Invehicle channel sounding in the 5.8GHz band
 Pavel Kukolev^{1},
 Aniruddha Chandra^{1}Email author,
 Tomáš Mikulášek^{1},
 Aleš Prokeš^{1},
 Thomas Zemen^{2, 3} and
 Christoph F Mecklenbräuker^{4}
https://doi.org/10.1186/s136380150273x
© Kukolev et al.; licensee Springer. 2015
Received: 29 November 2014
Accepted: 9 February 2015
Published: 10 March 2015
Abstract
The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intravehicle and outofvehicle environments were carried out. It was observed that the largescale variations (LSVs) of the power delay profiles (PDPs) can be best described through a twoterm exponential decay model, in contrast to the linear models which are suitable for popular ultrawideband (UWB) systems operating in the 3 to 11GHz band. The smallscale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample KolmogorovSmirnov (KS) tests validated that the logistic distribution is optimal for incar, whereas the GEV distribution serves better for outofcar 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 incar as well as outofcar wireless applications in stationary environments.
Keywords
1 1 Introduction
1.1 1.1 Motivation
Vehicle area networks (VANs) and vehicular ad hoc networks (VANETs) generally refer to networks between cars and infrastructure points located along the road side [1,2]. These networks are aimed to deliver information about the traffic, to ensure safety of the passengers, and to provide driver assistance and passenger entertainment [3]. The majority of future vehicular networks are envisaged to conform with the IEEE 802.11p standard [4] described in wireless access in vehicular environments (WAVE) [5] and governed by a nonprofit organization, the car2car communication consortium (C2CCC) [6]. IEEE 802.11p standardizes signal transmission for vehicletovehicle (V2V) or vehicletoinfrastructure (V2I) communications, operated at a frequency band of 5.8 GHz [7].
Presently, there had been an upsurge in the interest of the automobile industries regarding wider applications of intravehicular wireless transmission. The use of wireless communication in the vehicle cuts down the wiring harness, which will reduce the weight and cost of the car. It also eliminates the need of drilling to pass the cables, thereby improving robustness of the vehicle, and will simplify the design as well as production processes. As mentioned earlier, the IEEE 802.11p protocol was specified primarily for V2V/V2I scenarios where both transmitter and receiver are placed outside the vehicle [8]. In order to realize fully integrated intelligent transportation systems (ITSs), it is important to evaluate the efficacy of the protocol for wireless connections in incar (both transmitter and receiver are inside the vehicle) and outofcar (transmitter is inside, and receiver is outside, or viceversa) scenarios as well.
1.2 1.2 Literature survey
There is a good number of open literature available that deal with vehicular channel measurement and modelling. We begin the list with [9], which provides a general review on advances and challenges in V2V channel measurement campaigns. The following papers, namely [1012], describe measurementbased narrowband channel models for different situations: on highways, in cities, and on country roads. Different aspects of nonstationary vehicular channel measurements in the frequency band of our interest are addressed in [13,14]. Reports from some intervehicular measurement campaigns in the 5.9GHz band are also made available in [15] and [16]. In particular, Cheng et al. [15] study the suitability of IEEE 802.11a for vehicular wireless links. Sen and Matolak [16] provide a wide set of power delay profile (PDP) measurements and proposed tapped delay line models based on Markov chains.
As far as intravehicular channel measurements are concerned, most of the articles are focused on ultrawideband (UWB) operating over a broad frequency spectrum of 3 to 11 GHz. For example, the performance of multiband orthogonal frequency division multiplexing (MBOFDM) in intracar communication is studied by Maehara et al. [17]. In [18], Schack et al. report a comparison of broadband channel sounding experiments over a different range of cars. Another interesting paper is by Niu et al. [19], where they describe a detailed UWB channel modelling campaign for intravehicular environments. The characterization of the 5GHz intravehicle communication channel is only attempted recently in [20], where the authors present power delay profiles, delay spread, and statistical channel models for a minivan and a bus.
Finally, in [21] and [22], the throughput and packet delivery performance of the IEEE 802.11p protocol is studied in V2V and V2I scenarios with different speeds of movement. However, to the best of our knowledge, none of the authors utilize the measured intravehicle channel models to evaluate the bit error rate (BER) for the IEEE 802.11p standard.
1.3 1.3 Contributions of the paper

Results for intravehicle and outofvehicle single input single output (SISO) channel measurements performed in the 5.875 to 5.885GHz frequency band.

Characterization of the LSV trends via a twoterm exponential decay model and the SSV random variations via logistic, normal, and generalized extreme value (GEV) distributions with the twosample KolmogorovSmirnov (KS) test.

Comparison of PDP decay trends of UWB and 802.11p for an identical measurement setup.

BER simulation for 802.11p using the measured channel data.
1.4 1.4 Organization of the paper
The paper reads as follows: Section 2 describes the measurement setup realized through a VNA. In Section, we provide a decay model to characterize the PDP, characterize the LSV trends, and find the optimal statistical distribution for the SSV. This section also includes a comparison between 802.11p and vehicular UWB channel characteristics. Next, the BER performance for the 802.11p standard is presented in Section 4. Finally, some conclusions are presented in Section 5.
2 2 Measurement setup
Measurements were performed with one transmitter (Tx) and three receiver (Rx) antennas in a righthand, fourdoor Skoda Octavia car with dimensions: 4.659 × 1.814 × 1.462 m. The vehicle was parked on the sixth floor in an underground garage of the Faculty of Electrical Engineering (FEKT), Brno University of Technology (VUT). Walls and floors of the garage premises are made of reinforced concrete, and they provide an environment that is free from narrowband interference. There were no parked cars on neighboring parking lots.
Equipments for recording data were placed outside of the vehicle. All doors and windows were closed, except the driver’s window, which was slightly open to pass the cables between the antennas and the recording equipment.
The schematic diagram of the setup for IEEE 802.11p frequency domain channel sounding is presented in Figure 3 [top] [23]. Real and imaginary parts of the transfer function (S _{ x1}) were exported to MATLAB. The frequency domain data over the entire bandwidth BW = 100 MHz were partitioned into 10 MHz bins, where each bin corresponds to a subchannel of 802.11p. All results were transformed from the frequency domain into the time domain, \(h(\tau)=\mathcal {F}^{1}H(f)\), utilizing the IFFT with a typical rectangular window. The PDP was calculated by averaging over ten subchannel timedomain data.
Detailed settings for measurements (Tx and Rx legends are shown in Figure 4 )
Measurement  TxRx  Tx  Rx  Remarks 

number  separation (m)  position  position  
1  0.53  2R  2R  LOS 
2  0.69  4R  4M  LOS 
3  0.74  2M  2L  LOS 
4  0.85  2M  2R  LOS 
5  0.87  2M  4M  LOS 
6  0.94  2R  2L  LOS 
7  1.26  4R  2R  NLOS 
8  1.28  2R  4M  NLOS 
9  1.41  4R  2L  NLOS 
10  1.86  0R  2L  Tx at an angle 
11  2.03  0M  2L  Tx in front 
12  2.08  0M  2R  Tx in front 
13  2.74  0R  2R  Tx at an angle 
14  3.15  0R  4M  Tx at an angle 
15  3.38  0M  4M  Tx in front 
3 3 Channel description
where τ _{ i } is the propagation delay, a _{ i } exp(j θ _{ i }) is the complex amplitude coefficient of the ith multipath component, δ(.) is the Dirac delta function, and N is the total number of multipath components.
The PDP is simply the squared channel impulse response P(τ)=h(τ)^{2}, and it includes LSV and SSV, which can be designated mathematically in the following manner: P(τ)=γ(τ)+ξ(τ), where γ(τ) denotes LSV and ξ(τ) is the SSV.
3.1 3.1 Largescale variations
The first term includes power from direct and major reflected rays, and the second term, with a very low slope (close to linear), reflects the power from diffused multipath components. This exponential model (2) offers more flexibility compared to singleterm exponential or linear models. Further, it also avoids discontinuities in the extracted LSVs, which are present when one attempts to divide the PDP into two (or more) delay parts and tries to fit individual expressions for each of these parts [27].
The MSE is 6.59×10^{−5}, averaged over all the M=15 measurements.
Parameter values for LSV
TxRx  Parameter values  

separation (m)  A  B (×10 ^{ 4 } )  C  D (×10 ^{ 5 } ) 
0.53  −49.81  0.63  45.98  −7.05 
0.94  −48.56  0.64  43.89  −6.47 
1.28  −50.66  0.46  45.37  −5.20 
2.03  −47.36  0.34  38.82  −3.68 
3.38  −45.32  0.14  38.25  −4.28 
3.2 3.2 Smallscale variations
where \(\beta =1+k\frac {x\mu }{\sigma }\). The parameters, μ, σ, and k, are the location, scale, and shape parameters, respectively.
Two sample KS test p values for fitting SSV with different continuous distributions
Tx  TxRx  Distributions  

position  separation (m)  GEV  Logistic  Normal 
0.53  0.3456  0.8838  0.7085  
Incar  0.94  0.8838  0.8838  0.7085 
1.28  0.7085  0.7085  0.8838  
Outofcar  2.03  0.9997  0.6297  0.5142 
3.38  0.8838  0.7085  0.8838 
3.3 3.3 Comparison with UWB
UWB possesses a great potential for highspeed data communication and precise localization operations in cluttered closedspace hostile towards radio frequency (RF) signal propagation. Traditionally, the PDP for UWB channels are described with a modified SalehValenzuela (SV) model [19]. However, in a recent work by Demir et al. [36], the authors found that the PDP for UWB transmission in vehicular networks may be characterized by segmenting the PDP (in dB scale) into several linear slopes. Inspired by these facts, we tried to compare our results for 802.11p protocol with measurements for UWB (3 to 11 GHz) performed using the same VNAbased setup. The goal was to find if one can attain similar LSV trends in wider bandwidths as well.
The number of measured points was the same; however, due to the larger BW (8 GHz) and a frequency step size of f _{ s }=100 MHz, we have a smaller time range t _{ d }=1/f _{ s }=10 ns. Thus, we cannot compare the PDPs in an onetoone basis. For analyzing LSV models, we use a scaled comparison instead. For the UWB measurement, the propagation space resolution is P _{sr}=3 cm and the maximum propagation distance is L _{ d max}=30 m.
4 4 Simulation results
The Tx generates 10^{6} data subframes for a given energy per bit to noise power spectral density ratio (E _{ b }/N _{0}). For signal transmission, we use rate 1/2 convolutional coding and BPSK modulation. On the receiver side, we use simple least square (LS) estimation and a hard Viterbi decoder. The 802.11p standard is based on OFDM with N _{IFFT}=64 for a bandwidth of 10 MHz. In the time domain, each OFDM symbol contains 80 chips including a cyclic prefix of length 16. The final transmitted signal has a duration of 8 μs.
Characteristics of the channel models
Tap delay (ns)  Tap gain (dB)  

0.53 m LOS  0.94 m LOS  1.28 m NLOS  2.03 m NLOS  3.38 m NLOS  
0  0  0  0  0  0 
10  −11.78  −10.61  −9.61  −6.06  −6.69 
20  −17.69  −16.24  −14.90  −10.28  −11.06 
30  −20.69  −19.27  −18.27  −13.22  −13.93 
40  −22.26  −20.93  −20.32  −15.28  −15.80 
50  −23.11  −21.87  −21.58  −16.74  −17.04 
60  −23.62  −22.45  −22.39  −17.76  −17.85 
70  −23.95  −22.83  −22.91  −18.50  −18.40 
80  −24.20  −23.10  −23.27  −19.04  −18.76 
90  −21.41  −23.33  −23.53  −19.43  −19.01 
K factor (dB)  21.30  20.07  19.61  15.15  15.40 
5 5 Conclusions
The aim of the text was to assess the suitability of protocol 802.11p for incar wireless applications. For the purpose, extensive vehicular channel measurements in the 5.8GHz band were carried out. A double exponential decay model was used for describing the basic trend of the measured PDP, and we utilized it for IEEE 802.11p BER simulation. The BER achieves the recommended values for all variants of the channel, and it can be concluded that 802.11p standard (in particular, the PHY protocol stack) can be adopted for intravehicular communication systems.
Declarations
Acknowledgements
This work was supported by the SoMoPro II programme, Project No. 3SGA5720 Localization via UWB, cofinanced by the People Programme (Marie Curie action) of the Seventh Framework Programme of EU according to the REA Grant Agreement No. 291782 and by the SouthMoravian Region. The research is further cofinanced by the Czech Science Foundation, Project No. 1338735S Research into wireless channels for intravehicle communication and positioning, and by Czech Ministry of Education in frame of National Sustainability Program under grant LO1401. For research, infrastructure of the SIX Center was used. The generous support from Skoda a.s. Mlada Boleslav are also gratefully acknowledged.
Authors’ Affiliations
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