This demo presents a hardware-in-the-loop (HiL) framework for validating and verifying wireless communication hardware under controlled and repeatable laboratory conditions. The setup integrates modems as transmitters and receivers with a real-time channel emulator. To simplify the hardware interfaces we exchange multi-path component parameters between the channel model and the radio channel emulator, following the proposed structure in the ongoing IEEE P1944 standardization for site-specific radio channel representations. The demo features an urban vehicular communication scenario, demonstrating the capability to replicate realistic propagation conditions with non-stationary propagation conditions. Our HiL test system allows dynamic motion changes of the vehicles based on the received data during the emulation process. Site-specific channel emulation enables the lab-based validation of realistic vehicular applications, 5G and 6G physical layer technologies, and the training and testing of AI/ML based receiver architectures.

Effective communication between vehicles and road users is essential for reducing accidents and congestion. Reli-able wireless communication is crucial for decision-making in advanced driver assistance systems and autonomous vehicles. In this work, we propose a convolutional neural network to predict the frame error rate in vehicle-to-infrastructure scenarios. Using a geometry-based stochastic channel model and hardware-in-the-loop emulation, we generate a dataset on which our model achieves 90 % validation accuracy. To adapt the model to new data, such as vehicle-to-vehicle scenarios, and to reduce computational costs for retraining the entire model from scratch, we explore methods like fine-tuning, transfer learning, and learning without forgetting (LwF). While these methods improve performance on new data, they reduce accuracy on the original data. To address this, we modify LwF by including some original data, achieving a balanced accuracy of 81.96%.

Next-generation wireless communication systems will incorporate millimeter wave (mmWave) as one of the key technologies to increase data rates. These forthcoming mmWave systems will integrate multiple-input multiple-output (MIMO) technology to ensure sufficient link margin and are expected to be deployed in conjunction with sub-6 GHz systems. Configuring a MIMO communication link usually relies on estimating channel state information (CSI), which is difficult to acquire at mmWave frequencies due to the low pre-beamforming signal-to-noise ratio (SNR). In this paper, we propose a novel approach to estimate mmWave MIMO channels by leveraging out-of-band information from a sub-6GHz band. Utilizing this approach, we develop three channel estimation methods and compare these methods with one using only in-band information. We investigate the influence of theK-factor, the SNR and the number of antennas on the performance of the proposed channel estimation methods through simulations. Additionally, we compare these methods in terms of their computational complexity. Finally, we validate the performance of the proposed methods through channel measurements conducted in an outdoor environment. The results demonstrate that the proposed methods outperform in-band mmWave channel estimation in terms of spectral efficiency, particularly in scenarios of low SNR and high K-factor.

Since the design of wireless MIMO systems requires knowledge of the double-directional (i.e., directionally resolved at both link ends) channel characteristics, and 5G/6G use higher frequency bands, there is the need for double-directional measurements in the mmWave spectrum, along with channel sounders that can accurately perform such measurements. This paper introduces a novel channel sounding approach based on a redirecting rotating mirror arrangement (ReRoMA). The method is low-cost and flexible as it requires only a single radio frequency chain at each link end and performs mechanical beamsteering. However, in contrast to existing rotating-horn systems, it physically separates the signal generation/transmission and the beam steering components, resulting in orders-of-magnitude faster measurements. The paper outlines the fundamental concept, describes details of the implementation, and demonstrates its application and accuracy using a 60GHz prototype for measurements in static reference scenarios, as well as dynamic measurements. We illustrate the detected propagation paths using dynamic angular and delay power spectra and correlate these findings with the surrounding environmental structure. Locations of environmental objects are detected within the Fourier resolution determined by bandwidth and horn width, with no noticeable degradation due to the faster measurements.

With the move towards 6G and associated technology deployment in higher frequency bands, measurements of directionally-resolved channels and sounders capable of performing such measurements are a necessity. In this paper, we present a new concept of channel sounding based on a Redirecting Rotating Mirror Arrangement (ReRoMA), capable of performing double-directional channel measurements at millimeter wave frequencies by mechanical beam steering orders of magnitude faster than existing rotating-horn arrangements. We present this new concept, describe a prototype operating at 60 GHz, and use it to perform, as proof-of-principle, a dynamic cart-to-cart channel measurements at a T-intersection scenario. We show that this sounding principle works and allows the directional evaluation of the channel. We visualize the different resolvable propagation paths in terms of dynamic angular and delay power spectrum, and relate them to the environmental geometry.

Cooperative connected automated mobility depends on sensing and wireless communication functions. With increasing carrier frequency both functions can be realized with the same hardware, however, the attenuation of radio signals increases quadratically with the carrier frequency. Hence, link setup becomes challenging in vehicular scenarios due to the required beam finding process. In this paper we investigate the multipath components of the vehicle-to-infrastructure (V2I) radio channel in three frequency bands with center frequencies of 3.2 GHz, 34.3 GHz and 62.35 GHz using measurement data with 155.5 MHz bandwidth and a sounding repetition rate of $31.25 \mu \mathrm{~s}$. The channel impulse responses are collected simultaneously at all three carrier frequencies. Using the high temporal sampling rate we apply the CLEAN algorithm, enabling the estimation of the weight, delay and Doppler frequency of multipath components. By analyzing the collinearity of the Doppler normalized scattering function between the frequency bands we found that the collinearity between the 3.2 GHz and 34.3 GHz band as well as between the 3.2 GHz and 62.35 GHz is smaller in the non-line of sight (NLOS) region but increases for the line-of-sight (LOS).

Reconfigurable intelligent surfaces (RISs) can provide a reliable and low-latency millimeter wave (mmWave) communication link in cases of a blocked line-of-sight (LoS) between the base station (BS) and the user equipment (UE). In such cases, the RIS mounted on a wall or ceiling can act as a bypass for the radio communication link. We present an active RIS with 127 patch antenna elements arranged in a hexagonal grid. The RIS operates at a center frequency of 23.8 GHz and each RIS element uses an orthogonal polarization transformation to enable amplification using a field-effect transistor (FET). The source and drain voltages of each FET are controlled using two bits. We consider that the RIS control unit is aware of the UE coordinates within the measurement area, relevant to the industrial control scenarios. We measure the received power on a 2D grid of $60 \mathrm{~cm} \times 90 \mathrm{~cm}$ using an $x y$-positioning table, with the RIS working in reflective and active mode. The results demonstrate the ability of the RIS to effectively focus the radio signal on the desired target points. We characterize the halfpower beam width in azimuth and radial directions with respect to the RIS position, enabling us to obtain a practical RIS configuration update criterion for a mobile UE. These results clearly show that RISs are prominent solutions for enabling reliable wireless communication in indoor industrial scenarios.

Reconfigurable intelligent surfaces (RISs) will play a key role to establish reliable low-latency millimeter wave (mmWave) communication links for indoor automation and control applications. In case of a blocked line-of-sight between the base station (BS) and the user equipment (UE), a RIS mounted on a wall or on a ceiling enables a bypass for the radio communication link. In this work, we present an active RIS for the mmWave frequency band. Each RIS element uses a field effect transistor (FET) to amplify the reflected signal and an orthogonal polarization transformation to increase the isolation between impinging and reflected radio wave. By switching the bias voltage at gate and drain of the FET we can establish four states for each RIS element: two reflection states with different phase shifts, an active amplification and an off state. We present results of the active RIS with 37 patch antenna elements arranged in a hexagonal grid for a center frequency of 25.8 GHz. The RIS field patterns obtained by numerical simulations and by empirical measurements in an anechoic chamber are compared. They show a good match and the received power is improved by 12 dB in the active mode of the RIS compared to the reflective mode.

Wireless vehicular communication will increase the safety of road users. The reliability of vehicular communication links is of high importance as links with low reliability may diminish the advantage of having situational traffic information. The goal of our investigation is to obtain a reliable coverage area for non-stationary vehicular scenarios. Therefore we propose a deep neural network (DNN) for predicting the expected frame error rate (FER). The DNN is trained in a supervised fashion, where a time-limited sequence of channel frequency responses has been labeled with its corresponding FER values assuming an underlying wireless communication system, i.e. IEEE 802.11p. For generating the training dataset we use a geometry-based stochastic channel model (GSCM). We obtain the ground truth FER by emulating the time-varying frequency responses using a hardware-in-the-loop setup. Our GSCM provides the propagation path parameters which we use to fix the statistics of the fading process at one point in space for an arbitrary amount of time, enabling accurate FER estimation. Using this dataset we achieve an accuracy of 85% of the DNN. We use the trained model to predict the FER for measured time-varying channel transfer functions obtained during a measurement campaign. We compare the predicted output of the DNN to the measured FER on the road and obtain a prediction accuracy of 78%.

Future vehicular communication systems will extend deployed frequency bands from sub-6 GHz to millimeter wave (mmWave). To investigate different propagation effects between sub-6 GHz and mmWave bands in high-mobility scenarios, we proposed a suitable testbed setup to compare these two bands in a fair manner. Experiments conducted using the proposed testbed provide realistic results, but they are only usable if they can be faithfully reproduced. To quantify the reproducibility of the proposed testbed, we perform channel measurements at center frequencies of 2.55 GHz and 25.5 GHz at a velocity of 50 km/h. We investigate the influence of antenna pattern, time between measurements, signal-to-interference-and-noise ratio (SINR) and signal bandwidth on the reproducibility in terms of the channel correlation.

In an world shifting towards wireless communications, the already scarce electromagnetic spectrum within the unlicensed bands is becoming increasingly crowded. All wireless devices operating in those bands need to co-exist without interfering with each other. Frequency hopping spread spectrum (FHSS) is a communication technique especially resilient to interference due to its constant change of the carrier frequency and its narrowband transmission bandwidth. Furthermore, it produces minimal interference to other signals in the same frequency band using wider bandwidth. However, interference can also be harmful even for FHSS transmissions as a result of the loaded ISM bands. Intelligent spectrum sensing techniques can contribute to a more efficient spectral usage. In this paper, we propose a supervised learning algorithm which predicts the future time-frequency location of a FHSS signal. We design a convolutional neural network which is trained on a dataset, obtained from measurements of two FHSS sources. Based only on a small observation window of 50 ms, it predicts the signal appearance of the following 25 ms in a time-frequency representation. To show that we can accurately predict the signal, we introduce a special score measure. The mean score of about 0.9 with small standard deviation demonstrates the high fidelity prediction of the signal’s evolution.

One of the key research directions to increase the capacity of new radio (NR) vehicle-to-everything (V2X) communication systems is extension of employed frequency bands from sub-6 GHz to millimeter wave (mmWave) range. To investigate different propagation effects between sub-6 GHz and mmWave bands in high-mobility scenarios, one needs to conduct channel measurements in both frequency bands. Using a suitable testbed setup to compare these two bands in a fair manner, we perform channel measurements at center frequencies of 2.55 GHz and 25.5 GHz, velocities of 50 km/h and 100 km/h, and at 126 different spatial positions. Furthermore, we conduct a comparative study of the multi-band propagation based on measurement results. We estimate the power delay profile (PDP) and the Doppler power spectral density (DSD) from a large set of measurements collected in a measurement campaign. Finally, we compare measured wireless channels at the two employed frequency bands in terms of root-mean-square (RMS) delay spread and RMS Doppler spread.

In recent years, the amount of unmanned aerial vehicle (UAV) based applications has strongly increased. In order to fly the UAVs safely, their command and control link needs a reliable and robust communication channel. A line of sight (LOS) between the UAV operator and UAV is, at the moment, an essential requirement to guarantee an error-free communication. However, even in LOS conditions, the reception of a constant signal level is not assured. In this paper, we present the results of a measurement campaign with a UAV and a drone moving on the ground that were electronically tracked with simultaneous dedicated beams at 3.2 GHz coming from a 10 element antenna array. Small software-defined-radio modules were integrated in the drones to record the strength of the received signal when moving. The instantaneous GPS coordinates of the UAV were transmitted via a 4G link to a ground station that translated them into spherical coordinates used at the antenna array side. We show that the UAV itself and its flying inclination produce around 10 dB fluctuations in the received power, even in LOS conditions, and therefore shadowing cannot be ignored.

In this paper we present a hardware-in-the-loop (HiL) framework for testing wireless vehicle-to-everything (V2X) communication hardware, i.e., modems under realistic channel conditions. The framework includes a wireless channel emulator, which is capable of emulating non-stationary wireless channels in real-time. We validate the HiL framework by comparing the frame error rate (FER) obtained via emulation with data obtained during a V2X measurement campaign using the same IEEE 802.11p based modems. To do this we acquire measured time-variant channel transfer function and FER measurements simultaneously. The results show that our HiL approach is feasible and that we can obtain FER measurements in the laboratory that closely match the measurement results obtained on the road, giving the maximal distance of 0.099 between their cumulative distribution functions.

In this paper we present dual-band massive multiple-input multiple-output (MIMO) channel measurements for a railway station scenario. The massive MIMO link shall provide an ultra-reliable low-latency communication link from the control center to the locomotive. In the measurement campaign the locomotive moves from line-of-sight (LOS) to non line-of-sight. We present dual frequency band measurements, where the massive MIMO array at the base station has 24 receive antenna elements at 1890 MHz and 8 receive antenna elements at 748 MHz. The measurement bandwidth is 20 MHz and we use a repetition rate of 1 ms to acquire the time-variant channel frequency response from the locomotive to all 32 antenna elements in parallel. We provide a first analysis of the root mean square (RMS) delay spread, the path loss coefficients and the channel hardening in both frequency bands. The measurements show that the RMS delay spread at lower frequencies is slightly smaller compared to higher frequencies, due to a stronger LOS component at lower frequencies. Furthermore, the results indicate that increasing the number of receive antennas in vertical domain, does not allow for better channel hardening and that lower frequencies allow for better channel hardening with the same amount of antennas.

This paper discusses a freely available and open dataset containing vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and vehicle-to-pedestrian (V2P) OFDM-based wireless channel measurement data including synchronised sensor data such as radar, LiDAR and high precision GPS. The wireless channel measurement is conducted at the carrier frequencies of 3.2 GHz and 5.81 GHz which are the most promising frequency bands in which future V2X communication systems will operate. The dataset contains the wireless channel measurement data of various V2X scenarios along with synchronized sensor information from a vehicle. In addition to the wireless channel measurement data, the dataset also includes frame error rate measurements from a IEEE 802.11p based communication system, synchronized to the other measurement data.

In this paper we present and discuss results of a wireless vehicle-to-vehicle (V2V) dualband channel measurement campaign at center frequencies of 3.2 GHz and 34.3 GHz in an urban street scenario. The measurement is conducted using a bandwidth of 155.5 MHz and a sounding repetition rate of 62.5 $\mu \mathrm{s}$ for both bands. At the transmitter side we use omni-directional antennas and at the receiver side directional antennas with 17° opening angles. With this setup, we present the first comparison of simultaneous and dynamic multiband V2V measurements using the time-variant power delay profile (PDP) and the Doppler spectral density (DSD). We find close similarities for the line-of-sight, specular as well as diffuse reflections in both frequency bands, enabling future work for out-of-band beam finding in vehicular mmWave systems.

In this paper we present a software defined radio (SDR) based measurement framework that allows for simultaneous measurements of wireless communication channels over multiple bands. We present and discuss results of a wireless vehicular-to-infrastructure multiband channel measurement campaign at center frequencies of 3.2 GHz, 34.3 GHz and 62.35 GHz in a street crossing scenario. The measurement is conducted using a bandwidth of 155.5 MHz and a sounding repetition rate of 31.25 μs. We compare the measurements using the time-variant power delay profile (PDP) and the Doppler spectral density (DSD).

In this paper we adopt and modify a well-known locality-aware hashing scheme to the problem of active stochastic scatterer selection in vehicular non-stationary geometry-based stochastic channel models (GSCM). We show, how under relaxed assumptions on the query set an efficient selection of active stochastic scatterers during simulation is computationally feasible. The proposed approach enables real-time simulation and emulation of large-scale GSCMs by restricting the active stochastic scatterer set to meet given resource constraints. We showcase our approach by introducing a GSCM that is boot-strapped via OpenStreetMap data. The stochastic scatterers are placed automatically along buildings, traffic signs and vegetation. We validate and investigate the impact of the proposed approach on the accuracy of a GSCM by means of second order statistics of the time- and frequency-varying fading process. For validation and performance evaluation we parameterize our GSCM using a vehicular wireless channel measurement campaign conducted in the inner city of Vienna. The impact of selecting only a subset of scatterers is then evaluated using the calibrated GSCM.

We present a mobile fronthaul methodology for the analogue optical transmission of native radio signals with integrated photonic true-time delay for the beam steering of phased-array antennas. Laser-based coherent homodyne detectors and the delay dissemination through ultra-dense wavelength division multiplexing ensure a low complexity at the optical layer. We experimentally demonstrate beamsteering for a linear phased-array antenna with a 1×3 configuration at 3.5 GHz carrier frequency and prove native radio signal transmission over the 14.3-km reach coherent optical fronthaul at a low end-to-end error vector magnitude of 3.3%. Experimental results are found to stand in good agreement with theoretical predictions.

We present a strategy to overcome channel aging and to enable massive multiple-input multiple-output (MIMO) in highly time-varying scenarios. Given the self-contained 5G slot structure, we introduce channel prediction methods for the down-link utilizing up-link reference symbols and investigate the prediction quality for synthetic and empirical high mobility channel measurement data. Further, we combine channel prediction with orthogonal precoding to decrease the bit error rate (BER) and allow longer prediction horizons. We show through link-level simulations that this framework exhibits a performance drop of only 1 dB compared to perfectly known channel state information for a velocity of 160 km/h at 3.5 GHz. We conclude the paper with a parametric BER study in dependence of the prediction/precoding horizon length.

In this paper we introduce the AIT ray tracer (RT) that is able to accurately simulate propagation effects of wireless communication channels. It covers the classical propagation mechanisms such as specular reflections, transmission and edge-diffraction. The novelty of our RT is that it allows to obtain correlated diffuse scattering and, thus, provides a time-variant Doppler spectral density. This is achieved by introducing a lattice-based surface tiling, which does not alter the position of the scattering points during simulation but provides high resolution diffuse scattering. The selection of the basis vectors for the finite lattice ensures that each ray falls into a separate delay bin (at least for first-order scattering). We implement our RT using the NVIDIA OptiX ray tracing engine, this enables us to trace a vast amount of rays in a single pass. We compare our RT simulations to a measurement conducted in a non-stationary urban intersection scenario achieving a near perfect match in terms of second order statistics.

Repeatable system-level test methods for vehicle-to-everything communication (V2X) are crucial in improving road safety and supporting connected autonomous driving. They rely on geometrical channel models that provide realistic signal propagation delays, Doppler shifts and path loss. In this work we focus on the validation of an OpenStreetMap (OSM) geometry based stochastic channel model (GSCM) that has a high degree of automation and low computational complexity. In an urban intersection scenario we compare the time-variant power delay profile (PDP) and Doppler spectral density (DSD) obtained from a measurement campaign to the ones obtained by the OSM-GSCM. Furthermore, we measure packet error rates (PER) of commercial modem hardware by connecting a transmitter and a receiver to the AIT channel emulator, i.e. using a hardware-in-the-loop (HiL) setup. We compare the PER obtained when the channel emulator uses the OSM-GSCM as input and when it uses the measured impulse responses. The OSM-GSCM path loss shows minor differences to the measurements due to the 2D structure of the OSM-GSCM, while the PER, PDP and DSD exhibit a good match between OSM-GSCM and empirical measurement data.

The advantages of measuring multiple wireless links simultaneously has been gaining attention due to the growing complexity of wireless communication systems. Analyzing vehicular communication systems presents a particular challenge due to their rapid time-varying nature. Therefore multi-node channel sounding is crucial for such endeavors. In this paper, we present the architecture and practical implementation of a scalable mobile multi-node channel sounder, optimized for use in vehicular scenarios. We perform a measurement campaign with three moving nodes, which includes a line of sight (LoS) connection on two links and non LoS(NLoS) conditions on the third link. We present the results on the obtained channel delay and Doppler characteristics, followed by the assessment of the degree of correlation of the analyzed channels and time-variant channel rates, hence investigating the suitability of the channel's physical attributes for relaying. The results show low cross-correlation between the transfer functions of the direct and the relaying link, while a higher rate is calculated for the relaying link.

This paper presents results obtained from a vehicle- to-vehicle channel measurement campaign carried out in the millimeter-wave band around a 60 GHz center frequency and with 8 GHz of bandwidth. We characterize a situation of two oncoming cars on a two-lane road in the campus of the Brno University of Technology. For several vehicle passes we evaluate: (1) observed root mean square (RMS) delay spreads as a function of the received power, (2) temporal decorrelation of the channel impulse response and (3) a dependency of the Pearson correlation coefficient on the received power. For the measurement campaign, a correlative time-domain channel sounder was used.

The performance of wireless communication systems is fundamentally determined by the properties of the underlying wireless communication channel. Vehicular communication channels exhibit time-variant multi-path propagation with non-stationary channel statistics. Thus, channel emulation tools for the reproducible test of wireless communication systems are urgently needed to enable the development of ultra-reliable low-latency communication links. In this paper we validate the vehicle-in-the-loop (ViL) test of vehicle-to-everything (V2X) communication links by means of time-variant channel emulation. The validation is performed by comparing the received signal strength indicator (RSSI) and packet error rate (PER) of measurements on a proving ground with the RSSI and PER obtained from ViL tests. For the ViL tests, the wireless communication channel is emulated using a geometry-based stochastic channel model, which is updated in real-time, dependent on the position and velocity of the vehicles. We collect results of different scenarios on the proving ground and from ViL tests. The results show an qualitative match between ViL test and measurement on the proving ground. An exact quantitative match can be obtained with the calibration parameters from the measurements.

This paper reports on a power-delay profile measurement campaign emulating a mobile vehicle-to-infrastructure urban-highway environment. The measured location is in the city of Brno, Czech Republic. Utilizing a correlative 50 GS/s time-domain channel sounder with a center frequency of 59.6 GHz and 8 GHz bandwidth and with open-ended WR15 waveguide antennas, we characterize the representative millimeter wave radio channels in terms of the RMS delay spread and its variability caused by mobile scatterers (i.e., vehicles). The RMS delay spread exhibits notable heteroscedasticity as its standard deviation can decrease by 40%. The measured high resolution power-delay profiles exhibit clustering behavior, where a typical number of reflected multipath components is four to five.

Ultra-reliable wireless communication links require the utilization of all diversity sources of a wireless communication channel. Hadani et al. propose a two dimensional discrete symplectic Fourier transform (DSFT) as orthogonal pre-coder for a time-frequency modulation scheme. In this paper we explore general orthogonal precoding (OP) and its performance in time- and frequency-selective channels. We show that iterative parallel interference cancellation (PIC) and iterative channel estimation methods can be used for the detection of OP. A scalar signal model for OP transmission is obtained by PIC. Based on this signal model, we can prove that all constant modulus sequences, e.g. the DSFT basis functions or Walsh-Hadamard sequences, lead to the same performance for OP. We validate our receiver structure by numerical link level simulations of a vehicle-to-vehicle communication link with a relative velocity of 0... 200 km/h, We demonstrate that OP achieves a gain of about 4.8 dB if compared to orthogonal frequency division multiplexing at a bit error rate of 10-4. Our performance results for coded OP are the best results for a fully documented receiver architecture, published so far.

The performance of wireless communication systems is fundamentally determined by wireless communication channel properties. Wireless vehicular communication channels exhibit multipath propagation and non-stationary channel statistics. Methods and tools for the repeatable test of wireless communication systems and signal processing algorithms in such environments are urgently needed to enable the development of reliable communication links with low-latency. In this paper we present the measurement and validation of a real time channel emulation method for non-stationary vehicular scenarios based on a geometry-based stochastic channel model.

Multi-Gb/s visible-light communication is demonstrated using a commercial off-the-shelf resonant-cavity light emitting diode (LED), which is originally rated for 150 Mb/s. By applying analog frequency response equalization and multi-carrier modulation schemes, a transmission capacity of up to 4.3 Gb/s is obtained over a single wavelength in a close-proximity scenario. Nyquist-shaped multi-band modulation and orthogonal-frequency-division multiplexing are applied with high spectral sub-carrier efficiencies of up to 8 b/symbol. The transmission rate is experimentally investigated as a function of the loss budget and further related to link reach based on free-space measurements under clear weather conditions. Analog signal transmission is also validated using real-time signal (de-)modulation with a high-definition video payload. We further demonstrate that on/off keying in combination with simpler baseband modulation can be facilitated for data rates of up to 750 Mb/s. This proves that commercially available LEDs can serve as a versatile low-cost transmitter. Finally, the joint transmission of energy and data has been validated. A power feed with an irradiance of 240 W/m2is experimentally shown to enable a remotely supplied optical burst receiver for periodic access to Gb/s data rates.

Reliable connectivity between vehicles is a requirement for efficient overtaking warning systems. We investigate the 6 GHz propagation channel between oncoming vehicles with five different types of large obstructing vehicles in a poor scattering environment. The presented channel gains emphasize the advantages of different antenna positions and the difference between a straight road and curved road. We conclude that connectivity ranges on a straight road are close to the minimum distance required by a warning system. We furthermore conclude that the channel gain of antennas mounted inside the vehicle can be higher compared to antennas mounted on the roof, which can increase the connectivity range significantly.

The next digital subscriber line (DSL) generation, called G.fast, extends the frequency band up to 212MHz and achieves Gigabit data-rates. Vectoring technology cancels the performance-limiting crosstalk among DSL lines on a signal level, but requires co-located line termination. Differently, dynamic spectrum management level 2 (DSM-L2) coordinates the transmit power spectra among interferers and thus, does not require all line termination units to be co-located. In this work we analyze the data-rates of G.fast under full vectoring, partial vectoring restricted to groups of users, and non-vectoring scenarios. We also propose interference alignment (IA) as an alternative method to DSM-L2 for dealing with the interference in G.fast and show that IA is superior to DSM-L2 in non-vectoring scenarios. Furthermore, we also propose time division multiple access (TDMA) for coordination of multiple vectoring groups in partial vectoring scenarios.

The fading process describing the propagation effects caused by scattering between two mobile transceivers shows strong non-stationary properties. For its characterization the local scattering function (LSF) and the instantaneous delay Doppler probability density function (pdf) have been introduced. In this paper, a relation between LSF and the joint pdf is investigated. In previous works, it was conjectured that a proportionality relationship between LSF and pdf might exist, similar to the relationship between the scattering function and the delay Doppler pdf in the wide-sense stationary uncorrelated scattering case. The goal here is to demonstrate this proportionality empirically based on the analysis of channel measurements. Both the LSF and the delay Doppler pdf can be combined in order to create a model for mobile-to-mobile (M2M) channels. The LSF is hereby used to process the measurement data and extract information like the stationarity time. With this information the joint delay Doppler pdf can be used to create a realistic simulation environment of the wireless channel for M2M communication systems.

Opportunistic interference alignment (OIA) exploits channel randomness and multiuser diversity by user selection. The transmitter needs channel state information (CSI), which is usually measured on the receiver side and sent to the transmitter side via a feedback channel. Lee and Choi show that d degrees of freedom (DoF) per transmitter are achievable in a 3-cell MIMO interference channel assuming a fully informed network, where every user feeds back a real-valued variable to their own transmitter. This paper investigates the achievable DoF using only 1-bit feedback per user. We prove that 1-bit feedback is sufficient to achieve the optimal DoF d. Most importantly, the required number of users for OIA with 1-bit feedback remains the same as with real-valued feedback. Moreover, for a given system configuration, we provide an optimal choice of the 1-bit quantizer, which captures most of the capacity provided by a system with real-valued feedback.

Sub-band divided ray tracing (SDRT) is one technique that has been extensively used to obtain the channel characteristics for ultra-wideband (UWB) radio wave propagation in realistic indoor environments. However, the computational complexity of SDRT scales directly with the number of sub-bands. Although we have proposed a low-complexity SDRT algorithm for one terminal position [1], the computational complexity is still extremely high when involving multiple mobile terminal positions. Moreover, some indoor positioning techniques require for high positioning accuracy data from measurements/simulations with a very fine spatial resolution. To cope with this, we propose an algorithm to reduce the computational complexity of SDRT for multiple mobile terminal positions. The algorithm uses a projection of all propagation paths on a subspace spanned by two-dimensional discrete prolate spheroidal (DPS) sequences at each sub-band. It is important to note that, since the geometrical information of the propagation paths is the same in all sub-bands, the subspace dimension and basis coefficients in frequency dimension do not need to be recalculated at different sub-bands. We justify the simplifications of the proposed method by numerical simulations. Furthermore, we evaluate the effect of antenna characteristics on the proposed algorithm. Our proposed algorithm reduces the computational complexity by more than one order of magnitude for indoor scenarios.

Intelligent transport systems (ITS) require low-latency dependable wireless communication links in between vehicles as well as between vehicles and the infrastructure. In vehicular communication scenarios communication channels are time- and frequency (doubly) dispersive and the channel statistics are non-stationary, i.e., they change over time. Hence, the design of appropriate channel estimators is challenging. Recently an adaptive reduced-rank channel estimation technique for non-stationary time-variant channel estimation was introduced by Zemen and Molisch, 2012. This technique uses a hypothesis test to obtain an estimate of the current channel statistics on a per frame basis. The optimum number of hypotheses is not known. In this paper we present new empirical insights on the optimum choice of the number of hypotheses for the hypothesis test for non-stationary time-variant channel estimation. With these considerations the complexity of an adaptive reduced-rank channel estimator can be reduced and its performance improved.

Urban intersections constitute an important safety-critical scenario for vehicle-to-vehicle communication. Based on measurements, this paper presents detailed investigations of the radio wave propagation processes in a typical urban intersection. We focus on one time instance of the propagation process and set up hypothesis for locations of the scattering objects. Multipath components (MPCs) are identified and an MPC tracking algorithm is applied. The number of MPCs and the lifetime of MPCs for this communication scenario are analyzed. It is concluded that the lifetime of an MPC is heavily dependent on its relative power, with typical values in the range 0.05-0.3 s corresponding to 0.5-3 m travel distance of the vehicles.

Opportunistic interference alignment (OIA) exploits channel randomness and multiuser diversity by user selection. In this paper, we address the major disadvantage of OIA which requires the feedback of the locally measured interference alignment from all users. We propose a selective feedback scheme for OIA by thresholding, where only a subset of users are required to send feedback to the transmitter. The proposed scheme can reduce the amount of feedback and still achieve the optimal degrees of freedom (DoF). We characterize the threshold and the corresponding feedback load to achieve the full DoF for a given signal-to-noise ratio. Both theoretical analysis and simulation results show that the amount of feedback can be dramatically reduced (by one order of magnitude at 20dB SNR and two orders of magnitude at 30dB SNR), while still preserving the essential DoF promised by conventional OIA with full feedback.

Vehicular communication channels are characterized by a non-stationary time- and frequency-selective fading process due to fast changes in the environment. We characterize the distribution of the envelope of the first delay bin in vehicle-to-vehicle channels by means of its Rician$K$-factor. We analyze the time–frequency variability of this channel parameter using vehicular channel measurements at 5.6 GHz with a bandwidth of 240 MHz for safety-relevant scenarios in intelligent transportation systems (ITS) . This data enables a frequency-variability analysis from an IEEE 802.11p system point of view, which uses 10 MHz channels. We show that the small-scale fading of the envelope of the first delay bin is Rician distributed with a varying$K$-factor. The later delay bins are Rayleigh distributed. We demonstrate that the$K$-factor cannot be assumed to be constant in time and frequency. The causes of these variations are the frequency-varying antenna radiation patterns, as well as the time-varying number of active scatterers, and the effects of vegetation. We also present a simple but accurate bimodal Gaussian mixture model, which allows to capture the$K$-factor variability in time for safety-relevant ITS scenarios.

Sub-band divided ray tracing (RT) has been widely used to reproduce as reliably as possible the ultra-wideband (UWB) radio wave propagation channel in realistic indoor environments. However, its accuracy is strictly limited by the available description of the environment. Moreover, its computational complexity scales with the number of selected subbands and the number of propagation paths. In the present work, our RT tool considers not only deterministic propagation paths but also diffuse scattering components. Based on a low-complexity sub-band divided RT implementation, we propose a calibration method for indoor UWB sub-band divided RT. The method estimates the optimal material parameters, including the dielectric parameters and the scattering parameters, using channel measurements and multiobjective simulated annealing (MOSA). This calibration can improve the accuracy of sub-band divided RT in terms of the power delay profile (PDP) and the root mean square (RMS) delay spread for all test locations including those not considered by the calibration. A measurement campaign is used to verify the calibration technique.

This contribution documents and discusses recent wideband radio channel measurements carried out in the intra-vehicle environment. Channels in the millimeter-wave (MMW) frequency band have been measured in 55-65 GHz using open-ended rectangular waveguides. We present a channel modeling approach based on a decomposition of spatially specific Channel Impulse Responses (CIRs) into the large and small scale fading. The decomposition is done by a Hodrick-Prescott filter. We parametrize the small scale fading utilizing Maximum-likelihood estimates for the parameters of a generalized extreme value (GEV) distribution. The large scale fading is described by a two dimensional polynomial curve. We also compare simulated results with our measurement exploiting two-sample Kolmogorov-Smirnov test.

Ray tracing has been extensively used to simulate indoor channel characteristics. For an ultra-wideband system, the channel characteristics vary significantly over the entire bandwidth. To cope with this, sub-band divided RT has been proposed by dividing the frequency of interest into multiple subbands and superposing the RT results at the individual center frequency of each subband. Thus, the computational complexity is directly proportional to the number of subbands. In this paper, we propose a mathematical method to significantly reduce the computational complexity of the sub-band divided RT, making it almost independent of the number of subbands. It is important to note that, based on our approach, not only the determination of the rays reaching a give location is made only once, but also the electromagnetic calculation of the received signal is not needed to perform repeatedly. The accuracy of low-complexity subband divided RT algorithm is verified through a measurement campaign.

Ray tracing (RT) is an accurate propagation prediction tool that has been widely used to simulate channel characteristics in indoor environments. To date, the developed RT tool includes not only specular reflection, penetration through dielectric blocks and diffraction, but also diffuse scattering mechanisms. The accuracy, provided by a detailed modeling of the environment, comes at the cost of a high computational complexity, which directly scales with the number of propagation paths considered. We are interested in simulating the radio propagation conditions for a mobile terminal, communicating in a frame based communication system indoors with several fixed nodes. This communication shall be used to obtain the position of the mobile terminal in indoor scenario. Therefore, the correlated temporal and spatial evolution of the channel impulse response is of utmost concern. In this paper, we propose a method to significantly reduce the computational complexity of RT by using a projection of all propagation paths on a subspace spanned by two-dimensional discrete prolate spheroidal (DPS) sequences. With this method the computational complexity can be reduced by more than one order of magnitude for indoor scenarios. The accuracy of our low-complexity DPS subspace based RT algorithm is verified by numeric simulations.

Dependable vehicular communications systems are a key requirement for the implementation of intelligent transportation systems (ITS). Multiple antenna receivers enable the utilization of spatial diversity to increase the reliability as well as improve the availability. The cost of a multiple antenna receiver is the increased hardware complexity due to multiple receive chains. In this paper we demonstrate that antenna selection for IEEE 802.11p allows to connect the antenna with the best instantaneous signal to noise ratio (SNR) to a single receive chain while maintaining the diversity gain. We extend the IEEE 802.11p frame structure by two short preambles to estimate the SNR for each receive branch. The numerical simulation results from our standard compliant link level simulation show a bit error ratio reduction from 8.159 · 10-3to 6.681 · 10-3at an SNR of 8 dB and from 4.688 · 10-5to 1.063 · 10-5at an SNR of 12 dB with antenna selection.

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 received 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.

Single receive antenna selection (AS) allows single-input single-output (SISO) systems to retain the diversity benefits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying channels, in which practical limitations imposed by next-generation wireless standards such as training, packetization and antenna switching time are taken into account. The proposed method utilizes low-complexity subspace projection techniques spanned by discrete prolate spheroidal (DPS) sequences. It only uses Doppler bandwidth knowledge, and does not need detailed correlation knowledge. Results show that the proposed AS method outperforms ideal conventional SISO systems with perfect CSI but no AS at the receiver and AS using the conventional Fourier estimation/prediction method. A closed-form expression for the symbol error probability (SEP) of phase-shift keying (MPSK) with symbol-by-symbol receive AS is derived.

The assumption of wide-sense-stationarity (WSS) and uncorrelated scattering (US) of wireless propagation channels is widespread for the design and analysis of wireless propagation channels. However, the assumption is only valid within a limited range. In this paper, we investigate the extension of this range not only in time (WSS), but also in frequency (US), for measured vehicular propagation channels. We do this by using the collinearity of the local scattering function, which is a bounded spectral distance metric, and thus allows us to set an indicative threshold, which in turn enables a WSS and a US test. We prove that the fading process in vehicular communications is strongly non-WSS, which agrees with results previously reported in the literature. Furthermore, for the first time (to the authors' knowledge), we show their non-US behavior as well, mainly in scenarios with rich scattering. The dimensions of the minimum stationarity region are on the order of 40 ms in time and 40MHz in frequency.

This work focuses on the signal to interference plus noise ratio (SINR) comparison of a relaying and a user cooperation strategy. For the relaying strategy we consider operator placed relays in each cell and power control is utilized in the source nodes to achieve a target SINR. For the cooperative strategy, user cooperation with coherent combining is utilized in order to meet a given target SINR at the receiver. Both cases are analyzed in a multi-cell scenario with a soft frequency reuse factor of 3. With 16QAM modulation and no cooperation only 80% of the users achieve the target SINR. We can show that with user cooperation 82% of all users achieve the target SINR and with relaying 98%.

In cyber-physical systems where sensors measure the temporal evolution of a given phenomenon of interest and radio communication takes place over short distances, the energy spent for source acquisition and compression may be comparable with that used for transmission. Additionally, in order to avoid limited lifetime issues, sensors may be powered via energy harvesting and thus collect all the energy they need from the environment. This work addresses the problem of energy allocation over source acquisition/compression and transmission for energy-harvesting sensors. At first, focusing on a single-sensor, energy management policies are identified that guarantee a minimum average distortion while at the same time ensuring the stability of the queue connecting source and channel encoders. It is shown that the identified class of policies is optimal in the sense that it stabilizes the queue whenever this is feasible by any other technique that satisfies the same average distortion constraint. Moreover, this class of policies performs an independent resource optimization for the source and channel encoders. Suboptimal strategies that do not use the energy buffer (battery) or use it only for adapting either source or channel encoder energy allocation are also studied for performance comparison. The problem of optimizing the desired trade-off between average distortion and backlog size is then formulated and solved via dynamic programming tools. Finally, a system with multiple sensors is considered and time-division scheduling strategies are derived that are able to maintain the stability of all data queues and to meet the average distortion constraints at all sensors whenever it is feasible.

Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying fading. By explicitly accounting for practical constraints imposed by the next-generation wireless standards such as training, packetization and antenna switching time, we propose a single receive AS method for time-varying fading channels. The method exploits the low training overhead and accuracy possible from the use of discrete prolate spheroidal (DPS) sequences based reduced rank subspace projection techniques. It only requires knowledge of the Doppler bandwidth, and does not require detailed correlation knowledge. Closed-form expressions for the channel prediction and estimation error as well as symbol error probability (SEP) of M-ary phase-shift keying (MPSK) for symbol-by-symbol receive AS are also derived. It is shown that the proposed AS scheme, after accounting for the practical limitations mentioned above, outperforms the ideal conventional single-input single-output (SISO) system with perfect CSI and no AS at the receiver and AS with conventional estimation based on complex exponential basis functions.

For a receiver that observes a mixture of desired and interfering multiple-input multiple-output (MIMO) transmissions, not all interference has the same severity: its effect is modulated by the degree of alignment between the eigenspaces of the desired and undesired channel matrices. An analytical channel model is proposed to account for this effect. Two metrics of eigenspace compatibility are studied, and a method to generate channels of a given degree of compatibility is derived. The resulting model is parameterized using radio channel measurement data, and an implementation recipe for immediate use of the model is provided.

The use of distributed space-time codes in cooperative communications promises to increase the rate and reliability of data transmission. These gains were mostly demonstrated for ideal scenarios, where all nodes are perfectly synchronized. Considering a cooperative uplink scenario with asynchronous nodes, the system suffers from two effects: timing errors and individual carrier frequency offsets. In effect, timing errors can completely cancel the advantages introduced by space-time codes, while individual carrier frequency offsets provide a great challenge to receivers. Indeed, frequency offsets are perceived as a time-variant channel (even if the individual links are static) in distributed cooperative communications. We show that using OFDM, space-time codes (STCs) become tolerant to timing errors. Channel estimation and tracking takes care of frequency offsets. Our simulations demonstrate that the bit error rate performance improves by an order of magnitude, when using a cooperative system design, which takes these two effects into account.

Inside a tunnel, electromagnetic wave propagation differs strongly from the well understood "open-air" situation. The characterization of the tunnel environment is crucial for deploying vehicular communication systems. In this paper we evaluate vehicle-to-vehicle (V2V) radio channel measurements inside a tunnel. We estimate the time-varying root mean square (rms) delay and Doppler spreads, as well as the excess delay and the maximum Doppler dispersion. The fading process in V2V communications is inherently non-stationary. Hence, we characterize the stationarity time, for which we can consider the fading process to be wide sense stationary. We show that the spreads, excess delay, and maximum Doppler dispersion are larger on average when both vehicles are inside the tunnel compared to the "open-air" situation. The temporal evolution of the stationarity time is highly influenced by the strength of time-varying multipath components and the distance between vehicles. Furthermore, we show the good fit of the rms delay and Doppler spreads to a lognormal distribution, as well as for the stationarity time. From our analysis we can conclude that the IEEE 802.11p standard will be robust towards inter-symbol and inter-carrier interference inside a tunnel.

In multiple-input multiple-output (MIMO) systems, the propagation channels can be characterized by their spatial structure, described by the (complex-valued) channel correlation. Accordingly, also interference in MIMO systems is likely to occur in a spatially structured, correlated way. We discuss that structured spatial interference affects mutual information under interference, depending on the eigenspace alignment between the channel of the desired signal and the channel carrying the interference. Intuitively, worst-case interference occurs, when the channels from the intended signal and the interference show a similar spatial structure. In contrast, least hurtful interference is encountered when these channels are maximally non-aligned. In this paper, we develop an analytical channel model generating multi-user MIMO channels with a given degree of severity of interference, described by the alignment of the channels' eigenspaces. Using radio channel measurements, we parameterize our model to reflect realistic scenarios.

The radio channels between nodes of an indoor peer-to-peer network show specific fast fading characteristics. Depending on the mobility and on the scattering properties of the environment, different kinds of fading distributions can occur: Ricean fading between static nodes, but also Rayleigh or even double-Rayleigh fading between mobile nodes. We investigate fast fading in indoor peer-to-peer networks based on radio channel measurements. It turns out that the fading statistics change over time. While the predominant fading mechanism is a combination of Rayleigh and double-Rayleigh fading, Ricean fading also occasionally occurs. On top of that, indoors, the statistics of the fast fading change over time even for small-motions of the nodes, since the propagation environment is inhomogeneous. We comprehensively model these effects using a hidden Markov model, parameterized from our measurements. The model is validated, revealing a convincing fit between the model and the measurements.

This paper deals with cooperative reconstruction of environmental variables (e.g., temperature) along a road by a vehicular sensor network using wireless communication. Vehicles take repeated measurements and approximate the environment using a set of basis functions. We investigate the applicability and performance of popular averaging techniques (gossiping and consensus propagation) on the basis coefficients, and propose a simpler approach to avoid divergence problems. We have developed a graphical simulation environment to study the behavior of different algorithms in this scenario and we show simulation results which support our simplified approach.

In scenarios with time-varying channels such as intelligent traffic systems or high speed trains, the orthogonality between subcarriers in orthogonal frequency division multiplexing (OFDM) is destroyed leading to inter-carrier interference (ICI). In the literature, ICI equalization algorithms have been proposed; however, they assume perfect channel knowledge at sample level. Unfortunately, existing channel estimation algorithms do not provide accurate channel estimates at high Doppler spreads, prohibiting data transmission with high spectral efficiency. In this paper, we propose an algorithm for ICI estimation that can be applied to OFDM systems with an arbitrary pilot structure. Thus, our algorithm can be applied to any already standardized OFDM system. Our ICI estimator models the channel variation by means of a basis expansion model (BEM). The performance of the estimator and of the subsequent equalization is evaluated in an UMTS long term evolution (LTE) link level simulator. In a Rayleigh fading scenario, the proposed algorithm allows a velocity increase of 150 km/h without throughput degradation. The gain in terms of the post-equalization signal to interference and noise ratio (SINR) is about 3.7 dB at a user speed of 300 km/h.

This work addresses the problem of energy allocation over source compression and transmission for a single energy-harvesting sensor. An optimal class of policies is identified that simultaneously guarantees a maximal average distortion and the stability of the queue connecting source and channel encoders, whenever this is feasible by any other strategy. This class of policies performs an independent resource optimization for the source and channel encoders. Analog transmission techniques as well as suboptimal strategies that do not use the energy buffer (battery) or use it only for adapting either source or channel encoder energy allocation are also studied.

To make transportation safer, more efficient, and less harmful to the environment, traffic telematics services are currently being intensely investigated and developed. Such services require dependable wireless vehicle-to-infrastructure and vehicle-to-vehicle communications providing robust connectivity at moderate data rates. The development of such dependable vehicular communication systems and standards requires accurate models of the propagation channel in all relevant environments and scenarios. Key characteristics of vehicular channels are shadowing by other vehicles, high Doppler shifts, and inherent nonstationarity. All have major impact on the data packet transmission reliability and latency. This paper provides an overview of the existing vehicular channel measurements in a variety of important environments, and the observed channel characteristics (such as delay spreads and Doppler spreads) therein. We briefly discuss the available vehicular channel models and their respective merits and deficiencies. Finally, we discuss the implications for wireless system design with a strong focus on IEEE 802.11p. On the road towards a dependable vehicular network, room for improvements in coverage, reliability, scalability, and delay are highlighted, calling for evolutionary improvements in the IEEE 802.11p standard. Multiple antennas at the onboard units and roadside units are recommended to exploit spatial diversity for increased diversity and reliability. Evolutionary improvements in the physical (PHY) and medium access control (MAC) layers are required to yield dependable systems. Extensive references are provided.

Cooperative transmission techniques for ad hoc and wireless sensor networks are known to increase the network lifetime. Indeed, the improved spatial diversity allows a more efficient energy usage. Under the Rayleigh fading assumption, the selection of cooperative partners is typically based on the knowledge of the average channel power. However, Rayleigh fading is not a suitable model in a large number of practical scenarios, in particular for indoor-to-outdoor applications. In these scenarios additional information of the fading distribution is needed for partner selection. The main focus of this work is to provide an analytical framework to evaluate the impact of the fading statistics on partner selection algorithms. A distributed multi-link channel model is derived from indoor-to-indoor and indoor-to-outdoor channel measurements in order to simulate practical scenarios where the proposed analytical framework is tested. Finally, we introduce a novel partner selection strategy that exploits the distributed knowledge of the effective coding gains provided by the wireless links fading statistics.

In this paper we analyze the Ricean K-factor for vehicle-to-vehicle (V2V) communications in a typical open sub-urban street crossing. The channel conditions vary from non line-of sight (NLOS) to line-of-sight (LOS). The antenna arrays used for recording the radio channels consist of 4 elements with directional radiation patterns. We measured 16 individual single-input single-output channels, with a bandwidth of 240MHz for a duration of 20 s. We performed two kind of evaluations. For the first analysis we partitioned the 240MHz bandwidth into 24 sub-bands with 10MHz each, according to 802.11p. The small-scale fading of the first delay bin is Ricean distributed with a time-varying K-factor. The later delay bins are mostly Rayleigh distributed. We observe that the large/small K-factor values are not necessarily correlated with the received power. We show that the K-factor can not be assumed to be constant in time, frequency, and space. The antenna radiation patterns, and the illuminated objects by them at different time instances are the cause of these variations. The second evaluation considers the 240MHz bandwidth, and the narrow-band K-factor is calculated for each frequency bin, with Δf = 312 kHz. We corroborate the need to consider the frequency variation of the K-factor. We conclude that a multi-dimensional varying K-factor models the large-scale statistical behaviour more accurately than a constant K-factor.

Vehicle-to-vehicle (VTV) communications are of interest for applications within traffic safety and congestion avoidance, but the development of suitable communications systems requires accurate models for VTV propagation channels. This paper presents a new wideband MIMO (multiple-input- multiple-output) channel model for VTV channels based on extensive MIMO channel measurements performed at 5.2 GHz in rural environments in Lund, Sweden. The measured channel characteristics, in particular the non-stationarity of the channel statistics, motivate the use of a geometry-based stochastic channel model (GSCM) instead of the classical tapped-delay line model. We introduce generalizations of the generic GSCM approach and find it suitable to distinguish between diffuse and discrete scattering contributions. The time-variant contributions from discrete scatterers are tracked over time and delay using a high resolution algorithm, and our observations motivate their power being modeled as a combination of a deterministic part and a stochastic part. The paper gives a full model parameterization and the model is verified by comparison of MIMO antenna correlations derived from the channel model to those obtained directly from measurements.

Non wide-sense stationary (WSS) uncorrelated-scatterering (US) fading processes are observed in vehicular communications. To estimate such a process under additive white Gaussian noise we use the local scattering function (LSF). In this paper we present an optimal parametrization of the multitaper-based LSF estimator. We do this by quantizing the mean square error (MSE). For that purpose we use the structure of a two-dimensional Wiener filter and optimize the parameters of the estimator to obtain the minimum MSE (MMSE). We split the observed fading process in WSS regions and analyze the influence of the estimator parameters on the MMSE under different lengths of the stationarity regions and signal-to-noise ratio values. The analysis is performed considering three different scenarios representing different scattering properties. We show that there is an optimal combination of estimator parameters for different lengths of stationarity region and signal-to-noise ratio values which provides a minimum MMSE.

Vehicle-to-vehicle (VTV) wireless communications have many envisioned applications in traffic safety and congestion avoidance, but the development of suitable communications systems and standards requires accurate models for the VTV propagation channel. In this paper, we present a new wideband multiple-input-multiple-output (MIMO) model for VTV channels based on extensive MIMO channel measurements performed at 5.2 GHz in highway and rural environments in Lund, Sweden. The measured channel characteristics, in particular the nonstationarity of the channel statistics, motivate the use of a geometry-based stochastic channel model (GSCM) instead of the classical tapped-delay line model. We introduce generalizations of the generic GSCM approach and techniques for parameterizing it from measurements and find it suitable to distinguish between diffuse and discrete scattering contributions. The time-variant contribution from discrete scatterers is tracked over time and delay using a high resolution algorithm, and our observations motivate their power being modeled as a combination of a (deterministic) distance decay and a slowly varying stochastic process. The paper gives a full parameterization of the channel model and supplies an implementation recipe for simulations. The model is verified by comparison of MIMO antenna correlations derived from the channel model to those obtained directly from the measurements.

In this work we explore the feasibility of implementing infrastructure-to-vehicle (I2V) communication through the UMTS infrastructure. We identify the problems that arise when providing I2V services on top of legacy UMTS networks as conceived in 3GPP Release 5 and consider an I2V architecture that exploits a new feature introduced by 3GPP Release 6, namely the multimedia broadcast/multicast services (MBMS). By means of an analytical model, we quantify the performance achievable with both releases in some realistic scenarios. We show that MBMS is able to provide I2V services efficiently on top of the UMTS network.

We focus on iterative detection for the uplink of a multi-carrier (MC) code division multiple access (CDMA) system based on orthogonal frequency division multiplexing (OFDM). The multiple-input multiple-output (MIMO) channel between each of the K users and the receiver is time-varying. At the receiver soft-symbol feedback is utilized for iterative linear minimum mean square error (LMMSE) channel estimation and multi-user detection after parallel interference cancelation. For multi-user detection we compare sphere decoding with an LMMSE detector. We show that a sphere decoder is more robust to channel estimation errors and less complex than an LMMSE detector while achieving better performance in terms of bit error rate versus signal to noise ratio.

We focus on sphere decoding for the uplink of a multi- carrier (MC) code division multiple access (CDMA) system based on orthogonal frequency division multiplexing (OFDM). The users move at vehicular speed, hence the multiple-input multiple-output (MIMO) channel from each user to the base- station is time-varying. The receiver at the base-station performs iterative multi-user (MU) detection using parallel interference cancelation followed by a sphere decoder. Such a MU-MIMO detector is less complex and more robust to channel estimation errors than a linear minimum mean square error (LMMSE) filter as was shown by the authors recently. However, for time-varying channels the complexity of the sphere decoder is still high, due to a QR-factorization for each symbol. In this paper we develop a novel implementation of the sphere decoder to reduce complexity. Time-limited snapshots of a bandlimited fading process span a subspace with very small dimensionality. The same subspace is spanned by prolate spheroidal sequences. Exploiting this specific structure we develop a new sphere decoding algorithm for time-varying channels that achieves considerable computational complexity reduction compared to a classical sphere decoder.

Car-to-car and car-to-infrastructure (henceforth called C2X) communications are constantly gaining importance for road- safety and other applications. In order to design efficient C2X systems, an understanding of realistic C2X propagation channels is required, but currently, only few measurements have been published. This paper presents a description of an extensive measurement campaign recently conducted in an urban scenario, a rural scenario, and on a highway. We focused on 4 x 4 multiple-input multiple-output (MHVIO) measurements at a center frequency of 5.2 GHz with high Doppler resolution. As first results from evaluating the measurement data we present the power-delay profile and the delay-Doppler spectrum from a selected, especially interesting measurement run from an urban measurement route. We observe dispersed Doppler contributions between zero and the Doppler shift corresponding to the relative speed of the cars, and very concentrated (in the Doppler domain), contributions from double reflections. Surprisingly, we also found paths with larger delays and zero Doppler shifts.

Iterative multi-user detection and time-variant channel estimation in a multi-carrier (MC) code division multiple access (CDMA) uplink requires high computational complexity. This is mainly due to the linear minimum mean square error (LMMSE) filters that are used for multi-user detection and time-variant channel estimation. Krylov subspace methods allow for an efficient implementation of the LMMSE filter. We show that a suitable chosen starting value, exploiting the iterative receiver structure, allows for a further speedup of the Krylov method. We achieve a complexity reduction by more than one order of magnitude. The Krylov subspace method allows a parallelization of the computations of the multi-user detector, while keeping the receiver performance constant. Numerical simulation results for a fully loaded system with K = 64 users are presented

We present the basic methodology for minimum-energy bandlimited prediction of time-variant flat Rayleigh-fading channels. This predictor is based on a subspace spanned by time-concentrated and bandlimited sequences. The concept of time-variant channel estimation using time-concentrated and band-limited sequences was introduced recently by Zemen et al. We extend this concept to the problem of time-variant channel prediction. Slepian showed that discrete prolate spheroidal (DPS) sequences can be used to calculate the minimum-energy bandlimited continuation of a finite sequence. DPS sequences are optimal for a time-variant channel with flat Doppler spectrum. We generalize the concept of time-concentrated and band-limited sequences to arbitrary Doppler spectra approaching closely the lower prediction error limit defined by the Wiener filter. In practical systems detailed channel covariance information is not available. We design a set of subspaces spanned by DPS sequences with fixed time-concentration but growing bandwidth. The best DPS subspace is selected dynamically for each observation interval using a Doppler bandwidth estimate allowing for low complexity channel prediction. The performance of the new predictor is compared to that of the Wiener filter by means of Monte Carlo simulations.

We consider the uplink of a time-variant multiple-input-multiple-output (MIMO) multi-user (MU) multi-carrier (MC) code division multiple access (CDMA) system. The linear minimum mean square error (LMMSE) filters for channel estimation and multi-user detection at the receiver side require too high complexity to be implementable in a system operating in time-variant channels. We develop a low-complexity implementation of an LMMSE filter based on the Krylov subspace method. We are able to reduce the computational complexity by one order of magnitude. Furthermore, in a system with K users having NTtransmit antennas, parallelization of the computations of the multi-user detector into KNTbranches is achieved as well as considerable storage reduction. We discuss more specifically a fully loaded system (the number of subcarriers N is equal to the number of users K) with NT= 2 transmit antennas per user, NR= 4 receive antennas and K = N = 64

Joint time-variant channel estimation and multi-user detection are key building-blocks for wireless broadband communication for mobile users at vehicular speed. We propose an iterative receiver for a multi-carrier (MC) code division multiple access (CDMA) system in the uplink. Multi-user detection is implemented through iterative parallel interference cancellation and conditional linear minimum mean square error (MMSE) filtering. MC-CDMA is based on orthogonal frequency division multiplexing (OFDM), thus time-variant channel estimation can be performed for every subcarrier individually. The variation of a subcarrier over the duration of a data block is upper bounded by the maximum Doppler bandwidth which is determined by the maximum velocity of the users. We exploit results from the theory of time-concentrated and bandlimited sequences and apply a Slepian basis expansion for time-variant subcarrier estimation. This approach enables time-variant channel estimation without complete knowledge of the second-order statistics of the fading process. The square bias of the Slepian basis expansion is one order of magnitude smaller compared to the Fourier basis expansion. The square bias of the basis expansion is the determining factor for the performance of the iterative joint channel estimation and data detection. We present an iterative linear MMSE estimation algorithm for the basis expansion coefficients in a multi-user system. The consistent performance of the iterative receiver using the Slepian basis expansion is validated by simulations for a wide range of velocities

In this work we compare the channel estimation algorithms for use in an iterative CDMA receiver in a block fading environment. The receiver consists of a soft multiuser data estimator, a bank of single user decoders, und a multiuser channel estimator. The multiuser data estimator is implemented as parallel interference canceler with unconditional post-MMSE filtering (PIC-MMSE) and the decoder is a soft-in soft-out MAP decoder. In the channel estimator we make use of dedicated pilot symbols and fed back soft-code symbols which are exploited as additional soft pilot symbols when the iterations proceed. We show that using extrinsic information increases the receiver performance significantly compared to using a posteriori information in the feedback for channel estimation. We introduce a linear MMSE (LMMSE) estimator which takes into account the variances of fed back code symbols and compare it to approximations of the least-squares (ALS) estimator and the linear minimum-mean-square-error (ALMMSE) estimator. Performance results are illustrated in terms of bit error rate (BER) and average normalized square error (ANSE) of the channel estimators. They show that the newly proposed LMMSE algorithm outperforms the ALS and ALMMSE algorithms.

In iterative receiver structures, soft information becomes available after the decoding stage. This information is used to enhance the quality of the channel estimates for the next iteration. We derive a generalized estimator based on the linear minimum mean square error (LMMSE) principle for deterministic pilot information combined with soft information. We present the special case of multi-carrier code division multiple access (MC-CDMA) in detail and provide simulation results. The presented channel estimation algorithm can be also applied to direct sequence (DS)-CDMA and multiple-input multiple-output (MIMO) systems.

Multi-carrier code division multiple access (MC-CDMA) systems are under intense investigation for high bit rate wireless communications systems. Their equalization is based on the fast Fourier transform, allowing for an efficient implementation. Iterative receivers with joint detection and decoding have been shown to achieve very good performance for direct-sequence (DS)-CDMA systems. We apply this concept to MC-CDMA, the multiuser detector is implemented as parallel interference canceller with post-minimum mean squared error filtering. In this contribution a new pilot based channel estimation scheme based on random time sequences is developed. The presented simulation results for a multi path scenario show, that in a fully loaded system with 64 users the single user bound can be approached up to 1 dB. A bit error rate (BER) of 10/sup -3/ is reached already at an E/sub b//N/sub 0/ of 12 dB with a 4 state, rate 1/2 convolutional code.