Partner selection in indoor-to-outdoor cooperative networks: an experimental study

In this paper, we develop a partner selection protocol for enhancing the network lifetime in cooperative wireless networks. The case-study is the cooperative relayed transmission from fixed indoor nodes to a common outdoor access point. A stochastic bivariate model for the spatial distribution of the fading parameters that govern the link performance, namely the Rician K-factor and the path-loss, is proposed and validated by means of real channel measurements. The partner selection protocol is based on the real-time estimation of a function of these fading parameters, i.e., the coding gain. To reduce the complexity of the link quality assessment, a Bayesian approach is proposed that uses the site-specific bivariate model as a-priori information for the coding gain estimation. This link quality estimator allows network lifetime gains almost as if all K-factor values were known. Furthermore, it suits IEEE 802.15.4 compliant networks as it efficiently exploits the information acquired from the receiver signal strength indicator. Extensive numerical results highlight the trade-off between complexity, robustness to model mismatches and network lifetime performance. We show for instance that infrequent updates of the site-specific model through K-factor estimation over a subset of links are sufficient to at least double the network lifetime with respect to existing algorithms based on path loss information only.Comment: This work has been submitted to IEEE Journal on Selected Areas in Communications in August 201

A personal, distributed exposimeter: procedure for design, calibration, validation, and application

This paper describes, for the first time, the procedure for the full design, calibration, uncertainty analysis, and practical application of a personal, distributed exposimeter (PDE) for the detection of personal exposure in the Global System for Mobile Communications (GSM) downlink (DL) band around 900 MHz (GSM 900 DL). The PDE is a sensor that consists of several body-worn antennas. The on-body location of these antennas is investigated using numerical simulations and calibration measurements in an anechoic chamber. The calibration measurements and the simulations result in a design (or on-body setup) of the PDE. This is used for validation measurements and indoor radio frequency (RF) exposure measurements in Ghent, Belgium. The main achievements of this paper are: first, the demonstration, using both measurements and simulations, that a PDE consisting of multiple on-body textile antennas will have a lower measurement uncertainty for personal RF exposure than existing on-body sensors; second, a validation of the PDE, which proves that the device correctly estimates the incident power densities; and third, a demonstration of the usability of the PDE for real exposure assessment measurements. To this aim, the validated PDE is used for indoor measurements in a residential building in Ghent, Belgium, which yield an average incident power density of 0.018 mW/m(2)

In-vehicle channel sounding in the 5.8-GHz band

The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3- to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample Kolmogorov-Smirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments.The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3- to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample Kolmogorov-Smirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments

Statistical millimeter wave channel modelling for 5G and beyond

Millimetre wave (mmWave) wireless communication is one of the most promising technologies for the fifth generation (5G) wireless communication networks and beyond. The very broad bandwidth and directional propagation are the two features of mmWave channels. In order to develop the channel models properly reflecting the characteristics of mmWave channels, the in-depth studies of mmWave channels addressing those two features are required. In this thesis, three mmWave channel models and one beam alignment scheme are proposed related to those two features. First, for studying the very broad bandwidth feature of mmWave channels, we introduce an averaged power delay profile (APDP) method to estimate the frequency stationarity regions (FSRs) of channels. The frequency non-stationary (FnS) properties of channels are found in the data analysis. A FnS model is proposed to model the FnS channels in both the sub-6 GHz and mmWave frequency bands and cluster evolution in the frequency domain is utilised in the implementation of FnS model. Second, for studying the directional propagation feature of mmWave channels, we develop an angular APDP (A-APDP) method to study the planar angular stationarity regions (ASRs) of directional channels (DCs). Three typical directional channel impulse responses (D-CIRs) are found in the data analysis and light-of-sight (LOS), non-LOS (NLOS), and outage classes are used to classify those DCs. A modified Saleh-Valenzuela (SV) model is proposed to model the DCs. The angular domain cluster evolution is utilised to ensure the consistency of DCs. Third, we further extend the A-APDP method to study the spherical-ASRs of DCs. We model the directional mmWave channels by three-state Markov chain that consists of LOS, NLOS, and outage states and we use stationary model, non-stationary model, and “null” to describe the channels in each Markov state according to the estimated ASRs. Then, we propose to use joint channel models to simulate the instantaneous directional mmWave channels based on the limiting distribution of Markov chain. Finally, the directional propagated mmWave channels when the Tx and Rx in motion is addressed. A double Gaussian beams (DGBs) scheme for mobile-to-mobile (M2M) mmWave communications is proposed. The connection ratios of directional mmWave channels in each Markov state are studied