This study reveals the vulnerabilities of Wireless Local Area Networks (WLAN) sensing, under the scope of joint communication and sensing (JCAS), focusing on target spoofing and deceptive jamming techniques. We use orthogonal frequency-division multiplexing (OFDM) to explore how adversaries can exploit WLAN’s sensing capabilities to inject false targets and disrupt normal operations. Unlike traditional methods that require sophisticated digital radio-frequency memory hardware, we demonstrate that much simpler software-defined radios can effectively serve as deceptive jammers in WLAN settings. Through comprehensive modeling and practical experiments, we show how deceptive jammers can manipulate the range-Doppler map (RDM) by altering signal integrity, thereby posing significant security threats to OFDM-based JCAS systems. Our findings comprehensively evaluate jammer impact on RDMs and propose several jamming strategies that vary in complexity and detectability.

Recently, there has been a growing interest in multistatic radar configurations to improve the localization of multiple targets. Theoretically, the maximum likelihood (ML) approach enables to fuse the information provided by each radar pair to localize the different targets. However, it involves a multidimensional search process whose complexity exponentially grows with the number of targets. Consequently, heuristic methods, notably including the block orthogonal matching pursuit (BOMP), have been used in the multistatic radar context to approach the ML estimation greedily. Interestingly, the more accurate block orthogonal least squares (BOLS) method has not been studied in this context because the performance improvement is usually low in regard to its computational complexity. In this work, we investigate the application of BOLS to an angle-based localization of multiple targets using a multistatic multiple-input and multipleoutput (MIMO) radar. First, an efficient implementation of BOLS is presented reducing its computational complexity. Then, using Monte Carlo simulations, we show evidence of the significant advantage of this efficient implementation of BOLS over BOMP in this scenario featuring highly correlated signals. The impact of radar parameters on the localization root mean square error and on the computational complexity of both algorithms is studied.

This paper evaluates the downlink performance of cellular networks in terms of coverage and electromagnetic field exposure (EMFE), in the framework of stochastic geometry. The model is constructed based on datasets for sub-6 GHz macro cellular networks but it is general enough to be applicable to millimeter-wave networks as well. On the one hand, performance metrics are calculated for β-Ginibre point processes which are shown to faithfully model a large number of motion-invariant networks. On the other hand, performance metrics are derived for inhomogeneous Poisson point processes with a radial intensity measure, which are shown to be a good approximation for motion-variant networks. For both cases, joint and marginal distributions of the EMFE and the coverage, and the first moments of the EMFE are provided and validated by Monte Carlo simulations using realistic sets of parameters from two sub-6 GHz macro urban cellular networks, i.e., 5G NR 2100 (Paris, France) and LTE 1800 (Brussels, Belgium) datasets. In addition, this paper includes the analysis of the impact of the network parameters and discusses the achievable trade-off between coverage and EMFE.

A novel unified frequency diverse array (FDA) and spatial data focusing (SDF) approach is proposed to simultaneously overcome time-variance and precision constraints of conventional FDA in geocasting, i.e., spatially confined broadcasting, scenarios. This paper describes a free space FDA-based SDF (FDA-SDF) system model for 2-dimensional range-angle-based focusing, including a generalized multi-purpose baseband approach for time-invariant FDA, complemented by SDF processing for improved spatial focusing precision and reduced array size. Comprehensive analytical derivations – general for any frequency offset configuration – describe the geographical FDA-SDF properties and design rules, such as geocast delivery zone steering, location, uniqueness, and size. Simulations of the proposed scheme validate theoretical derivations and demonstrate FDA-SDF’s superior spatial precision and minimal design complexity. In particular, using novel alternating logarithmic frequency offsets, a 3-antenna FDA-SDF setup is shown to match the radial and azimuthal precision of its beamforming-based FDA counterpart using, respectively, 64 and 24 antennas.

This paper presents the first-ever experimental validation of both spatial data focusing (SDF) and time-invariant frequency diverse array (FDA) range-angle-based focusing, in both free space and multipath environments. In particular, a hybrid FDA-based SDF (FDA-SDF) approach is considered for spatially confined broadcasting, i.e. geocasting. First, the base FDA-SDF free space system model is reviewed. Next, a novel OFDM-based FDA-SDF system model is introduced to ensure robust operation in multipath channels. The schemes are validated, respectively, in an anechoic chamber and outdoor measurement setup using software defined radios. Results confirm FDA-SDF's anticipated supreme spatial precision: a 0.9 m × 4.0° range-azimuth geocast delivery zone is generated by a 4-antenna array in free space. Additionally, they illustrate that OFDM-based FDA-SDF provides all necessary performance improvements for practical operation in outdoor multipath environments. Most notably, FDA-SDF is shown to overcome the time-variance flaw of conventional FDA.

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

Localization of non-cooperative radio frequency transmitters in wireless networks can be performed by using Time Difference of Arrival (TDoA). However, TDoA measurements are often degraded by limited signal-to-noise ratio, multipath components, non-line-of-sight (NLOS) visibility, etc. This causes the TDoA measurements to have strong outliers, which cannot easily be modelled mathematically. This paper investigates algorithms to perform TDoA-based localization in the presence of outlier measurements. Our algorithm is based on a geometric interpretation, rather than a mathematical, noise model-based approach. We show that our algorithm outperforms existing algorithms when applied to real-world data in a vehicular scenario.

A unified frequency diverse array (FDA) and spatial data focusing (SDF) system, or FDA-SDF, is proposed as a novel approach to perform spatially confined broadcasting of information, i.e. geocasting. It is shown that SDF processing exploits FDA range-angle-dependency more effectively than conventional power focusing implementations, resulting in improved spatial focusing precision and reduced array size. Additionally, the time-variance flaw in conventional FDAs is addressed and mitigated by introducing a generalized baseband FDA model. This paper describes the FDA-SDF system model in free space, including dedicated SDF precoding, beamsteering, and equalization, exploiting FDA multi-frequency transmission for 2-dimensional range-angle-based time-invariant geocasting. Simulations of the FDA-SDF system illustrate compatibility with conventional FDA frequency offset schemes and highlight degrees of freedom for geocast delivery zone manipulation. Finally, FDA-SDF's superior spatial precision is demonstrated: a 3-antenna FDA-SDF setup matches the radial and angular precision of a conventional FDA using, respectively, 13 and 23 antennas.

OFDM-based spatial data focusing (OFDM-SDF) is proposed as a novel means of performing wireless physical layer geocasting, i.e. spatially confined broadcasting. It is shown that this approach overcomes beamforming and directional modulation (DM) limitations by exhibiting higher spatial precision with a reduced number of antennas and offering uncoupled range-angle-dependent focusing. This paper describes the OFDM-SDF system model for multipath channels, including multipath robust equalization, design rules for steering phases and sidelobe mitigation, analytical geocast delivery zone derivation, and optimized symbol mapping. Using density-based clustering of the spatial bit error rate distribution, a procedure for identifying a practical geocast delivery zone and evaluating its precision and connectivity is proposed. OFDM-SDF’s performance and multipath robustness are evaluated through Rice channel simulations as a function of the Rice factor. In particular, it is shown that a 2-antenna OFDM-SDF array matches the radial and angular precision of, respectively, a 6 and 12-antenna DM array in recent literature, while robustness is ensured for 5G small cell channels.

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

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

Physical-layer security (PLS) has the potential to strongly enhance the overall system security as an alternative to or in combination with conventional cryptographic primitives usually implemented at higher network layers. Secret-key generation relying on wireless channel reciprocity is an interesting solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this article, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS). Moreover, as opposed to previous works, we take into account the fact that the eavesdropper's observations might be correlated and we consider the high signal-to-noise ratio (SNR) regime where we can find simple analytical expressions for the secret-key capacity. As already found in previous works, we find that RSS-based secret-key generation is heavily penalized as compared to CSI-based systems. At high SNR, we are able to precisely and simply quantify this penalty: a halved pre-log factor and a constant penalty of about 0.69 bit, which disappears as Eve's channel gets highly correlated.

Recently, event organizers and researchers have advocated the development of novel technologies supporting crowd control, notably for public events. This paper presents a crowd monitoring system based on probe requests (PRs), which are Wi-Fi packets smartphones send periodically. By estimating the global rate at which nearby smartphones send PRs, Wi-Fi sensors can estimate crowd counts. The core contribution of this paper is a computationally tractable method that forecasts crowd counts up to thirty minutes in the future, with forecasts becoming available as soon as two hours of data are available. The forecasting method relies on autoregressive integrated moving average (ARIMA) models. Contributions also include two methods that compute prediction intervals associated with the forecasts, one of which is based upon generalized autoregressive conditional heteroskedasticity (GARCH) models. Recent real-world data from Winter Wonders 2018/2019 (an event that took place in Brussels, Belgium) notably demonstrate that the proposed forecasting method outperforms its immediate variations as well as baseline models (i.e., random walk models).

An OFDM-based Spatial Data Focusing (OFDM-SDF) approach is proposed as an improvement over standard Time-based Spatial Data Focusing (T-SDF) as a means of wirelessly broadcasting information towards confined spatial locations, i.e. wireless geocasting. It is shown that this approach allows for 2-dimensional focusing, hence leading to far greater flexibility in terms of geocasting scenarios compared to T-SDF and beamforming, both limited to angular focusing only. This increased flexibility does not come at any trade-off costs in terms of spatial selectivity, and hence, just as T-SDF, OFDM-SDF is shown to establish a considerable increase in attainable geocasting accuracy when compared to traditional power focusing methods. This paper describes the free space OFDM-SDF system model for uniform linear antenna arrays, including beamsteering and sidelobe mitigation techniques. Based on simulations, the performance of OFDM-SDF is compared to both T-SDF, as well as classical beamforming.

Secret-key generation exploiting the channel reciprocity between two legitimate parties is an interesting alternative solution to cryptographic primitives for key distribution in wireless systems as it does not rely on an access infrastructure and provides information-theoretic security. Many works in the literature assume that the eavesdropper gets no side information about the key from her observations provided that: (i) it is spaced more than a wavelength away from a legitimate party and (ii) the channel is rich enough in scattering. In this paper, we show that this condition is not always verified under realistic propagation conditions and we study the resulting secret-key capacity.

Time-difference-of-arrival (TDOA) localization systems estimate the difference in propagation delay between a target transmitter and pairs of receivers in order to locate the target. One important requirement is that the receiver nodes should be accurately time-synchronized, which is hard to achieve in practice without relying on cable-connected receivers. Over-the-air synchronization algorithms often rely on periodic messages from a master node, but due to clock drift, the rate of these messages needs to be high. In this paper, we propose a new synchronization algorithm that additionally exploits the carrier frequency offset (CFO) between the target node and the receiver nodes to reduce the rate of messages from the master node while maintaining good synchronization accuracy. Simulation results show the good performance of the proposed method, and preliminary experimental results show its feasibility on a hardware platform.

In practice, the subspace-based algorithms such as Multiple Signal Classification (MUSIC) suffer from sensitivity to antenna-array response errors and therefore they require the assessment of the calibration gain and phase perturbations. This paper evaluates experimentally the accuracy of Angle-of-Arrival (AoA) estimation based on the MUSIC algorithm only coming from these perturbations in the context of Internet-of-Thing (IoT) applications. First of all, a new Over-the-Air (OTA) calibration method is proposed and gain and phase uncertainties are investigated. The impact of these uncertainties on the accuracy of AoA estimation is then studied and compared with the theoretical analysis. The experimental results show that the calibration errors coming from hardware imperfections can cause some degrees of uncertainty in AoA estimation.

A relay network can provide the extended link capacity and coverage thanks to its good spatial diversity. In order to analyze the relay network performance, most of the works in literature assume the independent relaying channels. In practice, the received signals experience the common scatterers, hence the correlated relaying channels should be considered. In this paper, we first derive a novel and accurate probability density function (PDF) of a modulus of the sum of products of two correlated zero-mean complex Gaussian random variables (RVs), which is useful for the statistical analysis of the cascaded relaying fading channels. Based on this result, we secondly investigate the received signal-to-noise ratio (SNR) outage probability of a relay network in the presence of correlated relaying channels. It is found that the correlation magnitude is more important than the correlation phase for the analysis of power-based signal-detection of relay networks. Numerical simulations have been carried out to confirm the correctness of the derivation.

Multiple-antenna technologies provide a good spatial diversity gain for emerging communication systems. In combination to the orthogonal frequency division multiplexing (OFDM) modulation, a precoding system can be easily implemented and efficient to combat the effect of fading channels. However, the precoding system requires a perfect knowledge of the channel, which is not usually hold in practical cases. In this paper, we investigate the impact of the imperfect channel state information (CSI) on the downlink performance of multiple-input single-output (MISO) OFDM systems using a matched-filter (MF) precoder. Particularly, the exact mean-square-error (MSE) expression of the equalized received signal of the MF precoding system is derived. Numerical simulations with Rayleigh fading channels are carried out to validate the analysis. The results show that the imperfect CSI-based precoder causes a MSE plateau compared to the ideal case of using the perfect CSI.

We address the problem of static clutter removal in Wi-Fi-based passive bistatic radars. Our goal is to detect slowly moving targets in highly cluttered indoor environments, using Orthogonal Frequency-Division Multiplexing signals from the 802.11n and 802.11ac Wi-Fi standards as sources of opportunity. We propose alternatives to the commonly used Extended Cancellation Algorithm (ECA) clutter removal method. Those alternatives are compared to ECA with simulations using an innovative metric based on CA-CFAR detection, and validated with experimental measurements using two Universal Software Radio Peripherals, along with a fan and an electric train as radar targets. The conclusion of that analysis is that, thanks to the decoupled range and Doppler radar processing, simple novel methods such as Average Removal are efficient alternatives to the computationally intensive ECA which is currently the state-of-the-art in CR.

Angle-of-arrival (AoA) estimation-based localization systems are a promising technology in the context of Internet-of-Things. The system considered is a densely deployed set of anchors equipped with arrays of antennas able to measure the AoA of the signal emitted by the device to be located. Naturally, the AoA measurements are prone to uncertainties due to noise, channel conditions and uncertainties on the anchors placement and orientations. In this work, a method based on Polynomial Chaos Expansions is proposed to perform anchor selection in order to enhance the precision of the positioning. An experimental setup with six anchors is implemented to evaluate the performance of the proposed method. The experimental results demonstrate that by applying our anchor selection method, the performance of the localization system improves.

The goal of this work is to identify the possible degradations on a Wi-Fi based Passive Radar in the presence of an interferer. We assume that the signal-of-opportunity and the interference are 802.11ax compliant. The mathematical model derived for the interference shows that in a synchronized case, the interference may yield ghost targets. When a more occasional interference scenario is considered, the range/Doppler Map accuracy decreases significantly. Furthermore, numerical results are provided to quantify certain effects of OFDM radar interference on range/Doppler Maps.

Spatial Data Focusing (SDF) is introduced as a novel technique that allows wireless broadcasting of information towards specific spatial locations only. It is shown that this approach allows one to target geographic areas more accurately than traditional power focusing methods, using limited equipment at the transmitter. This paper describes the SDF system model for linear arrays, based on simple modulation techniques and transmitter architectures, both in pure line-of-sight and multipath environments. In particular, the robustness of the scheme is proven for over-the-ground propagation environments. Theoretic results are illustrated by simulations, confirming the increased spatial selectivity of SDF and showing the influence of various design parameters of the scheme on the resulting beam.

Internet of Things (IoT) integrates numerous technologies to obtain the location information of the sensors in various ways. The most common localization methods are based on measuring a location dependent parameter such as Received Signal Strength (RSS) or Angle of Arrival (AoA). Then the measured parameters are used to estimate the sensor location by using a multilateration algorithm. AoA estimation can provide good localization accuracy for narrowband array-based systems. The research has drawn considerable attention in the literature and numerous methods have been proposed to improve the localization accuracy. The two-step method suffers from information loss from the received signals when the estimation of the parameters is communicated to the multilateration step. In this paper, we propose a new localization algorithm which iterates between AoA estimation and multilateration steps to refine the position estimate. We develop a localization scenario for the assessment and validation of the algorithm in Bluetooth Low Energy (BLE) sensor networks. Simulation results show that the proposed solution achieves a better localization accuracy when compared to the common two-step and achieving this after only a few iterations. Additionally, our method comes very close to the performance of the position estimation relying directly on the received signal, known as Direct Position Estimation (DPE), while reducing its complexity.

Time reversal-based indoor positioning system (TRIPS) is a promising technology for the centimeter-accuracy indoor positioning, since it exploits the rich multipath propagation in indoor environments as a specific signature for each location. In TRIPS, a database is first constructed via channel probing. Well-calibrated devices are usually assumed in this process, i.e., no hardware impairments. However, a low cost terminal to be located, whose typical impairment is the I/Q imbalance (IQI) at the front-end transmitter, can significantly influence the TRIPS performance. More specifically, IQI creates an interference image of the signal that reduces the metric value used in TRIPS and hence decreases the localization accuracy. In this paper, we analytically investigate the impact of the IQI on the metric of TRIPS. A closed-form approximation of the localization metric inherent to the IQI is derived. In order to improve the TRIPS performance, an effective IQI mitigation method is proposed. Numerical simulations are carried out to validate the derived analytical expression under the IQI impact and the proposed compensation method.

Iterative localization is arising as a promising solution to determine the position of a mobile station in a cellular network. We recently showed that in a perfect line-of-sight environment, iterating between the conventional delay estimation and multi-lateration steps allows to approach the performance of the direct localization based on the observation of the received signals. In this paper we extend our iterative localization method to operate in rich multipath environments. Simulation results prove that given some prior knowledge on the power delay profile of the channel, the proposed iterative algorithm is robust to harsh propagation environments and performs very close to the direct localization approach.

The introduction of the Bluetooth Low Energy (BLE) standard significantly streamlines the development of the Internet of Things (IoT) applications. These applications often require the sensor positioning to link the measurements with its location. Therefore, it is essential to conduct studies on BLE transmitter positioning methods. Power fingerprinting transmitter positioning approaches are commonly used in BLE network. However, these methods have their own limitations in terms of practical use and ease of implementation. The purpose is to develop a simple BLE transmitter positioning of high accuracy. In this paper, a BLE transmitter positioning method is proposed based on Angle of Arrival (AOA) estimation. Multiple Signal Classification (MUSIC) algorithm is used for angle estimation due to the high angular resolution and sensitivity. Several experiments have been conducted in an indoor environment and the results compared with simulation results. Experimental results show that our proposed BLE transmitter positioning method achieves a promising positioning accuracy.

Time reversal has been shown as a promising technology for the indoor positioning. Instead of mitigating the multipath channel, the time reversal based indoor positioning system (TRIPS) exploits the rich multipath propagation in indoor environments as a specific signature for each location. In order to do this, a database should be first constructed by channel probing. The devices used in this process are assumed to have no hardware impairments or be well calibrated. However, the low cost terminal to be located can exhibit impairments, such as I/Q imbalance at the front end transmitter known to create an interference image of the signal that can particularly impact the performance of time reversal. In this paper, we investigate the impact of the I/Q imbalance on the TRIPS. We analytically show that the I/Q imbalance modifies the metric used for the localization and hence reduces the spatial focusing gain of TRIPS. Numerical simulations are carried out to evaluate this observation. The results further show that the I/Q imbalance creates errors in the positioning estimation. More specifically, at the gain and phase imbalances of respectively 1.1 and 10°, the focusing gain reduction is about 0.5 dB while the estimation error rate is increased by about 5% in the specified scenario.

Offset-QAM-based filterbank multicarrier (FBMC-OQAM) modulations are known to progressively loose their orthogonality as the channel gets more selective in time and frequency. The effect of channel frequency selectivity on FBMC-OQAM systems has been extensively studied in the literature. Many compensations methods have been proposed to combat it. However, most of them have a significant implementation complexity and do not take into account the time selective nature of the channel. In this paper, we propose a MIMO equalizing structure for doubly selective channel based on a simple single-tap per-subcarrier decoding matrix. The decoding matrices are designed to minimize the mean squared error of the symbol estimate. This decoder exploits the degrees of freedom offered by the extra antennas at the receiver to compensate for the distortion induced by time and frequency selectivity. Simulation results demonstrate the performance gain of the proposed design with respect to classical designs.

Emerging cellular networks integrate the user terminal geo-localization function besides the communication function. The conventional positioning approach is to estimate the terminal location in two-steps: first the distance to all connected base stations is assessed based on signal time-of-flight measurements, then the location is deduced from the distances by multi-lateration. The two-step approach incurs a performance degradation because information is lost from the received signal when the multi-lateration is performed. In this paper, we propose to iterate between the two conventional steps to progressively refine the distance estimates based on the knowledge of the position estimate obtained from the previous iterations. The information exchanged between the two-steps not only consists in the mean of the estimates (distance or position) but also of their variance that convey information about the reliability of the estimates. Simulation results show that the achievable performance after a few iterations is close to the performance of the optimal approach that directly estimates the position based on the observation of the received signal.

This paper addresses the carrier phase recovery problem in Offset-QAM-based filterbank multicarrier (FBMC-OQAM) systems. The combined phase noise coming from the transmit and receive lasers, is known to induce a phase rotation of the demodulated symbols at the receiver. Several approaches have been proposed to recover the phase in FBMC-OQAM communication systems on optical fiber. Most of them have a significant complexity and do not make use of all information at disposal. In this paper, we propose two new estimators, obtained by minimizing a maximum likelihood (ML) and a maximum a posteriori (MAP) criteria. They use an error model formulation which allows to easily use priors on the phase noise statistics. By linearization of the error, an analytical solution is found for the phase error, which avoids the need for multiple phase tests. Simulation results demonstrate the better performance of the proposed estimators with respect to state of the art solutions in the low signal-to-noise (SNR) regime and for a small number of subcarriers.

Several exact recovery criteria (ERC) ensuring that orthogonal matching pursuit (OMP) identifies the correct support of sparse signals have been developed in the last few years. These ERC rely on the restricted isometry property (RIP), the associated restricted isometry constant (RIC) and sometimes the restricted orthogonality constant (ROC). In this paper, three of the most recent ERC for OMP are examined. The contribution is to show that these ERC remain valid for a generalization of OMP, entitled simultaneous orthogonal matching pursuit (SOMP), that is capable to process several measurement vectors simultaneously and return a common support estimate for the underlying sparse vectors. The sharpness of the bounds is also briefly discussed in light of previous works focusing on OMP.

The simultaneous orthogonal matching pursuit (SOMP) algorithm aims to find the joint support of a set of sparse signals acquired under a multiple measurement vector model. Critically, the analysis of SOMP depends on the maximal inner product of any atom of a suitable dictionary and the current signal residual, which is formed by the subtraction of previously selected atoms. This inner product, or correlation, is a key metric to determine the best atom to pick at each iteration. This letter provides, for each iteration of SOMP, a novel lower bound of the aforementioned metric for the atoms belonging to the correct and common joint support of the multiple signals. Although the bound is obtained for the noiseless case, its main purpose is to intervene in noisy analyses of SOMP. Finally, it is shown for specific signal patterns that the proposed bound outperforms state-of-the-art results for SOMP and orthogonal matching pursuit (OMP) as a special case.

A wideband spectrum sensing method for cognitive radios is presented which is based on compressed measurements. The proposed detector does not require signal reconstruction from the compressed measurements. A fusion centre collects the measurements from different sensing nodes and then makes a sensing decision based on a simplified maximum likelihood criterion which does not require prior signal information. This results in an efficient and low complexity spectrum detector especially for dynamic spectrum occupancy scenarios. The performance of the proposed detector is exhibited by means of numerical simulations for probability of erroneous detection and receiver operating characteristic curves.

Because of the small energy available aboard a satellite, the power amplifier must achieve a very high power efficiency which suggest to work close to the saturation point. This would be power efficient, but unfortunately would add non-linear distortions to the communication channel. Several equalization algorithms have been proposed to compensate for this non-linear behaviour. The Echo State Network (ESN), an algorithm coming from the field of artificial neural networks, has also been proposed for this task but has never been compared to state-of-the-art equalizers for non-linear channel. The aim of this paper is to adapt the ESN to the satellite communication channel and to compare it to the baseband Volterra equalizer. We show that the ESN is able to reach the same performances as the Volterra equalizer, evaluated in terms of bit error rate, and has similar complexity. In addition, we propose a new training strategy for the ESN and the Volterra equalizer to improve their performance.

In satellite broadcast and broadband communication systems, it is desirable to relax as much as possible the complexity of terminals for feeder-to-user links. Pre-distortion algorithms are therefore considered at the transmitter side to compensate for the non-linear interference induced by the channel. In case of large channel lengths and multi-level constellations, remaining interference after pre-distortion may however still be significant. In this paper, we show that the system performance can be improved by combining a pre-distortion algorithm with a low-complexity turbo-equalization structure at the receiver side. This structure relies on the observation that the interference before pre-distortion and the remaining interference after pre-distortion are correlated.

In a multi-carrier non-linear satellite communication channel, inter-symbol interference (ISI) and adjacent channel interference (ACI) occur due to the non-linear power amplifier aboard the satellite. In order to prevent a too high performance degradation, large input back-offs (IBO) are generally considered. However, if all carriers are issued from the same ground station, pre-distortion of the whole transmitted signal can be a better solution to achieve higher power efficiency aboard the satellite and/or spectral efficiency. The relation between the symbols transmitted on the channel and the received symbols is tricky for a multi-carrier system, as it involves several symbol flows. Few approaches have been proposed yet to provide an efficient algorithm with reasonable complexity in such context. In this paper, we will derive a sub-optimum algorithm for the pre-distortion of a multi-carrier non-linear satellite channel which offers a good trade-off between performance and complexity.

Digital Video Broadcasting-Satellite-Second Generation (DVB-S2) is the current European standard for satellite broadcast and broadband communications. It relies on high-order modulations up to 32 amplitude/phase-shift keying (APSK) in order to increase the system spectral efficiency. Unfortunately, as the modulation order increases, the receiver becomes more sensitive to physical-layer impairments and, notably, to the distortions induced by the power amplifier and the channelizing filters aboard the satellite. The predistortion of a nonlinear satellite channel has been studied for many years. However, the performance of existing predistortion algorithms generally becomes poor when high-order modulations are used on a nonlinear channel with long memory. In this paper, we investigate a new iterative method that predis-torts the blocks of transmitted symbols to minimize the Euclidian distance between the transmitted and received symbols. We also propose approximations to relax the predistorter complexity while keeping its performance acceptable.

Cognitive radios impose challenges on the design of efficient signal detectors, including wide bandwidth sensing and large dynamic range support. The recently considered compressed sensing theory helps in relaxing the constraints on the design of the analog front-end. The maximum likelihood method introduced here is computationally simple since it does not require a signal reconstruction, unlike most methods introduced in the current literature. Moreover, the metric is optimum, works for any modulation scheme and is independent of the emitted signal knowledge and the number of occupied bands. The results are supported with Matlab simulations, a statistical study is performed and the probabilities of misdetection and false alarm are plotted for different scenarios, proving the efficiency of the estimator in a range of plausible SNRs and subsampling factors.

In cognitive radios systems, the sparse assigned frequency bands are opened to secondary users, provided that the aggregated interferences induced by the secondary transmitters on the primary receivers are negligible. In this paper, a decentralized Q-learning power allocation algorithm is proposed to maximize the Signal on Interference-plus-Noise Ratio (SINR) at the secondary receivers while meeting the primary protection constraint. Numerical simulations allow to compare the performance of the proposed algorithm with the performance of the optimal centralized power allocation scheme in the scenario of multiple independent secondary cells located on the border of a primary network protection contour. The impact of the definition of the learning algorithm cost function on the secondary user fairness and the system performance is discussed. The optimal execution frequency of the algorithm is obtained and different strategies for the exploration of new solutions are compared.

We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node through specific control channels. The coordinator node then combines the received information in order to make a decision about the primary network presence. In this paper, we compute analytically the probability density functions of the noise coming from the two-bits non-uniform quantization of the energy measure at each node and from the non-uniform bit flipping on the control channel. The quantization step and the bit flipping probabilities are selected to reduce the impact of the error. A new optimal fusion rule is proposed that takes into account the control channel noise distribution. Numerical simulations show that this new scheme outperforms the Maximum Ratio Combining scheme when different false alarm probabilities are used by the nodes.

In cognitive radio systems, the sparse assigned frequency bands are opened to secondary users. We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved in the presence of fading by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node. The coordinator node combines the received information in order to make a decision about the primary network presence. The primary network sensing times used by the cognitive nodes should be chosen high enough to ensure the correct detection of the primary emitter but low enough so that the nodes still have enough time to communicate. In this paper, we propose a decentralized Q-Learning algorithm to allocate the sensing times of the cognitive radios in a way that maximizes the throughputs of the radios. A rigorous proof of the convergence of the proposed algorithm is provided. Numerical results show that it converges faster to the same throughputs as those obtained with a reference algorithm.

Compared to classical spatial MIMO wireless systems, cross-polarized MIMO systems are an interesting way to reduce equipment size while still maintaining low inter-antenna correlation. In this paper, the time-variation of the polarization of the received waves is investigated. In this scenario, a theoretical formulation is proposed in order to obtain the parameters of the elliptical polarization, based on the signals received on three perpendicularly polarized antennas. A measurement campaign has been performed in an indoor-to-indoor scenario and at a frequency of 3.6 GHz. Different measurement positions are considered in a Line-Of-Sight (LOS) and a Non-Line-of-Sight (NLOS) scenario. Based on these measurements and the proposed theoretical formulation, the time-variation of the parameters describing the polarization ellipse is analyzed and a time-variant statistical model is proposed.

To enable frequency domain equalization of continuous phase modulations (CPM), a block construction that ensures cyclicity over each block without disrupting the phase continuity between them was proposed in . We formalize and prove the constraints that should be respected to enable the application of this technique to any CPM scheme.

The large bandwidth available at 60 GHz together with the resulting wavelength of only 5 mm allow the design of multi-Gbps wireless devices equipped with large arrays of tiny antennas. This enables wireless communication of large contents multimedia such as high-definition video. However, due to the high cost and power consumption of analog frond-end (AFE) chains at 60 GHz, it is practically infeasible to allocate a dedicated AFE to each antenna. Thus, it is highly desirable to design low complexity multi-antenna architectures in which an analog linear transformation (ALT) is carried out in order to reduce the required number of AFE chains for digital spatial processing, while minimizing the capacity loss. In this paper, we propose a non-iterative algorithm for joint transmit/receive (TX/RX) ALT. The proposed algorithm is designed with the aim of maximizing the capacity of the resulting reduced dimension MIMO system, assuming a frequency selective propagation channel.

In previous work, it has been observed that the specular and the diffuse component are linked in the angular domain. The idea of adding a diffuse component to each specular cluster has been proposed to model the specular-diffuse channel. In this paper, an approach is proposed to treat the specular and the diffuse measurement data simultaneously, with a clustering algorithm that is applied jointly on the specular and the diffuse component. The output of the clustering algorithm gives clusters that are characterized by their specular and their diffuse component. Measurement results are presented based on double-directional measurements, and parameter values are extracted using the proposed methodology.

In cognitive radios systems, the sparse assigned frequency bands are opened to secondary users. We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node. The coordinator node combines the received information in order to make a decision about the primary network presence. In this paper, we propose a decentralized Q-learning algorithm to share the sensing time among the cognitive radios in a way that maximize the throughputs of the radios. Numerical results show the convergence of the proposed algorithm and allow to discuss the exploration strategy, the choice of the cost function and the frequency of execution of the algorithm.

To improve the performance of a DVB-S2 communication channel, it is necessary to remove the non-linear interferences induced by the power amplifier. Due to the presence of filters in the channel, this non-linear interference is also interference with memory. One of the most used techniques to cancel out the interferences in this case is the order p compensation. The order p compensation can be mathematically described as a recursive algorithm. The non- linear interference is supposed to be smaller after each step of the algorithm. However this is not always the case and it is necessary to define upper bounds on the system to ensure convergence of the algorithm. Upper bounds were already defined for general nonlinear systems, but are however very inaccurate for the case of a DVB-S2 communication channel. In this paper, we will present two new methods to refine these upper bounds.

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

High order linear modulations, combined with coherent detection and signal processing at the receiver, are nowadays considered to reach the new capacity targets for the communications over the optical fibers. In order to reduce the computational complexity of the algorithms at the receiver, it has recently been proposed to compensate for the chromatic dispersion (CD) and polarization mode dispersion (PMD) in the frequency domain. Orthogonal frequency-division multiplexing (OFDM) and single- carrier with frequency domain equalization (SC-FDE) are two alternative coding strategies to support frequency domain signal processing. Compared to OFDM, SC-FDE is particularly interesting because it potentially facilitates the implementation of the transmitter and it generates a lower peak-to-average power ratio (PAPR) waveform. The goal of the present paper is to demonstrate how the SC-FDE system can further support polarization division multiplexing (PDM) to double the communication capacity. The SC-FDE PDM system is derived analytically and its performance is assessed by numerical simulations. It is shown that a 72 Gbps bit rate can be obtained in a 10 GHz bandwidth.

We address the problem of co-channel interference (CCI) in wireless mesh networks (WMNs). In such networks, multiple nodes communicate concurrently using the same time/frequency resources. This is recognized as the interference channel (IFC) because the CCI is a major impairment in such a scenario. To mitigate the CCI, non-cooperative beamforming techniques can be employed. Non-cooperative beamformers are simpler to implement than their cooperative counter-parts because they require neither synchronization nor the sharing of information data between the transmit nodes. In this paper, we then propose a non-cooperative beamforming scheme to improve the performance of WMNs with frequency-selective channels. We present an iterative algorithm that maximizes the signal-to-interference-and-noise ratio criterion over all subcarriers of the orthogonal frequency division multiplexing system. The performance of this algorithm is evaluated through simulations.

Multi-antenna architectures, where beamforming processing is shared between analog and digital, are of great interest for future multi-Gbps wireless systems operating at 60 GHz. In this spectrum band, wireless systems can integrate large antenna arrays in a very small volume thanks to a wavelength of about 5 mm and thus provide the required gain to meet the severe link budget. However, the cost and power consumption of an analog front-end (AFE) chain, that carries out translation between radio frequency (RF) and digital baseband, are too high at 60 GHz to afford one AFE for each antenna. In this paper, we consider low cost multi-antenna architectures with a lower number of AFE chains than antenna elements. We propose a joint design of transmit-receive mixed analog/digital beamformers that aim at maximizing the received average signal-to-noise-ratio (SNR). The proposed scheme shows better performance than state-of-art solutions, which combine antenna selection techniques and digital beamforming.

Polarized MIMO systems are an efficient solution for reducing inter-antenna correlation while maintaining compact terminal size. In this paper, a time-variant statistical channel model is proposed for tri-polarized antenna systems. The model is based on a coherent and a scattered component, where each component includes inter-channel correlation and cross-polar discriminations. The temporal variations of the channel are separated in slow and fast channel variations. A measurement campaign has been performed at 3.6 GHz to parameterize the model, in both static and mobile cases. A variant of the variogram technique has been adopted for extracting the slow-varying channel parameters. Experimental results are investigated and presented. The Doppler spectrum of the fast channel variations show fundamental differences between the static case and the mobile case. Finally, it is explained how the proposed model can be generated.

We consider the sensing of the frequency spectrum based on energy detection for cognitive radios. It has been shown that the reliability of the sensing can be improved by using several cooperating cognitive radios. In such a network, the cognitive nodes exchange their individual sensing information to a coordinator node through specific control channels. The coordinator node then combines the received sensing informations in order to make a decision about the primary network presence. In this paper, we assess the impact of the noise coming from the quantization of the energy measure at each node and from the imperfect communication on the control channels. We also propose two complementary approaches to compensate for the noise: the system designer can firstly reduce the noise impact by using an energy coding technique that smartly shares out the bit error probabilities and secondly compensate for the remaining noise by designing a new soft metric fusion rule at the coordinator node. Numerical simulations show that this new scheme significantly improves the performance compared to the MRC scheme in the presence of control transmission noise.

Compared to classical spatial MIMO wireless systems, cross-polarized MIMO systems are an interesting way to reduce equipment size while reducing the inter-antenna correlation. Cross-Polar Discrimination (XPD) and Co-Polar Ratio (CPR) are two important parameters describing multi-polarized channels. In this paper, the behavior of these parameters is investigated for different observation scales. A measurement campaign has been performed in both Outdoor-to-Indoor and Indoor-to-Indoor scenarios, at a frequency of 3.5GHz. Small-scale variations of XPD and CPR are analyzed in different spatial positions. The distance-related and large-scale variations of XPD and CPR are also investigated and a model is deduced.

Cognitive radios are devices capable of sensing a large range of frequencies in order to detect the presence of primary networks and reuse their bands when they are not occupied. Due to the large spectrum to be sensed and the high power signal dynamics, low-cost implementations of the analog front-ends leads to imperfections. Two of them are studied in this paper: IQ imbalance and sampling clock offset (SCO). Based on a mathematical system model, we study analytically the impact of the two imperfections on the sensing performance of the energy detector and of the cyclostationarity detector. We show that the IQ imbalance does not impact the performance of the two detectors, and that the SCO only impacts significantly the performance of the cyclostationarity detector.

Cross-polarized antenna systems are an attractive way to reduce equipment size while maintaining low interantenna correlation. In this paper, the polarization behaviour of indoor channels is investigated. A measurement campaign has been conducted at 3.6 GHz for a dual-polarized transmitter and a tri-polarized receiver in a non-Line-of-Sight (NLOS) scenario. The spatial and delay characteristics are extracted using a pertap beamforming algorithm. Distinct paths are isolated and the polarization of each wave is expressed in terms of its spherical components. The cross-polarization discrimination (XPD) of the wave is investigated as a function of its physical propagation parameters. The XPD of the wave is shown to be sensitive to spatial characteristics, while being insensitive to delay.

To enable frequency domain equalization (FDE) for continuous phase modulation (CPM), both cyclicity of individual symbol blocks and phase continuity between different blocks have to be guaranteed. In this letter, we present new block constructions that use a subblock of data-dependent symbols, called intrafix, to satisfy both constraints for different CPM-FDE systems: using either a cyclic prefix or a training sequence (TS), both for precoded and nonprecoded CPM. The known symbols of a TS can be used to improve synchronization and channel estimation. Precoding can be applied to a certain class of CPM schemes to halve the bit error rate.

Analog beamforming (ABF) with one scalar weight per antenna is an attractive technique for low-cost, low-power 60 GHz multi-antenna wireless communication systems. However, the design of the corresponding joint transmit and receive (Tx/Rx) ABF optimization algorithms is still challenging in the case of multipath channels due to the constraint of having only one scalar weight per antenna. In this paper, we aim at maximizing the average signal to noise ratio (SNR) at the input of the equalizer and analytically derive close-to-optimal Tx/Rx scalar weights. We show that the required channel state information (CSI) for joint Tx/Rx ABF weights computation is the inner product between all Tx/Rx channel impulse response pairs. Taking the channel length into account, a training-based estimation strategy of this CSI is proposed. Simulation results carried out in a typical 60 GHz multipath environment show that the proposed scheme outperforms the existing ABF schemes in term of BER performances.

We present a new scheme for maximizing the signal-to-noise ratio (SNR) in wideband multi-antenna receivers that employ time-interleaved analog-to-digital converters (ADCs). Current wideband receivers interleave a fixed number of slower ADCs into one fast ADC and assign this latter to one antenna according to an antenna selection algorithm. However, this does not always guarantee an optimal trade-off between thermal noise and quantization noise. This results in an overall SNR that is lower than what could be obtained with the same number of ADCs, assigned in a more optimal way. Therefore, we propose to adjust the number of slower ADCs assigned to a certain fast, interleaved ADC dynamically, according to the SNR of every individual antenna. Our proposed algorithm can be implemented at the expense of a very limited hardware complexity increase. The SNR gain of our new scheme can exceed 7 dB, depending on channel conditions and ADC specifications.

info:eu-repo/semantics/published

A cluster-based channel model is presented that includes polarization characteristics. Measurements have been carried out in an indoor environment at 3.6 GHz using a dual-polarized transmitter and a tri-polarized receiver. Individual propagation paths are extracted using the SAGE algorithm, and a cross-polar discrimination (XPD) per ray is defined. Clusters are identified in the co-elevation-azimuth-delay domain, with an automatic clustering algorithm. The cluster properties are investigated and polarization characteristics are identified on a per-cluster basis. Finally, the obtained model is simulated and extraction-independent parameters are compared with experimental parameters for validation.

This paper investigates the polarization behaviour of indoor multi-polarized MIMO channels at 3.6 GHz. Measurements have been carried out in non-line-of-sight (NLOS) and line-of-sight (LOS) using a dual-polarized transmitter and a tri-polarized receiver. The spatial and delay characteristics are extracted using a per-tap beamforming algorithm. Distinct waves are isolated and the polarization of each wave is expressed in terms of its spherical components. The evolution of the waves polarization is investigated as function of its physical propagation parameters. The polarization of the waves is shown to be sensitive to spatial characteristics, while being insensitive to delay. Direct line-of-sight rays show to have higher XPD than in the NLOS case, while the reflected rays have a similar XPD than in a NLOS case.

In this paper, we develop a new low-complexity linear frequency domain equalization (FDE) approach for continuous phase modulated (CPM) signals. As a CPM signal is highly correlated, calculating a linear minimum mean square error (MMSE) channel equalizer requires the inversion of a nondiagonal matrix, even in the frequency domain. In order to regain the FDE advantage of reduced computational complexity, we show that this matrix can be approximated by a block-diagonal matrix without performance loss. Moreover, our MMSE equalizer can be simplified to a low-complexity zero-forcing equalizer. The proposed techniques can be applied to any CPM scheme. To support this theory we present a new polyphase matrix model, valid for any block-based CPM system. Simulation results in a 60 GHz environment show that our reduced-complexity MMSE equalizer significantly outperforms the state of the art linear MMSE receiver for large modulation indices, while it performs only slightly worse for small ones.

One of the techniques for spectrum sensing is the energy detection of signals from primary transmitters. However, when detecting in a certain frequency band, this technique suffers from the random fading introduced by the channel. This problem can be alleviated by the use of multiple antennas introducing spatial diversity. The performance of the energy detector with multiple antennas has already been analytically analyzed for flat fading channels. In this paper, we propose analytical expressions for the performance of multi-antenna energy detector with multi-paths fading channels. These expressions will enable to compare for different channel power profiles the gains brought by the two sources of diversity: spatial (or antenna) diversity and multi-path diversity. This analytical performance is compared to simulations to show the validity of the used approximations.

Continuous phase modulations (CPM) have a perfectly constant envelope and are inherently robust against analog front-end nonidealities. Therefore, they have recently been proposed for several modern wireless standards. In this paper, we further develop an existing high-performance frequency domain equalization approach for CPM signals. First, we introduce a polyphase matrix model, valid for any block-based CPM system, which has clear advantages compared to existing models. Second, the model is used to reduce the complexity of the existing minimum mean square error channel equalizer. The proposed technique can be applied to any CPM scheme. Simulation results in a 60 GHz environment confirm that it does not cause any noticeable performance degradation.

In this paper, we present an analytical analysis to predict the power spectral density (PSD) at the output of a nonlinear power amplifier (PA). We focus on offset quadrature phase shift keying (OQPSK) waveform band-limited by a square root raised cosine (SRRC) filter. This is one of the waveforms used in wideband code division multiple access (W-CDMA) wireless standard. We show that the PA output PSD obtained by our analytical analysis matches well the simulated PSD. Furthermore, we compare the PA output PSD of QPSK and OQPSK waveforms as a function of the SRRC filter roll-off. We conclude that for small roll-off, both QPSK and OQPSK experience almost the same level of spectral re-growth. As the roll-off increases, OQPSK becomes less sensitive to PA nonlinearity relative to QPSK.

We show how to apply Frequency Domain Equalization (FDE) to precoded Continuous Phase Modulation (CPM) systems. It is well known that differential precoding can be applied to the specific, popular class of CPM schemes with modulation index h = 1/2Q, where Q is any integer. This precoding halves the bit error rate (BER) compared to nonprecoded CPM without any overhead or complexity increase. We apply FDE to a block-based precoded CPM system. Therefore, we show that in addition to a cyclic prefix, two subblocks of data-dependent symbols have to be inserted in each block to cope with the memory in the CPM signal and to enable correct decoding by the receiver. We explain how to calculate these subblocks. Simulation results in a 60 GHz environment confirm that the BER is halved by precoding, and that this precoding is compatible with FDE using our new technique.

We present a new symbol block construction which yields a cyclic continuous phase modulated (CPM) signal to enable frequency domain equalization. It is known that in addition to a cyclic prefix, a subblock of data-dependent symbols has to be inserted in each block to cope with the memory in the CPM signal. We propose a new subblock, called intrafix, valid for any CPM scheme. Our intrafix is shorter than what is currently known in the literature, reducing the overhead. Moreover, it can be calculated on a per-block basis, without knowledge of previous blocks. We also prove that there are constraints on the length of both the intrafix and the total block by studying the influence of the modulation index. Simulation results in a 60 GHz environment show that our new block construction satisfies all requirements.

Cross-polarized antenna systems are used to reduce equipment size in MIMO systems while still achieving low inter-antenna correlation. One fundamental parameter of cross-polarized MIMO systems is the cross-polar discrimination (XPD). This paper proposes a model to determine the XPD as a function of channel condition and under different antenna configurations. The environment is supposed to have a truncated Laplacian Power Angular Spectrum (PAS) that is widely used in standardization bodies. Antenna XPD is shown to be sensitive to different channel conditions, as well as to different receiver orientations. Measurements were conducted at 3.5 GHz to validate the theoretical model. Good agreement is obtained between theoretical XPD and experimental results.

The impulse response in a reverberation chamber is investigated from an experimental and theoretical point of view. A full description is thus proposed based on measurements and confirmed by means of theoretical insights. In particular, the K factor of each tap is emphasized. BER simulations for OFDM and single carrier frequency domain equalization (SC-FDE) systems are applied on this channel model and compared to the 802.11n channel model showing some differences mainly for the OFDM transmission.

This paper proposes a closed-form expression for the correlation coefficient and the cross-polarization discrimination (XPD) of a randomly oriented dual- or tri-polarized MIMO system. The environment is supposed to have a truncated Laplacian power azimuth spectrum that is widely used in standardization bodies. correlation and XPD are shown to be highly sensitive to receiver orientation, azimuth spread and environment depolarization behavior. Measurements were conducted at 3.5 GHz to validate the theoretical model. Good agreement is obtained between theoretical curves and experimental results for correlation and XPD when comparing at different receiver orientations.

Using wireless sensors worn on the body for pervasive monitoring is expected to become more and more common in the next years. The achievement of this application requires solving some challenges, especially in the power saving domain. In order to develop efficient power radio communications, an interesting investigation field is the multi-sensor MIMO (MS-MIMO) ultra-wideband (UWB) network. It is realistic to assume that each sensor carries one antenna, while the central device uses an antenna array. In this paper, a new analytical channel model for the diffracted waves mechanism is proposed. It is derived from the existing IEEE 802.15.4a standard channel model and innovates with space-time considerations.

New air interfaces are currently being developed to meet the high spectral efficiency requirements of the emerging wireless communication systems. In this context, OFDM is considered as a promising air interface candidate for both indoor and outdoor communications. Besides spectral efficiency and power consumption, the production cost of the transceiver should also be optimized. Direct-conversion radio frequency receivers are appealing because they avoid costly intermediate frequency hardware. However, they imply analog IQ separation, introducing a phase and amplitude mismatch between the I and Q branches. A communication system based on OFDM is sensitive to synchronization errors, such as CFO, and to front- end non-idealities, such as IQ imbalance. The goal of this paper is to use the iterative EM algorithm to acquire jointly the CFO and the IQ imbalance. The solution relies on a standard compliant repetitive preamble and does not require the knowledge of the propagation channel. Based on a second order approximation of the likelihood function, the complexity of the EM algorithm is significantly reduced. The algorithm is shown to perform extremely well: the estimates of the CFO and of the IQ imbalance converge to their ML estimate after less than 3 iterations. It outperforms state-of-the-art solutions significantly and suffers from a lower computational complexity. While the CFO estimate is robust against variations of the SNR, the IQ imbalance estimate accuracy is reduced at values of the SNR below 10 dB and above 35 dB.

A new approach for frequency-domain equalization of continuous phase modulated (CPM) signals is presented. In contrast with state-of-the-art receivers, we separate channel equalization on the one hand and CPM demodulation on the other. This separation enables us to calculate independently of the CPM scheme a new low-complexity zero-forcing channel equalizer. We also present a new high-performance minimum mean square error (MMSE) channel equalizer for any CPM scheme and a method to lower its complexity for a popular class of CPM schemes. Simulations show that our new MMSE equalizer significantly outperforms state-of-the-art linear receivers in a 60 GHz multipath environment.

Single-carrier with cyclic prefix (SC-CP) is seen as an interesting air interface to replace orthogonal frequency- division multiplexing (OFDM) because it features a lower peak- to average power ratio (PAPR) while still allowing low complexity frequency domain equalization (FDE). Both air interfaces are highly sensitive to phase noise (PN) that degrades their system performances. In this paper, we study and compare analytically the PN impact on both air interfaces. Simulations are also carried out to validate the analytical results. PN causes the same common phase error (CPE) on both air interfaces, as well as it leads to Inter-Carrier Interference (ICI) in OFDM and inter-symbol interference (ISI) in SC-CP. However OFDM is found to be slightly less affected than SC-CP in both flat channels and frequency selective channels. It is shown also that CPE is the dominate impact if the PN cut-off frequency is smaller than the subcarrier spacing.

Advanced adaptive filters have been shown to be very powerful for tracking time varying channels in various wireless communications system. However, the performance comes at the expense of highly resource-demanding implementations, especially in the context of programmable architecture based SDR. We present the optimizations for programmable implementation of QRD based SRI-RLS, which represents a large family of advanced adaptive filters. The key contribution of our work is to comprehensively and systematically remove the redundant operations in the QRD for SRI-RLS. Although most signal processing and scientific libraries implement householder reflection based QRD, we explore different alternatives and then choose given rotations based QRD to enable the aforementioned systematic redundancy removals. Our work significantly reduces the resource requirements (cycle count, energy consumption, etc.) of SRI-RLS implementation. Comparing to the widely accepted QRD implementation in numerical recipes, our work reduces 96.4% cycle-count on a typical baseband DSP (TI TMS320C6713), enabling efficient implementations. The paper shows that removing redundancy is very effective for modern statistical signal processing algorithms that largely rely on cascaded matrix operations.

Multilevel continuous phase modulated (CPM) signals feature a perfectly constant envelope, attractive spectral properties and excellent power efficiency. However, their non-linear nature makes them less tractable and their processing more complex. Fortunately, a linear decomposition exists, allowing to apply linear signal processing techniques. This decomposition was originally developed for binary CPM schemes only, and is not suited for schemes with an integer modulation index. It was extended to multilevel CPM schemes, by decomposing the multilevel input sequence in a product of binary subsequences, and applying the binary decomposition to these subsequences. When one or more of these subsequences has an integer modulation index though, this technique fails. We present a general solution, and prove how many pulses are needed to represent the CPM signal in this particular case. The decomposition of the quaternary 3RC system with h = 1/2 is given as an example. A receiver based on this solution is presented.

In order to meet the data rate and quality-of-service (QoS) requirements of the future cellular systems, new air interfaces are currently under development. In this paper, we compare two air interfaces of particular interest for the uplink: cyclic-prefix code-division multiple access (CP-CDMA) proposed in the literature as an evolution of direct-sequence code-division multiple access (DS-CDMA) because it enables the low complexity equalization of the multipath channel in the frequency domain, and single-carrier frequency-division multiple access (SC-FDMA), recently proposed in the long term evolution of the 3GPP standard because it enables the easy separation of the users in the frequency domain. We demonstrate analytically that SC-FDMA is a special case of CP-CDMA, in which the CDMA codes have been optimized to minimize the symbol estimation mean square error (MSE) under a constraint of received power. Numerical results show that SC-FDMA outperforms significantly CP-CDMA at high user loads. The transmit power necessary to fulfill the received power constraint is higher in case of SC-FDMA than in case of CP-CDMA when the carrier sub-sets are allocated randomly to the users, and lower when the carrier sub-sets are allocated in an optimized way.

New air interfaces are currently being developed to meet the high spectral efficiency requirements of the emerging wireless communication systems. In this context, OFDM is considered as a promising air interface candidate for both indoor and outdoor communications. Besides spectral efficiency and power consumption, the production cost of the transceiver should also be optimized. Direct-conversion radio frequency receivers are appealing because they avoid costly intermediate frequency hardware. However, they imply analog IQ separation, introducing a phase and amplitude mismatch between the I and Q branches. A communication system based on OFDM is sensitive to synchronization errors, such as CFO, and to front-end non-idealities, such as IQ imbalance. The goal of this paper is to use the iterative EM algorithm to acquire jointly the CFO and the IQ imbalance. The solution relies on a repetitive preamble and does not require the knowledge of the propagation channel. Based on a second order approximation of the likelihood function, the complexity of the EM algorithm is significantly reduced. The algorithm is shown to perform extremely well: the estimates of the CFO and of the IQ imbalance converge to their ML estimate after less than 3 iterations. While the CFO estimate is robust against variations of the SNR, the IQ imbalance estimate accuracy is reduced at values of the SNR below 10 dB and above 35 dB.

Nowadays a lot of effort is spent on developing OFDM- based inexpensive wireless transceivers. Direct-conversion radio frequency transceivers are appealing because they avoid costly IF analog components. This kind of transceivers imply analog RF I/Q separation. The mismatch between the analog components in the in-phase and quadrature branches introduces an unwanted in-band interference. Unfortunately, OFDM-based systems are very sensitive to I/Q mismatch, mostly when high order modulation schemes are applied. A digital compensation of this unwanted effect is required. In this paper, we developed a method for compensating the transmitter/receiver frequency-dependent I/Q imbalance jointly with the propagation channel in the frequency domain. Based on a low complexity ML channel estimator, a pilot design criterion is derived for channel and IQ imbalance coefficients estimation. An advanced equalizer is proposed which compensates for the frequency-dependent IQ imbalance. Both steps, estimation and compensation, are low cost in terms of implementation complexity. The proposed algorithm enables the system to achieve high SNRs.

The huge bandwidth available at 60 GHz will allow short range wireless communication to deliver bit rates over 1 Gbps. However the design of millimeter wave analog blocks is more critical than at lower frequencies, leading to a possible high non ideality of the radio front-end (FE). A suitable air interface for low cost, low power 60 GHz transceivers should thus use a modulation technique that has a high level of immunity to FE non-idealities. In this paper, we compare the sensitivity to FE non-idealities of two promising air interfaces namely offset quadrature phase shift keying (OQPSK) with frequency domain equalization (FDE) and continuous phase modulation (CPM) with time domain equalization (TDE). Our study focus on three main analog imperfections that are likely to have the biggest impact on the overall system performance: phase noise generated by the voltage control oscillator (VCO), clipping and quantization errors caused by the analog-to-digital converter (ADC) and non-linearity in the power amplifier (PA). Results show that CPM based air interface is more robust than OQPSK-based regarding the FE non-idealities. However the latter is less complex to design and offers much higher data rate than the former in the same bandwidth.

Changing user scenarios demand wireless connectivity among different standards. As a result, reconfigurability is becoming a key issue in the design of future wireless terminals. In analog front-ends, reconfigurable components are very expensive in terms of design cost and area. Bandpass sampling and digital front-end solutions in general, move the ADC closer to the antenna, avoiding most of the reconfigurable analog hardware. We consider the extreme case of bandpass sampling at RF and analyze the ADC requirements for a multi-standard radio. Two different models, one based on cascade analysis and the other on time-domain simulations, are used with a representative set of emerging wireless standards to derive the ADC requirements: sampling frequency, resolution and clock jitter. This study shows that, with modest RF filtering, RF bandpass sampling will soon become a reality for low power terminals.

Single-carrier code-division multiple access (SC-CDMA), also named cyclic-prefix CDMA in the literature, is a promising air interface for the uplink of the 4G cellular wireless communication systems. It enables the high capacity intrinsically offered by CDMA by making the equalization of the multipath channels and the mitigation of the resulting interference possible at a low complexity. This paper proposes a new air interface that combines SC-CDMA with space-time block coding (STBC) across multiple transmit antennas in order to make the link more robust. Contrary to existing air interfaces that perform the STBC at the chip level, making them only applicable to the downlink, the STBC is performed at the symbol level, making it also applicable to the uplink. In order to optimally detect the different antenna and user signals, a linear joint detector optimized according to the minimum mean square error (MMSE) criterion is designed. By exploiting the cyclic properties of the channel matrices, the complexity of the joint detector is significantly reduced. Furthermore, it is shown analytically that the inter-antenna interference is canceled out at the output of the first stage of the linear MMSE joint detector, consisting of a matched filter. By space-time coding the signal through two antennas at each transmit mobile terminal, a significant gain in signal-to-noise-ratio can be achieved. However, the spatial diversity gain of the proposed system is limited by the multiuser interference (MUI), that is increasing with the user load. Higher complexity non-linear receivers are needed to better compensate the MUI and still benefit from the spatial diversity at high user loads.

In fast mobile environments, the reception of orthogonal frequency domain modulation (OFDM) signals with tight sub-carrier spacing is challenged by the inter-carrier interference (ICI). This ICI must be compensated for by a suitable equalizer design, which requires the estimation of a larger number of parameters than for static environments. In addition, ICI also degrades the quality of the channel estimation. We propose an analytical approach to estimate the frequency domain channel matrix that relies on its nearly banded structure and a first order Taylor approximation of the channel variation. An additional constraint of this work is to accommodate OFDM systems with large number of sub-carriers and scattered pilots, such as used in DVB-T and DVB-H broadcast. We provide simulation results to demonstrate the performance of the proposed channel estimation method.

Quality-Energy scalability has been proved to be an effective technique toward the cost reduction for signal processing. However, although it has large potentials for reducing signal processing energy in wireless transceivers, it has not yet been applied to them. In this paper, we elaborate an example and present a feedback control scheme to achieve Quality-Energy scalability for the chip level equalization in High Speed Downlink Packet Access (HSDPA) receivers. In conventional equalizers, the coefficients are updated according to the worst-case assumption that the channel is very dynamic. In our proposed approach, we take into account the speed of the channel variation to adapt the updating frequency. Specifically, a low-complexity closed-loop controller is designed to vary the update-interval while limiting the maximum equalization error. The proposed control scheme takes high order channel statistics implicitly into account without the need for an explicit estimator. Simulation results show that the Quality-Energy scalability for the equalizer results in significant energy reduction with minor quality degradation for channels with large coherence times. Specifically, for a pedestrian channel, 60% of the signal processing operations, and hence energy, can be saved with only 0.25 dBBERloss.

Nowadays OFDM is combined with advanced multiple access and multiple antenna techniques in order to improve the link capacity. In this context, a lot of effort is spent on developing inexpensive wireless OFDM-based receivers. Direct-conversion radio frequency receivers are appealing because they avoid costly IF filters. This kind of receivers implies analog RF I/Q separation introducing an unwanted in-band image interfearence encedue to the mismatch between the in-phase and quadrature branches. Unfortunately, systems combining OFDM with multiple antennas and multiple access techniques are very sensitive to I/Q mismatch, mostly when high order modulation schemes are applied. A digital compensation of this un-wanted effect is required. In this paper, we propose a method for estimating jointly the frequency dependent I/Q imbalance and the propagation channel in the frequency domain. First the channel is estimated based on a pilot optimized to suppress the interference caused by I/Q imbalance. Second I/ C imbalance is estimated and compensated relying on the estimated channel. Both steps are low cost in terms of implementation complexity. Finally, it is shown that the performance of the channel estimate is not degraded by I/Q imbalance. The proposed algorithm enables the system to work at high SNRs.

In the context of 4G wireless mobile systems with direct conversion receivers, an new algorithm for carrier frequency offset (CFO) and IQ-imbalance estimation and compensation at the receiver is proposed. All processing for estimation and compensation of both CFO and IQ-imbalance is done in the time domain. Because the CFO is estimated while taking into account the presence of IQ-imbalance, a very precise estimate of the CFO can be obtained, even in the presence of large IQ-imbalance. The algorithm uses a repetitive low peak-to-average preamble sequence. At the transmitter, in order to improve the estimation result, an artificial CFO is digitally super-imposed on a part of the preamble sequence. The new algorithm yields better results than existing CFO estimation algorithms for SNRs where the IQ imbalance is dominant over the Gaussian noise. The structure of the preamble also allows an effective IQ-imbalance estimation.

New air interfaces are currently being developed to meet the high spectral efficiency requirements of the emerging wireless communication systems. Multicarrier code-division multiple access (MC-CDMA) is seen as a promising candidate for the fourth-generation (4G) cellular communication systems because it can interestingly deal with the multipath propagation at a low processing complexity. Besides spectral efficiency and power consumption, the production cost of the transceiver should also be optimized. Direct conversion radio frequency (RF) receivers are appealing because they avoid costly intermediate frequency (IF) filters. However, they imply RF IQ separation, introducing a phase and amplitude mismatch between the I and Q branches. A communication system based on MC-CDMA is sensitive to synchronization errors and front-end non-idealities because it uses a long symbol duration. The goal of this paper is to evaluate the impact of the carrier frequency offset, the sampling clock offset, and the IQ imbalance on the MC-CDMA downlink system performance, considering a receiver based on channel tracking designed to cope with high mobility conditions. It is demonstrated that part of the effects is compensated by the channel estimation and an expression of the variance of the remaining symbol estimation error is provided. For the cellular system and the target performance considered in this paper, specifications are defined on the non-idealities. The results are validated with bit-error rate simulations

Single-carrier code division multiple access (SC-CDMA), also named cyclic-prefix CDMA in the literature, is a promising air interface for the uplink of the 4G cellular wireless communication systems. It enables the high capacity intrinsically offered by CDMA by making the equalization of the multipath channels and the mitigation of the resulting interference possible at a low complexity. This paper proposes a new air interface that combines SC-CDMA with space time block coding (STBC) across multiple transmit antennas in order to robustify the link. Contrary to existing air interfaces that perform the STBC encoding at the chip level, making them only applicable to the downlink, the STBC encoding is performed at the symbol level, making it also applicable to the uplink. In order to optimally detect the antenna and user signals, a joint detector optimized according to the minimum mean square error (MMSE) criterion is designed. By exploiting the cyclo-stationarity of the channels, the complexity of the joint detector is significantly reduced. It is analytically shown that the inter-antenna interference is canceled out at the output of the first stage of the linear MMSE joint detector, consisting of a matched filter. Assuming typical outdoor channels, a gain of 4 dB signal-to-noise-ratio (SNR) is achieved by the use of two transmit antennas over the single antenna system.

New air interfaces are currently being developed to meet the high requirements of the emerging wireless communication systems. In this context, MC-CDMA is seen as a promising candidate for the 4G cellular communication systems since it can interestingly deal with the multipath propagation. The goal of this paper is to evaluate the impact of the carrier frequency offset, the sampling clock offset and IQ imbalance on the MC-CDMA downlink system performance, considering a receiver based on channel tracking designed to cope with high mobility conditions. It is demonstrated that part of the effects is compensated by the channel estimation and an expression of the variance of the remaining error is provided. For the setup considered in this paper, mostly IQ imbalance degrades the performance. On the other hand, the impact of sample clock offset is negligible with respect to the one of carrier frequency offset.

Single-carrier code division multiple access (SC-CDMA), also named cyclic-prefix CDMA in the literature, is a promising air interface for the up-link of the 4G cellular wireless communication systems. It enables the high capacity intrinsically offered by CDMA by making the equalization of the multi-path channels and the mitigation of the resulting interference possible at a low complexity. This paper studies the impact of multi-user sample clock offset on the performance of up-link SC-CDMA and proposes a compensation strategy at the receiver. It is shown that clock offset leads to an unacceptable degradation of the performance if it is not compensated. In a simultaneous multi-user up-link system, the sample clock offset is usually pre-compensated at the transmitters. This paper demonstrates that the compensation can also be done at the receiver. In a first step the optimal linear multi-user joint detector is designed according to the MMSE criterion, taking the effect of clock offset into account. In a second step the MMSE joint detector is simplified to a low complexity detector incurring a negligible loss of performance

In this paper, we compare high-performance OFDM and single-carrier with frequency-domain equalization (SC-FD) schemes using multiple-antennas and decision-feedback equalization (DFE), while also accounting for the power amplifier efficiency. To make a realistic comparison, we also consider most important digital imperfections such as channel and noise estimation, transmit and receive filtering, clipping and quantization as well as link layer impact. Our analysis shows that for frequency-selective channels, the relative performance impact of the power amplifier is negligible compared to the frequency diversity impact. The higher frequency diversity exploitation of SC-FD allows it to transmit more efficiently than OFDM in most cases. Therefore, SC-FD is a suitable candidate for broadband wireless communication, especially for battery-powered up-link transmission.

OFDM is a popular modulation scheme for broadband wireless communication. It elegantly handles multipath and has low complexity. Recently, single-carrier with frequency-domain processing (SC-FD) is gaining attention as a possible competitor for OFDM. It is based on the same principles and, therefore, it has similar multipath handling capabilities and low complexity. Moreover, SC-FD promises several other attractive advantages, such as power amplifier efficiency and inherent frequency diversity exploitation. Current performance comparisons do not consider these effects combined. We make the comparison in a realistic scenario considering both the power amplifier efficiency and frequency diversity. Our results show that, in a multipath environment, SC-FD can outperform OFDM by 4 dB, largely due to the better frequency diversity exploitation. Therefore, SC-FD is a good alternative to OFDM for battery-powered terminals, and is therefore especially suited for uplink communication.

The goal of this paper is to propose new binary training sequences that allow for optimal joint estimation of multiple channels by relying explicitly on the cyclo-stationary structure of the signals in the OFDM-based communication systems. The new estimator is perfectly suited for multiple-user MIMO types of communication systems where multiple channels have to he estimated simultaneously at each receive antenna. It is shown that the resulting estimator is not only optimal in the sense that it minimizes the channel estimation error variance, but also requires a very low complexity computational effort. Considering two different types of systems, it is shown that the proposed estimator allows for significant SNR gain in comparison to existing methods.

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

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

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

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

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

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

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