary transceiver. We also derive closed-form expressions for the outage and error probabilities over independent and identically distributed (i.i.d.) Rayleigh fading channels. Numerical results show the effect of beamforming in enhancing the secondary system performance in addition to mitigating the interference to the primary users.

Three main collaborative beamforming (CB) designs based on different channel models could be applied in real-world environments where local scattering and implementation imperfections might exist: the optimal CSI-based CB (OCB), the conventional or monochromatic (i.e., single-ray) distributed CB (M-DCB), and the recently developed bichromatic (i.e., two-ray) distributed CB (B-DCB). In this paper, we perform an analytical comparison, under practical constraints, between these CB designs in terms of achieved signal-to-noise ratio (SNR) as well as achieved throughput. Assuming the presence of local scattering in the source vicinity and accounting for implementation errors incurred by each CB design, we derive for the first time closed-form expressions of their true achieved SNRs. At a low angular spread (AS) where both designs nominally achieve the same SNR in ideal conditions, we show that the B-DCB always outperforms OCB, more so and at larger regions of AS values when errors increase. Excluding exceptional circumstances of unrealistic low quantization levels (i.e., very large quantization errors) hard to justify in practice, we also show that the new B-DCB always outperforms the M-DCB as recently found nominally in ideal conditions. This work is also the first to push the performance analysis of CB to the throughput level by taking into account the feedback overhead cost incurred by each design. We prove both by concordant analysis and simulations that the B-DCB is able to outperform, even for high AS values, the OCB which is penalized by its prohibitive implementation overhead, especially for a large number of collaborating terminals and/or high Doppler frequencies.

An analytical characterization of the ergodic capacity of interference-limited multihop wireless networks with amplify-and forward (AF) relaying is presented. In our analysis, we consider that transmissions are performed over Nakagami-m fading where channel state information is only known at the receiving terminals. We derive an exact expression for the ergodic capacity by exploiting the moment generating function (MGF) of the inverse signal-to-interference ratio (SIR). The result is applicable for arbitrary numbers of interfering signals at the receiving terminals and can be efficiently evaluated. Furthermore, considering the special case of dual-hop transmission, we propose a more refined characterization where the high-SIR capacity is expanded as an affine function. The zero-order term or the power offset for which we find insightful closed-form expressions, is shown to play a chief role in understanding the impact of interference and power on the system's capacity. Finally, some simulation results sustaining our analysis are provided.

Integrating relaying techniques into cellular communications sheds new light on higher capacity and broader coverage. However, applying relaying techniques in practice has to take into account important issues such as co-channel interference (CCI). In this work, a generalized framework for the ergodic capacity analysis of dual-hop fixed-gain amplify and forward (AF) relaying systems in the presence of interference is presented. New expressions for the ergodic capacity are derived considering transmissions over independent but not necessarily identically distributed Nakagami-m fading channels in the presence of a finite number of co-channel interferers. Our results establish that the ergodic capacity is dominated by the source-relay interference power and that it improves slowly with the average signal-to-noise ratio (SNR) increasing. It slightly deteriorates, however, with a larger Nakagami-m fading parameter for interference channels. Furthermore, our results offer an analytical insight into the key impact of relay placement on performance. Our new ergodic capacity expressions could therefore provide a very practical/low-cost performance optimization tool for relayed-communication system designers.

In this paper, we use a distributed beamforming method in cognitive radio relay networks in an effort to enhance the spectrum efficiency and improve the performance of the cognitive (secondary) system. In particular, we consider a spectrum sharing system where a set of potential relays are employed to help a pair of secondary users in the presence of a licensed (primary) user. A selection relaying scenario in an amplify and forward (AF) scheme is investigated. In this context, we obtain the exact expressions for the cumulative distribution function (CDF) and the moment generating function (MGF) of the equivalent end-to-end SNR at the secondary destination. Then, to analyze the performance, we derive closed-form expressions for the outage probability and bit error rate (BER) over independent and identically distributed (i.i.d.) Rayleigh fading channels. Numerical results demonstrate the efficacy of beamforming in improving the secondary system performance in addition to limiting the interference to the primary users.

In this paper, a minimum variance distortionless response (MVDR) collaborative beamformer (CB) is considered to achieve a dual-hop communication from a far-field source surrounded by several interfering transmitters to a receiver, through a wireless network comprised of K independent terminals. Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source and interferences vicinities is considered, thereby broadening the range of applications in real-world environments. It is shown that the required bandwidth allocation to the MVDR CB implementation linearly increases with K and becomes prohibitive in some applications where the number of terminals is typically large. Aiming to improve the system's spectrum efficiency, a novel distributed collaborative beamformer (DCB) whose implementation does not require any bandwidth allocation and, further, that well-approximates its MVDR CB counterpart is then proposed. The performance of the proposed technique is analyzed and its net advantages against the scattering-free DCB technique, which is designed without taking into account the presence of local scattering in the source and interferences vicinities, are proved.

In this paper, transmit and receive collaborative beamforming (CB) techniques are considered to achieve a dualhop communication from a source to a receiver, through a wireless network comprised of K independent terminals. Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source or receiver vicinity is considered, thereby broadening the range of applications in real-world environments. Taking into account the local scattering, these CB techniques aim to maintain the beamforming response in the desired direction equal to unity. It is shown that the so-obtained collaborative beamformers are not suitable for a distributed implementation. We hence propose a novel beamformer solution that can be implemented in a distributed fashion and, further, well-approximates both transmit and receive collaborative beam-formers. The performance of the proposed distributed CB (DCB) technique is analyzed and its advantages against the conventional DCB technique, which is designed without taking into account the presence of local scattering in the source or receiver vicinity, are analytically proved and further verified by simulations.

In this paper, we develop a new implementation of maximum likelihood (ML) time delay estimation from direct-sequence CDMA (DS-CDMA) multipath transmissions. The formulation of the problem obtained from the DS-CDMA post-correlation model (PCM) leads to a non-linear likelihood function which is maximized by the iterative expectation maximization (EM) algorithm. In this approach, we avoid eigen-decomposition of the autocorrelation matrix widely used for multiple parameters estimation. Instead, we transpose the problem of multidimensional maximization to simpler one- dimensional maximizations carried out in parallel, thereby reducing the computational cost considerably. We also extend the application of the proposed single-carrier (SC) algorithm to multicarrier (MC)-CDMA systems by exploiting the frequency gain over subcarriers. Simulations suggest that the proposed EM-based algorithm provides accurate estimates even in the challenging case of closely-spaced delays from one transmitted symbol.

This paper derives for the first time the stochastic Cramer-Rao lower bounds (CRLBs) for direction of arrival (DOA) estimates of any linearly-modulated signals, in presence of additive white circular complex Gaussian noise (AWCCGN). The transmitted symbols are assumed to be completely unknown at the receiver side. The channel is slowly time-varying and assumed to introduce a constant distortion phase during the observation interval. Simulation results show that the CRLBs hold almost the same for all the modulation schemes. We also show that, contrarily to uniform lineair array (ULA) systems, the knowledge of the channel distortion phase does not bring any additional information to the achievable performance in uniform circular array (UCA) systems.

Closed-form error analysis of dual-hop fixed-gain amplify-and-forward (AF) relaying systems for transmissions over Nakagami fading channels has, so far, been tractable only with integer fading parameters. For the general Nakagami-m fading with arbitrary m values, the exact closed-form error analysis is more challenging. This paper goes toward solving this problem by deriving a unified error analysis framework that embraces several general modulation schemes. The obtained Error Probability (EP) expressions involve common functions which can be efficiently evaluated using standard numerical softwares. This work represents a significant improvement on previous contributions, not only by unifying the error probability expressions pertaining to dual-hop fixed gain relaying over integer Nakagami-m fading, but also by extending them to the general arbitrary Nakagami-m fading. Simulation results sustaining our analysis are provided, and the impacts of various parameters on the overall AF relaying system performance are investigated.

In this paper, transmit and receive collaborative beamforming (CB) techniques are considered to achieve a dualhop communication from a source to a receiver, through a wireless sensor network (WSN). Whereas the previous works assumed a model of plane wavefronts, here, a local scattering in the source or receiver vicinity is considered, thereby broadening the range of applications in real-world environments. Taking into account the local scattering, these beamformers aim to maintain the beamforming response in the desired direction equal to unity. It is shown that the so-obtained beamformers are not suitable for a distributed implementation in WSNs. We hence propose a novel distributed collaborative beamforming (DCB)technique that can be implemented in a distributed fashion and, further, well-approximates both transmit and receive CB techniques. The performance of the proposed DCB is analyzed and its advantages against the conventional DCB, which is designed without taking into account the presence of local scattering in the source or receiver vicinity, are analytically proved and are further verified by simulations.

We consider a dual-hop cooperative spectrum-sharing system with multiple relays that are available to opportunistically help the secondary communication system. In this primary/secondary cooperative system, we propose using a reactive relay selection (RRS) technique at the secondary system in which the best relay is chosen based on both the first and second hops transmission conditions. In fact, the best relay is selected as the relay node that not only satisfies a minimum required rate on the first-hop transmission, but can also achieve the highest signal-to-noise ratio (SNR) at the destination node. In this context, we first derive an expression for the cumulative distribution function (CDF) of the received SNR at the secondary destination node while assuming that the secondary transmission is limited by the appropriate interference constraints. Then, we use this CDF expression to obtain a closed-form expression for the end-to-end outage probability of the proposed cooperative system. Finally, illustrative numerical examples are shown and the benefits of using the proposed RRS technique in different channel propagation conditions are discussed.

In this paper, we introduce the Inverse Gaussian (IG) fading distribution to model the envelope and the power of the received signal in radio propagation fading channels and free-space optical (FSO) channels. The joint distribution of the IG process and its derivative and the marginal distribution of the derivative are developed. The obtained formulas are then used to derive the second-order statistics of the received signal envelope and the channel capacity under IG and Nakagami-IG (NIG) fading distributions. Numerical results sustaining our analysis are provided, and the impacts of various parameters on the system performance are investigated.

We study three relay selection schemes for uniformly distributed wireless sensor networks: 1) optimal selection where the relays that maximize the signal-to-noise ratio (SNR) at the destination are selected, 2) geometry-based, which is based on selecting the closest nodes to the source, and 3) random selection in which the nodes are selected randomly from a certain neighborhood of the source. In all schemes, we assume that all relays operate in the amplify-and-forward mode and transmit with equal average powers and each relay has only access to its backward channel and location. For each relay selection strategy, we propose a decentralized protocol whereby proper nodes choose to act as relays without requiring any central coordinating entity or any inter-node information transfer. We derive expressions for the average SNR at the relays and destination while assuming that the source-node distances and the inter-terminal channel links are completely random. We show that, for all proposed schemes, the SNR variance at the destination converges to zero as the number of relays increases. While each selection scheme has its pros and cons, we derive a sufficient condition under which the average SNR at the destination becomes independent of the selection scheme employed.

ABSTRACT Three main collaborative beamforming (CB) solutions based on different channel models exist: the optimal CSI‐based CB (OCB), the conventional or monochromatic (i.e., single‐ray) distributed CB (M‐DCB), and the recently developed bichromatic (i.e., two‐ray) distributed CB (B‐DCB). In this paper, we perform an analytical comparison, under practical constraints, between these CB solutions in terms of achieved signal‐to‐noise ratio (SNR) as well as achieved throughput. Assuming the presence of local scattering in the source vicinity and accounting for implementation errors incurred by each CB solution, we derive for the first time closed‐form expressions of their true achieved SNRs. For low angular spread (AS), where both solutions nominally achieve the same SNR in ideal conditions, we show that the B‐DCB always outperforms OCB, more so and at larger regions of AS values when errors increase. Excluding exceptional circumstances of unrealistic low quantization levels (i.e., very large quantization errors) that are hard to justify in practice, we also show that the new B‐DCB always outperforms the M‐DCB as recently found nominally in ideal conditions. This work is also the first to push the performance analysis of CB to the throughput level by taking into account the feedback overhead cost incurred by each solution. We prove both by concordant analysis and simulations that the B‐DCB is able to outperform, even for high AS values, the OCB which is penalized by its prohibitive implementation overhead, especially for a large number of collaborating terminals and/or high Doppler frequencies. Indeed, it is shown that the operational regions in terms of AS values over which the new B‐DCB is favored against OCB in terms of achieved throughput can reach up to 40°. Copyright © 2012 John Wiley & Sons, Ltd.

In this paper we derive a new method of DOA estimation for ULA configurations using the annihilating filter technique. The new method is non-data-aided (NDA) and does not therefore impinge on the whole throughput of the system. The noise components are assumed spatially and temporally white. The transmitted signals are also assumed to be temporally and spatially white (across the transmitting sources). The new method is compared in performance to the root-MUSIC algorithm, a powerful DOA estimation technique for ULA configurations. Simulations will show that the new method performs well over a wide SNR range. The main advantage of the new method is that it succeeds in accurately estimating the DOAs for fast moving sources or for short data snapshots, and even from a single snapshot where the root-MUSIC method fails completely.

In this paper, we propose a joint estimator of the Ricean K-factor and the signal-to-noise ratio (SNR) for singleinput multiple-output (SIMO) systems. The second-order moment and the fourth-order cross-moment matrix of the received signal envelope are used to estimate the desired parameters. The K-factor is estimated using the kurtosis of the Ricean channel gain while the SNR is obtained by separately estimating the powers of the useful signal and the additive noise. Two versions are developed depending on the value of the kurtosis of the transmitted data. Unlike the autocorrelation-based K-factor and SNR joint estimator developed in [1] that is tailored for unmodulated signals, the proposed method applies to any digital modulation and does not request the knowledge of the maximum Doppler spread. Simulation results are included to illustrate the performance behavior of the new estimator.

In this paper, we present a new time delay estimator for multipath environments using the importance sampling (IS) method. The new technique allows finding the maximum of the compressed likelihood function in an efficient manner. The main idea consists in generating realizations of a random variable distributed according to a function that approximates the actual compressed likelihood function and then computing the mean of the plausible realizations. We avoid eigen-decomposition operation that is widely used in the conventional high-resolution methods. We show through computer simulations that the new algorithm provides accurate estimates for closely spaced unknown time delays. Moreover, the method does not suffer from lack of convergence and initialization problems that arise with other iterative implementations of the maximum likelihood estimator.

In this paper, we derive for the first time analytical expressions for the Cramer-Rao lower bounds (CRLBs) of timing recovery estimators from binary phase shift keying (BPSK) and square quadrature amplitude modulation (QAM) transmissions. The bounds are derived in the presence of additive white Gaussian noise (AWGN). Moreover the carrier phase and frequency are considered as unknown nuisance parameters. Our new analytical expressions reveal that the CRLBs do not depend on the corresponding time delay parameter and that they do not change widely from one modulation order to another. They also corroborate previous works that computed them empirically and provide a meaningful tool for their quick and easy evaluation.

We consider a multipoint-to-multipoint cognitive network wherein the communications from L sources to their designated destinations are carried out through the use of K relays in a dual-hop amplify-and-forward cooperative scheme. Aiming to maximize the worst signal-to-interference-plus-noise ratio of the L destinations, we develop a technique that jointly optimizes the sources' transmit powers and the relays' beamforming weights while satisfying the sources and the relays total transmit power constraints as well as the sources individual power constraints and further guaranteeing that the interference powers inflicted from the cognitive network on the M existing primary users are below acceptable thresholds.

We address the problem of direction of arrival (DOA) finding for uniform linear arrays (ULAs). We derive a new and very simple method for estimating the DOA of a single source based on the covariance matrix of the received signal. The new method is non-data-aided (NDA) and does not therefore impinge on the whole throughput of the system. The noise components are assumed spatially and temporally white. The new method is derived in closed form and it exhibits exactly - over a wide practical SNR range - the same performance of the popular root-MUSIC algorithm, a powerful DOA estimation technique for ULA configurations. Therefore, the new estimator offers a way for a rapid and very easy DOA evaluation; making it very attractive for practical implementation as compared to the root-MUSIC algorithm that relies on the heavy operation of eigen decomposition.

Underground narrow-vein mines result in complex indoor scenarios which require sophisticated localization techniques to maintain basic security measures. While some traditional localization systems use the triangulation techniques for outdoor channels, fingerprint positioning techniques are mostly used in more complex indoor environments like mines. One of the techniques exploited in the quasi-curvilinear topology of underground mines is the Channel Impulse Response (CIR) based fingerprint positioning combined with Artificial Neural Networks (ANNs). This article innovates a CIR-based positioning technique within a cooperative memory-assisted approach that exploits both the temporal (from different time instances) and spatial (from different space positions) diversities of the collected fingerprints. Introducing memory-type signatures in a cooperative localization technique within the spatial confinements of the tunnel-shaped narrow-vein mines significantly increases the accuracy, precision and robustness of the localization system. The cooperative memory-assisted technique is capable of localizing a transmitter with an accuracy of less than 25 cm 90% of the time.

International audience

In the mining industry, knowing the position of miners and/or equipments is an important safety measure that reduces risks and improves the security of that facility. Being an indoor environment, wireless transmitted signals in underground narrow-vein mines suffer multiple kinds of distortions due to extreme multipath and non-line of sight (NLOS) conditions. One of the proposed solutions to accurate localization in such challenging environments is based on extracting the channel impulse response (CIR) of the received signal and using the fingerprinting technique combined with cooperative artificial neural networks (ANNs). Such localization systems use the spatial domain where the reference localizing units are implemented at different positions away from the transmitter. In this article, we introduce a localization technique that uses fingerprints successively recorded in time with in-built tracking as an alternative method to localize. Unlike the spatial-domain technique where cooperative localizing units collect memoryless fingerprints from different locations, this technique uses one localizing unit and is capable of estimating the position of a transmitter precisely using its current and previous registered fingerprints in time. Localization using time-domain fingerprinting (i.e., tracking) and ANNs is introduced as a new method that exploits time diversity and improves the accuracy, precision and scalability of the positioning system.

In this paper, we develop for the first time a method of estimating the DOA parameters assuming noncircular and spatially and temporally correlated signals. The new approach is based on the two-sided IV-SSF method (instrumental variable signal with subspace fitting). It will be shown that our newly developed method outperforms the classical two-sided IV-SSF in terms of lower bias and error variance. Its performance improvement increases as the noncircularity rate increases. Moreover, this improvement is more prominent at low SNR values. We also derive for the first time an analytical expression for the stochastic Cramér-Rao bound (CRB) of the DOA estimates from spatially and temporally correlated signals generated from noncircular sources. The new CRB is compared to that of circular and temporally correlated signals. It will be shown that the CRB obtained assuming both noncircular sources and temporally correlated signals is lower than the CRB derived considering only the temporal correlation. This illustrates the potential gain that both the noncircularity and the temporal correlation provide when considered together.

In this paper, we present a new non-data-aided (NDA) maximum likelihood (ML) time delay estimator based on importance sampling (IS). We show that a grid search and lack of convergence from which most iterative estimators suffer can be avoided. It is assumed that the transmitted data are completely unknown at the receiver. Moreover the carrier phase is considered as an unknown nuisance parameter. The time delay remains constant over the observation interval and the received signal is corrupted by additive white Gaussian noise (AWGN). We use importance sampling to find the global maximum of the compressed likelihood function. Based on a global optimization procedure, the main idea of the new estimator is to generate realizations of a random variable using an importance function, which approximates the actual compressed likelihood function. We will see that the algorithm parameters affect the estimation performance and that with an appropriate parameter choice, even over a small observation interval, the time delay can be accurately estimated at far lower computational cost than with classical iterative methods.

Noise statistics estimation is a paramount issue in the design of reliable noise-reduction algorithms. Although significant efforts have been devoted to this problem in the literature, most developed methods so far have focused on the single-channel case. When multiple microphones are used, it is important that the data from all the sensors are optimally combined to achieve judicious updates of the noise statistics and the noise-reduction filter. This contribution is devoted to the development of a practical approach to multichannel noise tracking and reduction. We combine the multichannel speech presence probability (MC-SPP) that we proposed in an earlier contribution with an alternative formulation of the minima-controlled recursive averaging (MCRA) technique that we generalize from the single-channel to the multichannel case. To demonstrate the effectiveness of the proposed MC-SPP and multichannel noise estimator, we integrate them into three variants of the multichannel noise reduction Wiener filter. Experimental results show the advantages of the proposed solution.

In this paper, we derive for the first time analytical expressions for the inphase/quadrature (I/Q) non-data-aided (NDA) Cramér-Rao lower bounds (I/Q NDA CRLBs) of the direction of arrival (DOA) estimates from square quadrature amplitude (QAM)-modulated signals corrupted by additive white circular complex Gaussian noise (AWCCGN) with any antenna configuration. Yet the main contribution embodied by this paper consists in deriving for the first time analytical expressions for the NDA Fisher information matrix (FIM) and then for the stochastic CRLB of the NDA DOA estimates in the case of square QAM-modulated signals. It will be shown that in the presence of any unknown phase offset (i.e., non-coherent estimation), the ultimate achievable performance on the NDA DOA estimates holds almost the same irrespectively of the modulation order. However, the NDA CRLBs obtained in the absence of the phase offset (i.e., coherent estimation) vary, in the high SNR region, from one modulation order to another.

In this paper, infinite integrals involving the product of Bessel functions of different arguments are solved in closed-form. The obtained solutions form a framework for the error probability analysis of wireless amplify and forward (AF) systems with an arbitrary number of variable-gain relays operating over independent but not necessarily identical Nakagami-m fading channels. Here we show that the error probability can be described by generalized hypergeometric functions, namely, Gauss's and Lauricella's multivariate hypergeometric functions. This work represents a significant improvement over previous contributions and extends previous formulas pertaining to dual-hop transmissions over identical Nakagami-m fading channels. Numerical examples show an excellent match between simulation and theoretical results.

In this paper, the quasi-convexity of a sum of quadratic fractions in the form Σi=1n[(1+ci x2)/((1+dix)2)] is demonstrated wherecianddiare strictly positive scalars, when defined on the positive real axis R+. It will be shown that this quasi-convexity guarantees it has a unique local (and hence global) minimum. Indeed, this problem arises when considering the optimization of the weighting coefficient in regularized semi-blind channel identification problem, and more generally, is of interest in other contexts where we combine two different estimation criteria. Note that V. Buchoux have noticed by simulations that the considered function has no local minima except its unique global minimum but this is the first time this result, as well as the quasi-convexity of the function is proved theoretically.

This paper presents an Ultra-Wideband (UWB) computationally-efficient fast acquisition system suggested for ranging in indoor, Line-Of-Sight (LOS) environments. The performance of the proposed scheme is evaluated and its implementation issues are discussed. The design complexity leverages field-programmable gate arrays (FPGA) to implement the parallel processing concept. Timing acquisition at high sampling rates of the ultra-short pulses used in UWB communications can be costly and slow for ranging. This is due to the large number of required operations in an intensive software-based signal processing. The proposed UWB scheme in this paper uses an efficient block-processing technique that simplifies hardware implementation with a greatly reduced number of operations and acquisition time, while also offering accurate ranging capabilities over the considered indoor channel at high levels of multiple-user interference (MUI) and Gaussian noise.

In this paper, we propose a cooperative beamforming (CB) technique for dual-hop amplify-and-forward communication in WSNs with one source, N - 1 interferences, and K relay nodes. First, an optimal beamformer is obtained that maximizes the signal-to-interference-plus-noise ratio at the intended receiver in the far-field subject to the following constraints: 1) The relay nodes total transmit power is bounded; and 2) the received power from the N transmitters at L - 1 unintended receivers in the far-field is zero. It is shown that the optimal beamformer can only be implemented if each relay node knows the locations and the backward channels of all other relay nodes in the network. As this knowledge is not typically available at nodes in WSNs, we use a technique to approximate the optimal beamforming coefficients with quantities that depend only on the locally-available information at each individual relay node. The average beampattern expression of the proposed CB technique is then derived and its properties are analyzed. In particular, it is shown that the average gain of the beamformer linearly increases with K in the direction of the intended receiver while remaining fixed in the directions of the unintended receivers.

We consider a multi-relay amplify-and-forward cooperative communication scheme in wireless sensor networks with uniformly distributed nodes. Fixing the average total transmission power from the network and preserving fairness among the selected relays by constraining them to transmit with equal average powers, we aim to improve the signal reception quality at the far-field receiver by means of a proper choice of the relays. Assuming that the nodes' forward channels are not known, the following three relay selection schemes are proposed and their performances are analyzed. 1) Optimal relay selection scheme that maximizes the average SNR at the receiver by exploiting K nodes with the highest SNRs as relays; 2) geometry-based relay selection scheme that is energy-efficient and achieves a close-to-optimal average SNR performance at the receiver by using K closest nodes to the source as relays; and 3) random relay selection scheme that is energy-efficient and further guarantees a fair usage of all nodes by randomly selecting K relays from a specific area around the source. By minimizing an outage probability, a strategy to determine this area is also proposed. Finally, it is shown for all relay selection schemes that the SNR variance at the receiver converges to zero as K increases.

In this paper, infinite integrals involving the product of Bessel functions of different arguments are solved in closed-form. These solutions provide novel expressions in the error rate analysis for wireless amplify and forward (AF) systems with an arbitrary number of variable-gain relays. Here we show that the error probability can be described by generalized hypergeometric functions, namely Lauricella functions. This work represents a significant improvement on previous contributions and extends previous formulas pertaining to dual-hop transmissions over identical Nakagami-m fading channels. Numerical examples show an excellent match between simulation and theoretical results.

A network with L single-antenna source-destination pairs is considered that uses a half-duplex K-antenna relay to establish the end-to-end links in a dual-hop cooperative communication scheme. The sources share a common channel to concurrently transmit their signals and the relay multiplies its received signal vector with L relaying matrices and then forwards the resulting signal vectors to the destinations in dedicated channels. Under the relay's transmit power constraint at every channel as well as both sources' individual and total power constraints, the jointly optimal sources' powers and the relaying matrices are obtained that maximize the minimum of the normalized signal-to-interference-plus-noise ratios at the destinations. Numerical simulations are then used to verify the analytical results.

The localization process consists in finding the candidate source location that maximizes the synchrony between the properly time-shifted microphone outputs. In addition to using well-known crosscorrelation-based criteria such as the steered response power (SRP), minimum variance (MV), and multichannel crosscorrelation (MCCC), this synchrony can be measured using the averaged magnitude difference function (AMDF) and the averaged magnitude sum function (AMSF) whose calculations involve low computational cost. In this paper, we study the crosscorrelation and AMDF (with AMSF) based approaches using an arbitrary number of microphones. Specifically, we use the eigenanalysis of the parameterized spatial correlation matrix (PSCM) to first provide a unifying study of the most popular crosscorrelation-based techniques. Then, we show the efficiency of the AMDF and AMSF in localizing an acoustic source using multiple microphones by proposing two new parameterized matrices named as the parameterized averaged magnitude difference matrix (PAMDM) and the parameterized averaged magnitude sum matrix (PAMSM). The eigenanalysis of these two matrices reveals new criteria.

We study the linearly constrained minimum variance (LCMV) and the minimum variance distortionless response (MVDR) filters when multiple interferers and unknown (ambient) noise coexist with a target speech signal. Precisely, the LCMV is designed to remove all the interference signals while preserving the desired speech and attempting to reduce the ambient noise components. The MVDR is simply formulated such that the overall ambient-noise-plus-interference are reduced while satisfying a distortionless constraint. We provide simplified expressions for both beamformers and show their relationship. Furthermore, we underline the limitations of the LCMV when the ambient noise is present. When the latter is absent, we also prove that the MVDR degenerates to the LCMV. Numerical examples are provided to support our study.

In this paper we investigate the end-to-end performance of dual-hop fixed gain relaying systems under asymmetric fading conditions. In such conditions, the links associated with the relay network undergo different fading phenomena. In our analysis, the source-relay and the relay-destination links are subject to fading-only or composite multi-path/shadowing environments. An outage analysis of the considered system is performed and the proposed expressions are applicable to general fading and shadowing conditions. Based on the newly derived analytical expressions of the cumulative distribution function (CDF) of the end-to-end signal to noise ratio (SNR), the average bit error probability of arbitrary rectangular QAM modulations is also computed. Some representative numerical examples of the system performance in terms of the above metrics are provided and discussed. For instance, it is confirmed analytically that the relaying system exhibits better performance when the first hop undergoes better channel conditions.

A collaborative receive beamforming technique is proposed that lends itself to a distributed implementation in wireless sensor networks (WSNs). In the first time slot, the transmitter of interest along with several interfering terminals send their signals while in the second time slot K nodes multiply their received signals with properly selected beamforming weights and forward the resulting signals to the receiver. The beamforming weights are selected such that they depend only on the locally-available knowledge at the relaying nodes while aiming to maximize the signal-to-interference-plus-noise ratio (SINR) at the receiver. The beampattern expression is obtained and its analytical properties are studied.

Localizing people in confined and underground areas is one of the topics under research in mining labs and industries. The position of personnel and equipments in areas such as mines is of high importance because it improves industrial safety and security. Due to the special nature of underground environments, signals transmitted in a mine gallery/tunnel suffer from severe multipath effects caused by reflection, refraction, diffraction and collision with humid rough surfaces. In such cases and in cases where the signals are blocked due to the non-line of sight (NLOS) regions, traditional localization techniques based on the RSS, AOA and TOA/TDOA lead to high position estimation errors. One of the proposed solutions to such challenging situations is based on extracting channel impulse response (CIR) fingerprints with reference to one wireless receiver and using an artificial neural network as a matching algorithm to localize. In this article we study this approach in a multiple access network where multiple access points are present. The diversity of the collected fingerprints will allow us to create artificial neural networks that will work separately or cooperatively using the same localization technique. The results will show that using cooperative artificial intelligence in the presence of multiple signatures from different reference points improves significantly the accuracy, precision, scalability and the overall performance of the localization system.

In this paper we investigate the end-to-end performance of dual-hop relaying systems over non identical-Nakagami-m fading channels. Our analysis considers channel state information (CSI-) assisted relays that just amplify and retransmit the information signal also known as "non-regenerative" relays. New closed-form expressions for the average bit error probability (ABEP) are derived. The proposed expressions apply to general operating scenarios with distinct Nakagami-m fading parameters and average signal to noise ratios (SNRs) between the hops. When the fading parameter is an odd multiple of one half, the ABEP is expressed in terms of hypergeometric functions. When m takes any real non integer value, the obtained results involve the fourth Appell's hypergeometric function. For an arbitrary fading parameter, an analysis of such a scheme is performed using the well known moment-based approach.

The parameterized multichannel Wiener filter (PMWF) is known to allow for a flexible tuning of speech distortion and noise reduction. In addition, the output signal-to-noise ratio (SNR) is a natural metric that shows the true effect of such a filter on both residual noise and filtered speech. Earlier contributions have only shown that the output SNR of the Wiener filter is larger than the input SNR (as a proof of its effectiveness). However, the effect of the tuning parameter (denoted as ß following the notation of [1]) on this metric is not yet understood. In this paper, we prove that the global (fullband) output SNR of the PMWF is an increasing function of ß but remains below an asymptotic value. As a byproduct, a very simplified proof of the global output SNR improvement is provided.

Several contributions have been made so far to develop optimalmultichannellinear filtering approaches and show their ability to reduce the acoustic noise. However, there has not been a clearunifying theoreticalanalysis of their performance in terms of both noise reduction and speech distortion. To fill this gap, we analyze the frequency-domain (non-causal) multichannel linear filtering for noise reduction in this paper. For completeness, we consider the noise reduction constrained optimization problem that leads to the parameterized multichannel non-causal Wiener filter (PMWF). Our contribution is fivefold. First, we formally show that the minimum variance distortionless response (MVDR) filter is a particular case of the PMWF by properly formulating the constrained optimization problem of noise reduction. Second, we propose new simplified expressions for the PMWF, the MVDR, and the generalized sidelobe canceller (GSC) that depend on the signals' statistics only. In contrast to earlier works, these expressions are explicitly independent of the channel transfer function ratios. Third, we quantify the theoretical gains and losses in terms of speech distortion and noise reduction when using the PWMF by establishing new simplified closed-form expressions for three performance measures, namely, the signal distortion index, the noise reduction factor (originally proposed in the paper titled ldquoNew insights into the noise reduction Wiener filter,rdquo by J. Chen (IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, no. 4, pp. 1218-1234, Jul. 2006) to analyze the single channel time-domain Wiener filter), and the output signal-to-noise ratio (SNR). Fourth, we analyze the effects of coherent and incoherent noise in addition to the benefits of utilizing multiple microphones. Fifth, we propose a new proof for thea posterioriSNR improvement achieved by the PMWF. Finally, we provide some simulations results to corroborate the findings of this work.

Broadband source localization has several applications ranging from automatic video camera steering to target signal tracking and enhancement through beamforming. Consequently, there has been a considerable amount of effort to develop reliable methods for accurate localization over the last few decades. Essentially, the localization process consists in finding the candidate source location that maximizes the synchrony between the properly time-shifted microphone outputs. In addition to using well known cross-correlation-based criteria such as the steered response power (SRP), minimum variance (MV), and multichannel cross-correlation (MCCC), this synchrony can also be measured using the averaged magnitude difference function (AMDF) and the averaged magnitude sum function (AMSF) whose calculations involve low computational cost. In earlier related works, the latter techniques have been used for time delay estimation (TDE) of a target source observed by only one pair of microphones. Their generalization to the multiple microphone case and application to source localization have not been studied yet. In this paper, we consider both categories, i.e., cross-correlation and AMDF (with AMSF)-based approaches, using an arbitrary number of microphones, and analyze their performance. Specifically, we first provide a unifying study of the most popular cross-correlation-based techniques, such as the SRP, MV, and MCCC. In this paper, we use the eigenanalysis of the parameterized spatial correlation matrix (PSCM) to classify these methods and gain some insight into their performance. We demonstrate, for instance, that the MV and SRP consist in searching the major eigenvalue of the PSCM, while the MCCC, essentially, combines its minor eigenvalues when scanning for the source location. Inspired by this analysis, we show, in the second part of this work, the efficiency of the AMDF and AMSF in localizing an acoustic source using multiple microphones. Indeed, we propose two new parameterized matrices named as the parameterized averaged magnitude difference matrix (PAMDM) and the parameterized averaged magnitude sum matrix (PAMSM). The eigenanalysis of these matrices also reveals new criteria for acoustic source localization. Simulation results are provided to illustrate the effectiveness of all the investigated and proposed methods.

The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications including reliable noise reduction algorithms. In this correspondence, we establish a new expression for speech presence probability when an array of microphones with an arbitrary geometry is used. Our study is based on the assumption of the Gaussian statistical model for all signals and involves the noise and noisy data statistics only. In comparison with the single-channel case, the new proposed multichannel approach can significantly increase the detection accuracy. In particular, when the additive noise is spatially coherent, perfect speech presence detection is theoretically possible, while when the noise is spatially white, a coherent summation of speech components is performed to allow for enhanced speech presence probability estimation.

In this paper, we derive for the first time analytical expressions for the exact Cramér-Rao lower bounds on the variance of unbiased non-data-aided (NDA) signal-to-noise ratio (SNR) estimators of square QAM-modulated signals. The channel is assumed to be constant over the observation interval and the received signal is supposed to be corrupted by additive white Gaussian noise (AWGN). The derived expressions corroborate previous attempts to numerically compute the considered CRLBs. It will be shown that the NDA CRLBs differ widely from one modulation order to another especially at moderate SNR levels.

In this contribution an accurate average Bit Error Rate (BER) formula is derived for MC-DS-CDMA in the context of asynchronous transmissions and random spreading sequences. We consider a flat Nakagami-m fading channel for each subcarrier. Our analysis is based on the Characteristic Function (CF) and does not rely on any assumption concerning the statistical behavior of the interference. We develop a new closed-form expression for the conditional CF of the inter-carrier interference and provide a procedure for calculating the exact BER expressed in the form of a single numerical integration. The accuracy of the Standard Gaussian Approximation (SGA) technique is also evaluated. Link-level results confirm the accuracy of the SGA for most practical conditions.

In this paper, we develop a new method for signal-to-noise ratio (SNR) estimation when multiple antenna elements receive linearly-modulated signals in complex additive white Gaussian noise (AWGN) spatially uncorrelated between the antenna elements. We also derive extensions of other existing moment-based SNR estimators to the single-input multiple-output (SIMO) configuration. The new SIMO SNR estimation technique is non-data-aided (NDA) since it is a moment-based method and does not rely, therefore, on the a priori knowledge or detection of the transmitted symbols; it does not require the a priori knowledge of the modulation type or order. The new method is shown by Monte Carlo simulations to clearly outperform the best NDA moment-based SNR estimation methods in terms of normalized root mean square error (NRMSE) over QAM-modulated transmissions, namely the M2M4method and the estimators referred to, in this paper, as the GT and the M6methods, even when we extend them to the SIMO configuration.

In this paper, we derive analytical expressions for the exact Cramer-Rao lower bounds (CRLBs) for the joint estimation of the carrier frequency, the carrier phase, the noise power and the signal amplitude of square quadrature amplitude (QAM) modulated signals. The channel is assumed to be slowly timevarying so that it can be assumed constant over the observation interval. The signal is assumed to be corrupted by additive white Gaussian noise (AWGN). The closed-form expressions for the corresponding modified Cramer-Rao lower bounds (MCRLBs) are also derived in this paper.

This paper addresses the stochastic Cramer-Rao lower bound (CRLB) for the non-data-aided (NDA) direction of arrival (DOA) estimation of square quadrature amplitude (QAM)-modulated signals when the transmitted symbols are supposed to be completely unknown to the receiver. These signals are assumed to be corrupted by additive white circular complex Gaussian noise (AWCCGN). The channel is supposed to be slowly time-varying so that it can be assumed constant over the observation interval. The main contribution of this paper consists in deriving an explicit expression for the Fisher information matrix (FIM) in the case of a single square QAM modulated waveform and an analytical expression for the stochastic CRLB of the NDA DOA estimates. It will be shown that the achievable performance on the DOA estimates hold almost the same irrespectively of the modulation order.

In this paper, we address the problem of non-data-aided SNR estimation in wireless SIMO channels. We derive the per-antenna ML SNR estimator using the expectation-maximization (EM) algorithm under constant channels and additive white Gaussian noise (AWGN). The new method is valid for any arbitrary constellation. It is NDA and, therefore, does not impinge on the hole throughput of the system. We obtain two non linear vector equations which are tackled by a less complex approach based on the EM algorithm. The noise components are assumed to be spatially uncorrelated over all the antenna elements and temporally white with equal power. Besides, in order to evaluate our EM-ML SNR estimator, we derive the Cramer-Rao lower bound (CRLB) in the DA case. Monte Carlo simulations show, that our new estimator offers, a substantial performance improvement over the SISO ML SNR estimator due to the optimal usage of the mutual information between the antenna branches, and that it reaches the derived DA CRLBs. To the best of our knowledge, we are the first to derive the ML per-antenna SNR estimators as well as the CRLBs in the NDA and the DA case, respectively, both over SIMO channels.

A novel distribution referred to as N*generalized K, constructed as the product of N statistically independent, but not necessarily identically distributed, generalized K random variables (RVs) is introduced. Statistical characterization of the proposed distribution is carried out via the derivation of closed-form expressions for its moment generating, probability density, cumulative distribution and moment functions. Using the obtained formulas, we present new closed-form expressions for the outage probability, the bit error probability and the average channel capacity of a digital communication system operating over the N cascaded generalized K distributed channels.

Null-steering transmit beamformers aim to maximize the received signal power at the direction of the access point (AP) while inflicting minimal interfering effect on unintended receivers. However, existing null-steering beamformers may not be directly applied to wireless sensor networks (WSNs) as they require every node to be aware of the locations of other nodes in the network. In this paper, a novel null-steering beamformer is introduced that can be implemented in uniformly distributed WSNs in which each node is oblivious of other nodes' locations. The average beampattern expression of the proposed beamformer is derived and its properties are analytically studied. In particular, it is shown that the average beampattern of the proposed beamformer is similar to that of the conventional beamformer in directions with far angular distance from any unintended receiver. The analytical results are also adopted to design a null-steering beamformer with a single null and required average beampattern properties. The optimal null position is obtained which minimizes the maximum sidelobe of the average beampattern while having negligible deteriorating effect on the received power at the AP. Finally, computer simulations are used to validate the analytical results as well as to confirm the effectiveness of the design approach.

We investigate a general framework for noise reduction which consists in controlling the level of signal distortion while reducing the level of noise. A parameterized non-causal filter that allows for tuning the signal distortion and noise reduction inversely is obtained and is referred to as parameterized multichannel non-causal Wiener filter (PMWF) herein. The same optimization problem leads to the minimum variance distortionless response (MVDR) as a particular case of the PMWF. In contrast to earlier works, the proposed expressions of the PMWF and MVDR are simplified and require the knowledge of the speech and noise statistics only. To rigorously quantify the gains and losses when using these filters, we establish simplified closed-form expressions for three measures, namely, the signal distortion index, the noise reduction factor, and the output signal-to-noise ratio (SNR), and highlight the tradeoff between noise reduction and speech distortion in the multichannel case.

Due to the unsupervised nature of wireless sensor networks (WSNs), intensive communications are required among the selected nodes to reach a consensus and synchronize prior to entering a distributed beamforming (DBF) procedure. Therefore, a sensible approach to select the nodes should not only take into account the required beampattern, but also should aim to preserve the inter-node connectivity and the network energy. We show for a uniformly distributed WSN that when the nodes are selected from a ring of proper radii, the resulting beampattern mainlobe is narrower compared to that of the classical DBF technique proposed in [1]. At the same time, our proposed technique may preserve a substantial amount of network energy and reduce the probability of network disconnectivity. Directivity of the proposed DBF technique is analyzed and an extension of the technique to a multi-ring case is presented. It is shown that the sidelobe peaks can be considerably decreased if the nodes are selected from multiple concentric rings.

This paper addresses the issue of the optimization of the regularization constant in semi-blind channel estimation techniques, in which the training sequence-based criterion is combined linearly with the blind subspace criterion. In such semi-blind estimation techniques, the optimization of the regularizing constant with respect to the channel estimation error is mandatory, otherwise, the expected improvement in performance could not be achieved. In this context, recent works proposed numerical methods for the setting of the regularization constant. However, these methods are often sub-optimum and involve high computational complexities. In this paper, we propose to optimize with respect to a regularizing matrix instead of a regularizing scalar. We prove that interestingly in this case, a closed-form expression for the optimum regularizing matrix exists, thereby avoiding iterative algorithms as for the conventional techniques. We also prove that the obtained scheme has slightly better performance in terms of mean square error and bit error rate while ensuring lower complexity.

The performance of a cooperative multiuser direct-sequence code-division multiple-access (DS-CDMA) system is analyzed in the asymptotic regime where both the spreading codes and the number of users grow large with the same ratio. A simple signal-to-interference-plus-noise ratio (SINR) expression is derived that is independent from the spreading codes and explicitly accounts for the effects of the multiple-access interference (MAI) and the relay noise. The so-obtained SINR expression is then computed based entirely on the available local information. The results obtained above are then used to optimally design the cooperative system. In particular, it is shown how the amount of cooperation between each collaborating pair can be adjusted to simultaneously achieve a pre-assigned target SINR for both users. Based on the local information, the globally optimal amount of the relay power is also obtained that maximizes the achieved SINR at the access point.

In this paper, considering a multicarrier transmissions system, we propose two techniques of maximum-likelihood (ML) subcarrier signal-to-noise ratio (SNR) estimation, in both data-aided (DA) and non-data-aided (NDA) schemes, and derive the corresponding Crame¿r-Rao lower bounds (CRLBs). The channel gains and phases are assumed to be constant over the observation window and the received signal is assumed to be corrupted by additive white Gaussian noise (AWGN). The proposed SNR estimators both exploit the mutual information between the different subcarriers and reach the corresponding CRLBs, as shown by Monte-Carlo simulations.

Considering orthogonal frequency division multiplexing (OFDM) transmissions, we derive analytical expressions for the Cramer-Rao bounds for the subcarrier signal-to-noise ratio (SNR) estimates. The channel coefficients of the different subcarriers are assumed to be constant over the observation interval and the received signal is assumed to be corrupted by additive white Gaussian noise (AWGN). We will show that exploiting the mutual information between the different tones improves the achievable performance of subcarrier SNR estimators.

In this paper, we derive analytical expressions for the inphase/quadrature Cramer-Rao lower bounds (I/Q CRLB) for the non-data-aided (NDA) signal-to-noise ratio (SNR) estimation of square quadrature amplitude modulated (QAM) signals. The channel is supposed to be slowly time-varying so that it can be assumed constant over the observation interval. The signal is assumed to be corrupted by additive white Gaussian noise (AWGN). We will demonstrate that the shape of the bounds differs greatly as the modulation order changes.

This paper presents an outage analysis of wireless systems operating in gamma-shadowed Nakagami-faded environments where the desired signal also suffers from co-channel interference. The interfering signals are also subject to fading and shadowing. Based on the obtained signal to interference ratio (SIR) probability density function (pdf), closed- form expressions for the outage probability are obtained in both cases of statistically identical interferers and multiple interferers with different parameters. The effects on the aforementioned performance metric of the reuse distance and of the combined fading, shadowing and co-channel interference are analyzed subsequently. The newly derived closed-form expressions for the outage probability allow as to assess the effects of the different channel and interference parameters easily.

The relay selection problem in a large wireless sensor network (WSN) with uniformly distributed identical nodes is investigated for a two-phase cooperative protocol where the signal transmitted from a single source is overheard by the network and is then relayed by multiple selected nodes subject to a total average transmission power. First, a relay selection technique is considered that maximizes the average signal-to-noise ratio (SNR) at the access point (AC) while is applicable to a distributed WSN where only a limited information is available to the nodes. As this technique is shown to be energy inefficient, two other alternative relay selection techniques are also presented that substantially reduce the energy consumption of the network. One of these alternative techniques takes advantage of the static nature of the network topology and, as verified by simulations, achieves near-optimal SNR performance, while the other one randomly selects the relays from a neighborhood around the source and further guarantees a fair power consumption among the nodes at the cost of possible SNR performance drop at AC. Accounting for the randomness of the nodes locations as well as the inter-terminal fading channel coefficients, the SNR performances of the energy efficient relay selection schemes are analyzed and a condition is derived under which the average SNR at AC is independent from the technique used to select the relaying nodes. This condition clarifies when the energy efficient and fair random relay selection scheme may be used without compromising the quality of the received signal at AC.

The removal of noise and interference from an array of received signals is a most fundamental problem in signal processing research. To date, many well-known solutions based on second-order statistics (SOS) have been proposed. This paper views the signal enhancement problem as one of maximizing the mutual information between the source signal and array output. It is shown that if the signal and noise are Gaussian, the maximum mutual information estimation (MMIE) solution is not unique but consists of an infinite set of solutions which encompass the SOS-based optimal filters. The application of the MMIE principle to Laplacian signals is then examined by considering the important problem of estimating a speech signal from a set of noisy observations. It is revealed that while speech (well modeled by a Laplacian distribution) possesses higher order statistics (HOS), the well-known SOS-based optimal filters maximize the Laplacian mutual information as well; that is, the Laplacian mutual information differs from the Gaussian mutual information by a single term whose dependence on the beamforming weights is negligible. Simulation results verify these findings.

Composite multipath fading/shadowing environments are frequently encountered in different realistic scenarios. These channels are generally modeled as a mixture of Nakagami-m multipath fading and log-normal shadowing. The resulting composite probability density function (pdf) is not available in closed form, thereby making the performance evaluation of communication links in these channels cumbersome. In this paper, we propose to model composite channels by the G-distribution. This pdf arises when the log-normal shadowing is substituted by the inverse-Gaussian one. This substitution will prove to be very accurate for several shadowing conditions. In this paper we conduct a performance evaluation of single-user communication systems operating in a composite channel. Our study starts by deriving an analytical expression for the outage probability. Then, we derive the moment generating function of the G-distribution, hence facilitating the calculation of average bit error probabilities. We also derive analytical expressions for the channel capacity for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate.

In this letter we provide an analytical expression for the moments of the capacity for the log-normal fading channel. Since the developed expression involves infinite series, we show that the error that results from the truncation of these series is insignificant. We also analyze in more details the ergodic capacity by giving a simpler expression for the remainder of the truncated series. Relying on the fact that the sum of log-normal random variables (RV) is well approximated by another lognormal RV, we further utilize the obtained results to approximate the capacity of diversity combining techniques in correlated lognormal fading channels. The results that we provide in this letter are an important tool for measuring the performance of communication links in a log-normal environment.

This paper presents an analytical framework for performance evaluation of mobile radio systems operating in composite fading/shadowing channels in the presence of colocated co-channel interference. The desired user and the interferers are subject to Nakagami fading superimposed on gamma shadowing. The paper starts by presenting generic closed-form expressions for the signal-to-interference ratio (SIR) probability density function (pdf). From this pdf, closed-form expressions for the outage probability, the average bit error rate and the channel capacity are obtained in both cases of statistically identical interferers and multiple interferers with different parameters. The newly derived closed-form expressions of the aforementioned metrics allow us to easily assess the effects of the different channel and interference parameters. It turns out that the system performance metrics are predominantly affected by the fading parameters of the desired user, rather than by the fading parameters of the interferers.

Abstract In this paper, we address the issue of multi‐user receiver design in realistic multi‐cellular and multi‐rate CDMA systems based on performance analysis. We consider the multi‐user detection (MUD) technique, denoted interference subspace rejection (ISR), because it offers a wide range of canonic suppression modes that range in performance and complexity between interference cancellers and linear receivers. To further broaden our study, we propose a modified ISR scheme called hybrid ISR to cope better with multi‐rate transmissions. The performance analysis, which is based on the Gaussian assumption (GA) and validated by simulations, takes into account data estimation errors, carrier frequency mismatch, imperfect power control, identification errors of time‐varying multipath Rayleigh channels and intercell interference. This analysis enables us to optimize the selection of the MUD mode for multi‐rate transmissions in different operating conditions. The effectiveness of interference cancellation is indeed investigated under different mobile speeds, numbers of receiving antennas, near‐far situations, channel estimation errors, and out‐cell to in‐cell interference ratios. This investigation suggests that the out‐of‐cell interference, the residual in‐cell interference, the noise enhancement as well as low mobility favor the simplest MUD modes as they offer the best performance/complexity tradeoffs. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper, we consider composite multipath/shadowing fading channels characterized by Nakagami- m fading with inverse Gaussian shadowing, and Rice fading with inverse Gaussian shadowing. These channel models are very convenient for land mobile satellite systems and communications with low mobility or stationary users. From an analytical standpoint, one major advantage of these models is that they lead to closed-from expressions for the envelope probability density function (pdf) and the cumulative density function (CDF). Moreover, in this paper, we derive mathematically tractable new expressions for fundamental channel statistics such as the level crossing rate (LCR) and the average fade duration (AFD). Also, we validate our analytical results by providing several numerical examples showing the LCR and the AFD as a function of the Nakagami-m factor, Rice factor, and shadowing spread.

The acoustic source localization problem has significance for modern intelligent communication systems and future human-computer interaction applications. Although steered-beamforming localization methods perform well in adverse conditions, the algorithms are inherently computationally burdensome due to their need to search the entire location space. This paper presents a computationally- reduced version of the steered response power (SRP) method. The proposed approach is rooted in the inverse mapping of relative delays to candidate source locations, which allows for the transformation of the iterative search from the multidimensional location space to the one-dimensional relative delay space. By subsetting the set of traversed relative delays to only those that experience a high-level of cross-correlation, the computational load is reduced by up to 90 % without incurring a loss in localization accuracy.

We propose a new method for noise reduction using a microphone array. The method takes advantage of the spatial diversity inherent to microphone arrays and optimizes certain criteria, namely, the output signal to noise ratio (SNR) or the mean squared error (MSE), subject to the constraint of spatial prediction that relates the noise free signals captured by the microphones. Simulation results demonstrate that resorting to this new method leads to high rate of noise reduction and low signal distortion.

A major application of wireless communications in confined indoor areas is positioning. Ultra-wideband (UWB) has been recently promoted as a very promising physical support for such use. However, fast and accurate timing acquisition of the ultra-short pulses transmitted in indoor environments is significantly challenging, and even more so in hostile areas such as underground mines. This paper presents an UWB fast acquisition system proposed for positioning in an underground mining environment. The parameters of the proposed UWB acquisition system are detailed and its effectiveness is confirmed by computer simulations.

Composite multipath/shadowing fading environments are frequently encountered in different realistic scenarios. These channels are generally modeled as a mixture of Nakagami- m multipath fading and log-normal shadowing. The resulting composite probability density function (pdf) is unfortunately not in closed-form, thereby making the performance evaluation of communication links in these channels cumbersome. In this paper, we propose to model composite channels by the very general G-distribution. This pdf arises when the log-normal shadowing is substituted by the Inverse-Gaussian one. This substitution will prove to be very accurate for several shadowing conditions. In this paper we conduct an exhaustive performance evaluation of communication systems operating in these channels. Our study starts by deriving a closed-form expression for the outage probability. Then, we derive the moment generating function of the G-distribution, hence facilitating the calculation of average bit error probabilities. We also derive closed-form expressions for the channel capacity for three adaptive transmission techniques, namely, (i) optimal rate adaptation with constant power, (ii) optimal power and rate adaptation, and (iii) channel inversion with fixed rate. The different expressions that will be provided are of great importance in assessing the performance of communication systems in composite channels.

Tremendous effort was previously made to estimate the location of moving sources with large angular velocities. However, to the best of our knowledge, no previous work has thoroughly investigated the effect of the combined angular velocity and mobile speed on the spectrum of the signal received by an antenna-array. In this contribution, we address this issue in the particular context of wideband CDMA transmission. We first show both by theoretical development and by simulations that the maximum frequency shift is the sum of the conventional Doppler term and a new term due to angular speed and that it is a linear function of both. We also show that the additional frequency shift due to the angular speed increases channel identification errors and thereby degrades the performance of antenna-array receivers. This performance loss becomes even higher at a larger number of antennas in the array.

In this paper, we propose a novel frequency scheduling strategy for an OFDM switched-beam system. We deal with dynamic frequency allocation based on the distance of the user from the serving base station (BS) or on the power of the channel response received by the user. The key idea is to reduce the interference among the neighboring cells. To do so, we consider a time-space-frequency allocation scheme where users are assigned with the appropriate set of subcarriers according to their serving beam at any given time. We evaluate the performance of the proposed frequency allocation scheme when Kalman filtering is used for joint channel estimation and beam selection. A system-level simulator is developed which computes the signal to interference ratio (SIR) for a reference mobile user with different resource allocation strategies. Previously obtained link-level throughput vs. signal to noise ratio (SNR) results are then translated into a system-level cumulative distribution function (cdf) of the user throughput. Link-level frame error rate (FER) results suggest that the proposed Kalman-based OFDM switched-beam system offers high performance over slow fading channels. System-level SIR results show that the proposed frequency scheduling scheme reduces significantly the interference. Our scheme enhances the system throughput compared to other allocation schemes.

This paper focuses on the problem of angular spread (AS) estimation at the base station in a macro-cellular system when a line-of-sight (LOS) component is potentially present. We will limit our study to low-complexity methods prone to practical implementation. The paper demonstrates the limitations of the well-known low complexity AS estimation method, spread root-MUSIC. As supported by simulations, it introduces a lower complexity "look-up table" (LUT) based approach that compares advantageously with spread root-MUSIC from the point of view of complexity and performance.

In this contribution an accurate average bit error rate (BER) formula is derived for Nakagami-faded MC-DS-CDMA in the context of asynchronous transmissions and random spreading sequences. Our analysis is based on the Characteristic Function (CF) and does not rely on any assumption concerning the statistical behavior of the interference. We develop a new closed-form expression for the conditional CF of the inter-carrier interference and provide a procedure for calculating the exact BER expressed in the form of a single numerical integration. The accuracy of the standard Gaussian approximation (SGA) technique is also evaluated. Link-level results confirm the accuracy of the SGA for most practical conditions.

A signal's spectrum is a representation of the signal in terms of elementary basis functions which facilitates the extraction of desired information. For a temporal signal, the spectrum is one-dimensional and expresses the time-domain signal as a linear combination of sinusoidal basis functions. A space-time signal possesses a multidimensional Fourier transform known as the wavenumber-frequency spectrum, which represents the space-time signal as a weighted summation of monochromatic plane waves. The spatial and temporal frequencies are not separable, as spatial frequency is itself a function of the temporal frequency. Thus, it seems natural to analyze and estimate the spatial and temporal frequency components in tandem. It is therefore surprising that conventional spectral estimation methods focus on either the spatial or temporal dimension, without any regard for the other. Spatial spectral estimation is commonly referred to as source localization, as the direction of the wavenumber vector is indeed the direction of propagation. Conventional methods analyze a solely spatial aperture without accounting for the temporal structure of the desired signal. Conversely, temporal spectral estimation is performed using a single sensor, and thus the signal aperture is purely temporal. This paper proposes a spatiotemporal framework for spectral estimation based on the linearly constrained minimum variance (LCMV) beamforming method proposed by Frost in 1972. The aperture consists of an array of sensors, each storing a set of previous temporal samples. It is first shown that by taking into account the temporal structure of the desired signal, the ensuing source location estimate is more robust to the effects of noise and reverberation. Unlike conventional localizers, the LCMV steered beamtemporallyfocuses the array onto the desired signal. The desired signal is modeled by an autoregressive (AR) process, and the resulting AR coefficients are embedded in the linear constraints. As a result, the rate of anomalous estimates is significantly reduced as compared to existing techniques. Moreover, it is then demonstrated that by employing multiple sensors and steering the array to the assumed source location, the estimate of the desired signal's temporal spectrum contains a lesser contribution from the unwanted noise and reverberation.

This paper presents a new adaptive antenna-array beamforming receiver for multipath correlated signals in hostile environments, such as indoor confined or underground areas, where intersymbol interference (ISI) and intrasymbol interference (isi) are predominant. The proposed receiver uses a new synchronization approach for multipath propagation and is based on sequential blind CMA and nested LMS beamformings with adaptive fractional-time-delay estimation. This approach uses on one hand CMA and LMS to recover any time path arrival (TPA) that is an integer multiple of the sampling interval, and nested adaptive fractional time delay estimation with LMS on the other hand to recover any TPA that is a non-integer multiple of the sampling interval. Coherent Maximum Ratio Combining (MRC) with hard Decision Feedback Identification (DPI) is also proposed for optimal and constructive combination of these different extracted paths. Analysis and results show the promising performance of the new adaptive antenna-array structure for different operating conditions and modulation schemes.

This letter investigates the capacity of generalized-k fading channels. This very general model describes accurately composite multipath/shaodwing fading channels which are widely encountered in real-world environments. We derive closed-form expressions for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate. The analytical expressions obtained match perfectly the results obtained by computer simulations. These expressions provide a good tool to assess the spectral efficiency of the aforementioned adaptive transmission techniques over composite channels.

This paper investigates the capacity of generalized- K fading channels. This very general model describes accurately composite multipath/shadowing fading channels which are widely encountered in real-world environments. We derive closed-form expressions for three adaptive transmission techniques, namely, i) optimal rate adaptation with constant power, ii) optimal power and rate adaptation, and iii) channel inversion with fixed rate. The analytical expressions obtained match perfectly the results obtained by computer simulations. These expressions provide a good tool to assess the spectral efficiency of the aforementioned adaptive transmission techniques over composite channels.

In this paper, we consider a pulse shaping OFDM/BFDM system operating over a doubly dispersive channel. We propose to search the optimal pulse maximizing the signal to interference ratio (SIR). We show that the impact of interference, composed by both inter-symbol interference (ISI) and inter-carrier interference (ICI), occurring in such a system, depends crucially on time frequency localization of transmit and receive pulses. We propose to maximize the SIR, written as a ratio of two quaternary forms, by altering between transmit and receive pulse spaces both generated by Hermite Waveforms. Numerical results show that optimized BFDM systems can outperform conventional OFDM systems with respect to SIR. In fact, biorthogonality offers more freedom to design pulses improving robustness of the multi-carrier system against channel dispersion.

The estimation of the direction-of-arrival (DOA) of one or more acoustic sources is an area that has generated much interest in recent years, with applications like automatic video camera steering and multi-party stereophonic teleconferencing entering the market. Time-difference-of-arrival (TDOA) based methods compute each relative delay using only two microphones, even though additional microphones are usually available, and thus suffer from the effects of background noise and reverberation. This paper deals with DOA estimation based on spatial spectral estimation, and proposes a novel DOA estimator based on the eigenvalues of the parameterized spatial correlation matrix. Simulation results confirm the ability of the proposed method to provide reliable estimates even in heavily reverberant environments.

This paper investigates the capacity of log-normal fading channels with receiver channel state information. We provide a closed-form expression for the ergodic capacity of the log-normal fading channel. Since the developed expression involves an infinite series, we show that the error that results from the truncation of this series is insignificant. Relying on the fact that the sum of log-normal Random Variables (RV) is well approximated by another log-normal RV, we further apply the obtained results to find the capacity of correlated log-normal fading channels with Maximum Ratio Combining and Equal Gain Combining. The analytical expressions obtained match perfectly the capacity given by simulations.

Ultra-wideband (UWB) has been recently promoted as a very promising technology for wireless communications. Rapid and accurate timing acquisition of ultra-short pulses and the high sampling rates create challenges for both signal acquisition and the overall UWB transceiver implementation, and even more so under non-ideal conditions. In this paper, we evaluate the performance of a computationally-efficient implementation of a DS-UWB acquisition scheme. The suggested rapid acquisition system based on a block-processing technique adapted to a circular frequency domain correlation, shows explicit design characteristics that offer greatly improved acquisition time, accuracy and implementation cost, while also yielding very satisfactory performance at high noise and MAI levels.

This paper investigates non-data-aided (NDA) SNR estimation for QAM transmission over additive white Gaussian noise channels. It proposes a novel class of moment-based SNR estimators. This class is found to be a generalization of the well-known moment-based M2M4 SNR estimation method for PSK modulation. The performance of the proposed estimators is evaluated for M-PSK and rectangular 16-QAM modulation.

This letter proposes a new data-aided carrier frequency offset (CFO) estimation scheme for orthogonal frequency division multiplexing (OFDM) communications suitable for frequency-selective channels. The proposed method is based on the transmission of a specially designed synchronization symbol that generates a particular signal structure between the received observation samples at the receiver. This structure is exploited to derive a closed-form expression of the CFO. The proposed solution offers a wide acquisition range with reduced computational load. Simulations over frequency-selective channels confirm the superiority of the proposed method compared to recent data-aided synchronization algorithms

The estimation of the direction-of-arrival (DOA) of one or more acoustic sources is an area that has generated much interest in recent years, with applications like automatic video camera steering and multiparty stereophonic teleconferencing entering the market. DOA estimation algorithms are hindered by the effects of background noise and reverberation. Methods based on the time-differences-of-arrival (TDOA) are commonly used to determine the azimuth angle of arrival of an acoustic source. TDOA-based methods compute each relative delay using only two microphones, even though additional microphones are usually available. This paper deals with DOA estimation based on spatial spectral estimation, and establishes the parameterized spatial correlation matrix as the framework for this class of DOA estimators. This matrix jointly takes into account all pairs of microphones, and is at the heart of several broadband spatial spectral estimators, including steered-response power (SRP) algorithms. This paper reviews and evaluates these broadband spatial spectral estimators, comparing their performance to TDOA-based locators. In addition, an eigenanalysis of the parameterized spatial correlation matrix is performed and reveals that such analysis allows one to estimate the channel attenuation from factors such as uncalibrated microphones. This estimate generalizes the broadband minimum variance spatial spectral estimator to more general signal models. A DOA estimator based on the multichannel cross correlation coefficient (MCCC) is also proposed. The performance of all proposed algorithms is included in the evaluation. It is shown that adding extra microphones helps combat the effects of background noise and reverberation. Furthermore, the link between accurate spatial spectral estimation and corresponding DOA estimation is investigated. The application of the minimum variance and MCCC methods to the spatial spectral estimation problem leads to better resolution than that of the commonly used fixed-weighted SRP spectrum. However, this increased spatial spectral resolution does not always translate to more accurate DOA estimation.

The process of locating an acoustic source given measurements of the sound field at multiple microphones is of significant interest as both a classical array signal processing problem, and more recently, as a solution to the problems of automatic camera steering, teleconferencing, hands-free processing, and others. Despite the proven efficacy of steered-beamformer approaches to localization in harsh conditions, their practical application to real-time settings is hindered by undesirably high computational demands. This paper presents a computationally viable implementation of the steered response power (SRP) source localization method. The conventional approach is generalized by introducing an inverse mapping that maps relative delays to sets of candidate locations. Instead of traversing the three-dimensional location space, the one-dimensional relative delay space is traversed; at each lag, all locations which are inverse mapped by that delay are updated. This means that the computation of the SRP map is no longer performed sequentially in space. Most importantly, by subsetting the space of relative delays to only those that achieve a high level of cross-correlation, the required number of algorithm updates is drastically reduced without compromising localization accuracy. The generalization is scalable in the sense that the level of subsetting is an algorithm parameter. It is shown that this generalization may be viewed as a spatial decomposition of the SRP energy map into weighted basis functions-in this context, it becomes evident that the full SRP search considers all basis functions (even the ones with very low weighting). On the other hand, it is shown that by only including a few basis functions per microphone pair, the SRP map is quite accurately represented. As a result, in a real environment, the proposed generalization achieves virtually the same anomaly rate as the full SRP search while only performing 10% the amount of algorithm updates as the full search.

This paper proposes a spectrum-efficient spatio-temporal array-receiver for multi-carrier CDMA systems named MC-STAR. First, we derive a new post-correlation model for MC-CDMA that characterizes the structure of the channel in space, time and frequency. Based on this model, we introduce a new multi-carrier array-receiver with rapid and accurate joint synchronization in time and frequency. There, we exploit jointly the spatial, temporal and frequency diversities as well as the intrinsic inter-carrier correlation (termed hereafter frequency gain) to improve the channel identification and the synchronization operations. In addition, based on a new link/system-level performance analysis, with a band-limited chip waveform assumption, we provide a comparative performance study of MC-STAR over two multi-carrier CDMA air-interface configurations, namely MT-CDMA and MC-DS-CDMA, in the most realistic operating conditions. Link/system-level results confirm the advantages of MT-CDMA in increasing throughput and bandwidth efficiency. The current trend is to design radio air-interfaces with flat fading subcarriers. In contrast, with MC-STAR we show that the positive effects of multipath diversity and frequency gain over large strongly-overlapping subcarriers is more significant than the negative effects of multipath and multi-carrier interference.

This article addresses a new topic in OFDM with switched-beam systems, which is the exploitation of the OFDM symbols' structure to jointly perform the beam selection and channel estimation. Unlike previous works which were based on the symmetry of the channel to select the serving beam from the uplink of a MISO/MIMO system, our approach deals with the MISO downlink where the selection process is controlled at the mobile level. The method is based on the use of Kalman filtering with very spectrum-efficient overlapping pilots to separate the beams.

In a harsh indoor environment, fingerprinting geolocation techniques perform better than the traditional ones, based on triangulation, because multipath is used as constructive information. However, this is generally true in static environments as fingerprinting techniques suffer degradations in location accuracy in dynamic environments where the properties of the channel change in time. This is due to the fact that the technique needs a new database collection when a change of the channel's state occurs. In this paper, a novel solution based on a hierarchy of artificial neural networks (ANNs) is proposed to enhance such a geolocation system. It is shown that the enhanced system detects the change in the channel's properties via geolocation reference points, identifies the new channel state and activates a new database that best represents the current radio environment

Non-data-aided (NDA) SNR estimation is considered for M-PSK transmission over additive white Gaussian noise channels. An iterative SNR estimator is derived from an envelope- based estimator. The performance of the proposed estimator is compared to existing algorithms. Simulation results shown for QPSK and 8-PSK demonstrate that the new estimator clearly performs as well as the best SNR estimator in each SNR range.

The spatio-temporal array-receiver (STAR) decomposes generic wideband CDMA channel responses across various parameter dimensions (e.g., time-delays, multipath components, etc...) and extracts the associated time-varying parameters (i.e., analysis) before reconstructing the channel (i.e., synthesis) with increased accuracy. This work verifies the performance of STAR by comparing the results achieved with generic and measured channels for an average multipath power profile of [0, -4, -8] dB and a vehicular speed below 30 Km/h. The results suggest that losses due to operations with real 5 MHz channels are only 1 dB in SNR and 20-30% in capacity with DBPSK and single transmit and receive antennas. The corresponding SNR threshold for operation with real channels is about 5 dB.

Many research efforts were recently spent to address the challenging problem of DOA and angular spread estimation. However, to the best of our knowledge, no previous work has thoroughly investigated their specific impact on the performance of DOA-based antenna-array beamforming. In this contribution, we address this issue in the particular context of wideband CDMA using pilot-assisted or blind antenna-array receivers. In the process, we also assess whether the generalized channel-matched beamforming (i.e., without DOA estimation or a priori knowledge of the spatial structure of the channel) offers a better alternative. Link-level simulation results in terms of required SNR at target BER of 1% suggest that wideband CDMA array-receivers, whether pilot-assisted or blind, are extremely sensitive to angular spread mismatches and that the benefits of exploiting the spatial structure of the channel (i.e., estimation of DOA, angular spread, etc..) translate, at best, in negligible SNR gains when accurate channel identification is already implemented. These results call for implementing channel-matched instead of conventional DOA-based beamforming.

In this paper, a new technique enabling path diversity maximum ratio combining (MRC) is proposed to leverage the performance of the previously proposed Sequential Blind Beamforming (SBB) method. The latter mitigates the inter-symbol and intra-symbol interferences and recovers the signal and its integer and non-integer (fractional) multiple replicas using jointly CMA, LMS and adaptive fractional time delay estimation. While implementing EGC at the combining step can give an acceptable performance in the SBB, since the resolved paths have common phase ambiguity, more substantial improvement can be obtained by implementing coherent MRC with hard decision feedback identification. Simulations results in different scenarios validate the superiority of the SBB using the proposed MRC compared to the EGC path combiner.

This paper presents a new adaptive antenna-array structure using CMA/fractional-delay sequential blind beamforming for multipath correlated signals in environments, such as indoor, confined or underground areas where the multipath problem is more severe than the co-channel interference. The new receiver uses a new synchronization approach for multipath propagation, based on combining a CMA adaptive antenna array and an adaptive fractional time delay estimation filter. This approach is designed to sequentially recover multipath rays based on adaptive time delay estimation for fractional time path arrival delays. The bit-error rate is evaluated for different operating conditions. Simulation results show the promising performance of the new adaptive antenna-array structure

The performance of an OFDM system is highly sensitive to both carrier and sampling frequency offsets. This paper proposes a new joint carrier and sampling frequency offset estimation scheme for OFDM communications suitable for a frequency-selective fading channel. The joint carrier frequency offset (CFO) and sampling frequency offset (SFO) estimation in OFDM is reformulated and resolved as a harmonic retrieval problem. Accurate estimation can be reached even when only one OFDM symbol is used, hence making this method appropriate for offsets with a high level of variability in time. Extension to block processing is presented. Moreover the presented method proved to be robust against large CFO-SFO values, a claim that can not be made for other joint estimation techniques.

In this paper, we extend the investigation of the generalized MC-CDMA system by considering a practical band- limited chip waveform, namely, a square-root raised cosine waveform. The analysis is based on the standard Gaussian approximation. The effects of the chip waveform and the spacing between two adjacent subcarriers on the interference level and on the average BER have been evaluated. The results show that for a given subcarrier spacing between two adjacent subcarriers, there exists a corresponding best choice of the chip waveform. In addition, they suggest that MT-CDMA has the optimum spacing between subcarriers and achieves the best BER performance.

An exhaustive investigation of the overdetermined blind source separation (BSS) 3 times 2 problem is presented. We establish a new relationship between the column vectors of the channel matrix using second order statistics (SOS) only. This relationship is then exploited to factorize the separating matrix into a whitening term, whose expression depends on whether the observations are corrupted by noise or not, and a 2 times 2 orthogonal matrix that can be determined using high order statistics (HOS). Simulation results demonstrate that resorting to the new form of the whitening matrix, mainly in the case of noisy ill-conditioned BSS, results in improved performance compared to the common whitening-based techniques.

The location of people, mobile terminals and equipment is highly desirable for operational enhancements in the mining industry. In an indoor environment such as a mine, the multipath caused by reflection, diffraction and diffusion on the rough sidewall surfaces, and the non-line of sight (NLOS) due to the blockage of the shortest direct path between transmitter and receiver are the main sources of range measurement errors. Unreliable measurements of location metrics such as received signal strengths (RSS), angles of arrival (AOA) and times of arrival (TOA) or time differences of arrival (TDOA), result in the deterioration of the positioning performance. Hence, alternatives to the traditional parametric geolocation techniques have to be considered. In this paper, we present a novel method for mobile station location using wideband channel measurement results applied to an artificial neural network (ANN). The proposed system, the wide band neural network-locate (WBNN-locate), learns off-line the location 'signatures' from the extracted location-dependent features of the measured channel impulse responses for line of sight (LOS) and non-line of sight (NLOS) situations. It then matches on-line the observation received from a mobile station against the learned set of 'signatures' to accurately locate its position. The location accuracy of the proposed system, applied in an underground mine, has been found to be 2 meters for 90% and 80% of trained and untrained data, respectively. Moreover, the proposed system may also be applicable to any other indoor situation and particularly in confined environments with characteristics similar to those of a mine (e.g. rough sidewalls surface).

This paper proposes a spectrum-efficient spatio-temporal array-receiver (STAR) for multi-carrier CDMA systems named MC-STAR. First, we derive a new post-correlation model for MC-CDMA that supports both the MT-CDMA and MC-DS-CDMA air-interfaces. Based on this model, we introduce a new multi-carrier receiver with rapid and accurate joint synchronization in time and frequency. We also exploit the intrinsic subcarrier correlation to improve the channel identification and the synchronization operations. We analyze the performance of MC-STAR in an unknown time-varying Rayleigh channel with multipath, carrier offset and cross-correlation between subcarrier channels. Simulation results confirm the accuracy of the joint time/frequency synchronization. They also confirm that for each MC-STAR configuration there exists an optimum number of subcarriers which results in maximum throughput. A higher number of subcarriers increases the inter-carrier interference while a lower number of subcarriers reduces the frequency gain. With four receiving antennas and five MT-CDMA subcarriers in 5 MHz bandwidth, MC-STAR provides about 1.2 bps/Hz at low mobility for DBPSK, i.e., an increase of 30% in spectrum efficiency over DS-CDMA.

We proposed recently a new technique for multiuser detection in CDMA networks, denoted interference subspace rejection (ISR), and evaluated its performance on the uplink. This paper extends its application to the downlink (DL). On the DL the information about interference is sparse, e.g., spreading factor (SF) and modulation of interferers may not be known, which makes the task much more challenging. We present three new ISR variants, which require no prior knowledge of the interfering users. The new solutions are applicable to MIMO systems and can accommodate any modulation, coding, spreading factor, and connection type. A new dynamic power-assisted channelization code allocation (DACCA) technique significantly reduces implementation complexity at the receiving mobile. Simulations under practically reasonable conditions suggest that increased user capacities and data-rates are attainable with downlink interference subspace rejection (DLISR) and system capacity increases linearly with the number of antennas. Capacity gains are at least 3 dB over the single-user detector and increase to 8 dB for high data-rates with 16-QAM.

Recently, we developed an efficient multiuser upgrade of the single-user spatio-temporal array-receiver (STAR), referred to as interference subspace rejection (ISR) (Affes, S. et al., IEEE J. Selec. Areas Comm., vol.20, no.2, p.287-302, 2002). The resulting STAR-ISR receiver offers a number of implementation modes covering a large range in performance and complexity for wideband CDMA networks. Here we apply STAR-ISR to high data-rate (HDR) transmissions by extending operation to delay spreads larger than the symbol duration. Low processing gain situations render symbol timing extremely difficult, especially with RAKE-type receivers. For HDR links of 512 Kbps in 5 MHz bandwidth, simulations indicate that the simplest mode of STAR-ISR outperforms the 2D-RAKE-PIC by a factor of 4 to 5 in spectrum efficiency while requiring the same order of complexity. This gain increases by up to a factor of 7.5 in high Doppler.

We extend application a new scheme for efficient use of pilot signals in wideband CDMA array-receivers from the pilot-channel to the pilot-symbol case. The new scheme exploits the pilot signals for the simple resolution of the sign ambiguity arising in BPSK-decision-directed blind channel identification and achieves significant spectrum efficiency gains and power or overhead savings over the same array-receiver versions, which use pilots for conventional channel identification only. Both analysis and simulations suggest that pilot channel and pilot-symbol array-receiver versions, either with conventional or new pilot use, have similar performance at weak Doppler. They also indicate increasing performance gains with increasing Doppler due to the improved use of the pilot information. For a data rate of 144 Kbps with 60 Kmph speed, simulations indicate efficiently gains due to new pilot use of about 25 and 70% in the pilot-channel and pilot-symbol cases, respectively.

We consider packet scheduling and rate assignment on the uplink of a packet data wireless CDMA network in the presence of imperfect interference cancellation (IC) and limited user transmission rates, and subject to in-cell and out-of-cell resource limitations. The objective is to propose and implement a system level position-based flow control algorithm that accounts for a limited IC capability provided by power control for multi-user detection. The proposed algorithm assigns packets to be transmitted to separate queues, one for each spatial zone within which packets generate roughly the same in-cell interference and impose equal interference on a neighboring base station. Given the cell partitioning into zones, the algorithm dynamically adapts to the resource constraints and efficiently uses IC to provide for fairness in serving the various queues without giving up the objective of maximizing data throughput. Throughput and fairness are two conflicting objectives to be optimized. We show that the joint use of IC and location-based scheduling is able to achieve complete fairness with negligible loss in throughput even under stringent resource limitations.

This paper presents comprehensive experimental results obtained from narrowband and wideband radio channel measurements in an underground mine with narrow veins at 2.4 GHz. From CW measurement data, large-scale distance-power curves and path-loss exponents of the environment are determined. Other relevant parameters such as mean excess delay, maximum excess delay and rms delay spread are extracted from wideband measurement data. Results show a propagation behavior that is specific for these underground environments with rough surfaces.

We consider forward-link soft-handoff with multiple antenna selection and fast joint power control at high data rates in a cellular code-division multiple-access network, where signals are directed to a mobile station (MS) from antennas located at the same or different base stations. The total power transmitted to any mobile is divided among the active antennas selected according to the momentary channel conditions so as to maximize the signal-interference ratio at each MS. Multiple-antenna selection is used to mitigate the effects of both short- and long-term fading, and achieve the best soft-handoff with respect to system capacity and complexity. To achieve capacity gains with soft-handoff, we derive optimum handoff thresholds corresponding to the optimum handoff region in different cell environments. Numerical results demonstrate that under high Doppler spread and large handoff-delay conditions, the proposed soft-handoff employing two transmit antennas and the optimum handoff threshold achieves a significant gain in microcell environments, but not in macrocell environments.

We present the propagation characteristics at 2.45 and 18 GHz resulting from the statistical analysis of a narrowband measurement campaign in an underground mining environment. Parameters, such as the amplitude distribution of the envelope, level crossing rate, average fade duration and coherence time of the channel, have been examined. An analysis by linear regression has also been used to study the variations of the received power according to the transmitter-receiver distance.

We propose a carrier frequency offset recovery (CFOR) module for CDMA to operate with STAR, the spatio-temporal array-receiver. The new CFOR module implements simple linear regression (LR), similar in approach to that implemented for time-delay synchronization in STAR. Simulations in selective Rayleigh-fading channels at various mobile speeds show that an increasing carrier frequency offset (CFO) severely degrades the capacity of a CDMA system, the relative loss being more significant at low mobility and transmission rate. CFOR with STAR reduces the effect of CFO and compensates almost completely the capacity loss. Relative capacity gains due to CFOR increase with the CFO. For nomadic voice and data-rates, the capacity gain is in the range of 270 and 150% respectively, at a CFO of about 1 ppm.

STAR, the spatio-temporal array-receiver was shown to outperform RAKE-type array-receivers and to increase the capacity of wideband CDMA networks. Turbo codecs were also identified as offering significant performance improvements. We demonstrate the gain achieved by turbo codecs over conventional convolutional codecs in a STAR-based CDMA system. For high data-rates of 153.6 Kbps with low mobility, link-level simulations on the uplink indicate that turbo codecs gain 2 to 3 dB in required SNR at a BER<10/sup -6/. System-level simulations confirm that SNR gains almost double capacity, from 7 to 13 mobiles/cell for blind STAR (i.e., without pilot) and from 10 to 22 mobiles/cell for pilot-aided STAR.

We present a unifying framework for a new class of receivers that employ linearly-constrained interference cancellation (IC). The associated multiuser detectors operate in various modes and options ranging in performance from that of IC detectors to that of linear receivers, yet provide more attractive performance/complexity tradeoffs. They exploit both space and time diversities as well as the array-processing capabilities of multiple antennas and carry out simultaneous channel and timing estimation, signal combining and interference rejection. Additionally, they can operate on both links and in multiple mixed-rate traffic scenarios. The improved performance can be translated to increased utilization of wideband code division multiple access networks, particularly at high data rates.

Abstract A more efficient detection of orthogonal Walsh‐modulated Code Division Multiple Access (CDMA) signals is required not only for better exploitation of current IS‐95 CDMA systems but also for future cdma2000 3G networks. Integration of adaptive antennas at the base station has been recognized as one key lever to increasing capacity and spectrum efficiency. Prospective array‐receiver solutions such as the 2‐D‐RAKE improve performance; however, in the absence of a pilot signal, they have to implement noncoherent detection. In this work, we propose a space‐time processor that achieves coherent detection of orthogonal Walsh‐modulated CDMA signals without a pilot. We assess its performance in spatially correlated Rayleigh‐fading. Simulation results for voice links of 9.6 Kbps indicate that up to an antenna‐correlation factor of 0.8, the proposed receiver outperforms the conventional 2‐D‐RAKE's capacity by 90% in nonselective fading. This gain shrinks fast at higher correlation factors. In selective fading, however, it maintains about a 130% gain in capacity over the entire correlation range. For data links of 153.6 Kbps, this performance advantage increases up to 180–200%. With high‐speed mobiles, however, it vanishes quickly at correlation factors beyond 0.5. Overall, the capacity gains of the proposed spatiotemporal receiver structure increase with reduced relative Doppler (Doppler‐frequency/symbol‐rate ratio). This may arise from increased spatiotemporal diversity, higher transmission rates, and/or slower mobility. Copyright © 2002 John Wiley & Sons, Ltd.

This paper extends our study on a multi-user receiver structure for base-station receivers with antenna arrays in multicellular systems. The receiver employs a beamforming structure with constraints that nulls the signal component in appropriate interference subspaces. Here we introduce a new mode, ISR-D (diversities), which finds and suppresses the subspace of the identified paths of all known interferers. A frame extension technique is proposed which can be applied to all available ISR modes to increase the dimensionality of the observation space and thereby avoid noise amplification as a result of subspace suppression, as well as allow asynchronous transmission. Performance differences arise between the modes due to different sensitivities to channel identification and data detection errors. For homogeneous high data-rate situations ISR-DX manifests the best performance. However, due to its reduced complexity, ISR-TRX appears to offer the best complexity-performance tradeoffs.

Multiuser CDMA detectors suppress interference to provide improved noise immunity, increased capacity, higher data rates and reduced precision requirements for power control. A new multiuser detector structure is formulated which offers a number of implementation modes ranging in performance from that of interference cancellation (IC) detectors to that of linear receivers, yet provides more attractive performance/complexity tradeoffs. It exploits both space and time diversities as well as the array-processing capabilities enabled by multiple antennas and carries out simultaneous channel and timing estimation, signal combining and interference rejection. The improved performance enables increased utilization of wideband CDMA networks, especially at high data rates.

The synchronization performance of the receivers may severely impact the capacity or spectrum efficiency of wideband code division multiple access (CDMA) networks. Evaluations of the uplink capacity for improved spatio-temporal array receivers (STAR) and the two-dimensional RAKE (2-D-RAKE) with both perfect and active synchronization indicate that synchronization with the early-late gate component of a RAKE-type receiver may constitute a bottleneck to performance improvement. Enhancement of synchronization remains a key issue. Results also suggest that STAR offers a promising alternative to the 2-D-RAKE with early-late gate, offering an average increase in spectrum efficiency up to 100% in the presence of synchronization errors at both data rates of 9.6 and 128 kb/s. This gain further increases in high Doppler and fast multipath delay drifts. Data oversampling above the chip-rate favors STAR even more. Significant simplifications are introduced in the formulation of the STAR receiver which result in a complexity comparable to the 2-D-RAKE.

The use of coherent modulation for the uplink of wireless CDMA systems requires pilot signals which contribute to the interference seen by other users. In previous work we showed that blind array-receivers outperform pilot-channel assisted array-receivers in capacity for various operating conditions. These array-receivers avoid additional interference due to pilot signals and achieve better channel identification using relatively stronger data signals. However, for BPSK signals they identify the channel within a sign ambiguity and require differential modulation and decoding of coherently detected bits. In this contribution we implement coherent modulation and detection and further increase the advantage of this blind channel identification scheme by introducing a new pilot called "pilot-sign". This pilot simply allows resolution of the channel sign ambiguity after its estimation by long-term averaging of the pilot-channel combiner output. Analysis indicates that the resulting pilot-sign assisted array-receiver requires very weak pilot power ratios, in the range of a fraction of a percent, and allows very significant pilot power savings and large capacity gains compared to pilot-channel array-receivers.

The spatio-temporal array-receiver (STAR) achieves good performance in CDMA with multiple receiving antennas where the interference can be characterized as AWGN uncorrelated with the signal. To enhance its near-far resistance in correlated noise environments, we introduce optimal combining of the spatio-temporal components. Nearly as good performance can be obtained with a low complexity adaptive beamformer combination of the antenna and multipath diversity branches. Simulation results indicate that the modified STAR manifests significant gain in near-far resistance over its original version, more so with more branches. They also suggest that exploiting additional temporal correlation fingers as interference references can further improve near-far resistance in poor diversity situations.

We propose an efficient signal processing technique to exploit smart antennas in IS-95 CDMA. It integrates decision feedback identification (DFI) and new decision variables into the adaptive antenna beamforming scheme. These two features permit implementation of a coherent detection on the uplink without a pilot and spatio-temporal maximum ratio combining (MRC). With two antennas and nonselective fading, the additional gain in SNR achieved by either feature is as significant as the gain obtained by simple antenna beamforming over diversity combining. Up to a 2 dB performance advantage is obtained in selective fading as compared to simple beamforming.

We propose a spatio-temporal array-receiver (STAR) for asynchronous code division multiple access (CDMA), using a new space/time structural approach. First, STAR performs blind identification and equalization of the propagation channel from each mobile transmitter. Second, it provides fast and accurate estimates of the number, relative magnitude, and delay of the multipath components. From this space/time separation, STAR reconstructs the identified channel with respect to a partially revealed space/time structure and reduces identification errors by the order of the ratio of the processing gain and the number of paths. Therefore, STAR offers a high potential for increasing capacity, with relatively low computational complexity. Simulations confirm the good multipath acquisition and tracking properties of STAR in the presence of strong interference and fast Doppler.

Matched filtering and adaptive beamforming are both necessary for efficient speech dereverberation and noise reduction by microphone arrays. This can be achieved by the identification of impulse responses. We show that adaptive microphone arrays are sensitive to the identification errors of the impulse responses, particularly due to speaker movements. We prove that adjusted matched-filtering and permanent tracking of the impulse responses are also necessary. The proposed microphone array responds well to these requirements under realistic conditions.

Efficient multipath tracking is a crucial requirement for high performance in asynchronous cellular CDMA. Despite the recent increased focus on use of array receivers at the base stations, the problem of time-delay estimation for individual paths has not been specifically addressed. In this contribution we propose simple and fast multipath tracking procedures in a nonstationary CDMA environment, using the spatio-temporal array-receiver (STAR). Both the time-delays and their number are tracked in time in a partially blind scheme with a low order of computational complexity. We show by simulations the tracking capability of STAR at a high interference level.

This paper presents a method of adaptive microphone array beamforming using matched filters with signal subspace tracking. Our objective is to enhance near-field speech signals by reducing multipath and reverberation. In real applications such as speech acquisition in acoustic environments, sources do not propagate along known and direct paths. Particularly in hands-free telephony, we have to deal with undesired propagation phenomena such as reflections and reverberation. Prior methods developed adaptive microphone arrays for noise reduction after a time delay compensation of the direct path. This simple synchronization is insufficient to produce an acceptable speech quality, and makes adaptive beamforming unsuitable. We prove the identification of source-to-array impulse responses to be possible by subspace tracking. We consequently show the advantage of treating synchronization as a matched filtering step. Speech quality is indeed enhanced at the output by the suppression of reflections and reverberation (i.e., dereverberation), and efficient adaptive beamforming for noise reduction is applied without risk of signal cancellation. Evaluations confirm the performance achieved by the proposed algorithm under real conditions.

We propose in this paper an array of microphones which achieves good performance in double talk situations. By a subspace tracking procedure, we jointly identify the acoustic paths from the speech and echo sources. With an adaptive beamformer constrained over these paths, we properly recover the original speech, cancel the echo and reduce the background noise. Simulations made with real data confirm the efficiency of this array.

We consider the problem of locating and extracting sources received by an array of sensors in two significant cases. In one case, sensor positions are partially unknown. In the other one, the propagation to a subset of sensors is unknown. The core of the algorithm is partially blind identification of steering vectors. It relies on a tracking procedure with low computational complexity. We apply it to the calibration of maneuvering and towed arrays receiving multiple and correlated sources.

We present a novel adaptive algorithm in the frequency domain with a low order of arithmetic complexity for simultaneously performing beamforming, source direction finding and array shape calibration. The algorithm is proposed for multiple wideband sources, but could be applied to the narrowband case or to a single wideband source. The source signals are first estimated using a set of beamformers. These estimates are processed with the observation signals to track the steering vectors within the signal subspace. The adapted steering vectors are projected over the array manifold, to finally estimate the source directions and sensor positions. Simulations show the efficiency of the algorithm to achieve the proposed tasks.

This paper presents an algorithm implementing robustness in beamforming, by directly reducing localization errors in the presence of pointing errors or a single moving target. Given an initial position, the desired source signal is first estimated using a classical beamforming unit. It is in a second step, processed by an LMS-like gradient stochastic estimation procedure of the steering vector, to adaptively track the correct source position. The newly identified source position is projected over the array manifold, then finally transmitted in a feedback loop to the beamforming unit, closing in this way the global algorithm iteration. The simulation results show that robustness is effectively realized without any compromising output SNR loss. Moreover, they prove an efficient tracking behavior in the presence of mobile sources. >