In this article, we present the measurement and description of channel parameters for the time-varying Infostation UWB channel. We also consider how such parameters can be used to improve system performance in terms of optimally combating inter-symbol interference (ISI) and inter-channel interference (ICI) in the case of multiband OFDM

Chude-Okonkwo, U. A. K.

Ngah, R.

Rahman, T. A.

Zahedi, Yasser K.

Zaid, S. M.

English

Universiti Teknologi Malaysia Institutional Repository

1476 PIERS Proceedings, Kuala Lumpur, MALAYSIA, March 27–30, 2012Measurement and Parameter Description of Time-varyingUltra-wideband Infostation ChannelU. A. K. Chude-Okonkwo, R. Ngah,Yasser K. Zahedi, S. M. Zaid, and T. A. RahmanWireless Communication Center, Universiti Teknologi Malaysia, MalaysiaAbstract— In this article, we present the measurement and description of channel parametersfor the time-varying Infostation UWB channel. We also consider how such parameters can beused to improve system performance in terms of optimally combating inter-symbol interference(ISI) and inter-channel interference (ICI) in the case of multiband OFDM.1. INTRODUCTIONThe concept of infostation [1–3] presents a new way to look at the problem of providing high datarate wireless access. It is an isolated pocket area with small coverage (hundreds of meters) ofhigh bandwidth connectivity that collects information requests from mobile users and delivers datawhile users are going through the coverage area. Infostations can be located in heavily populatedareas such as airports, shops, pubs, hotels, and along highways. One of the technologies that havethe potential to deliver the envisaged high-data rate infostation services is the UWB signaling [3].The UWB has the basic attributes of extremely low transmission power, operating at unlicensedfrequency, high data rate, multipath immunity and low cost. Existing channel characterization andmeasurement for the UWB channel have been limited to the case where the channel is assumedto be stationary over the transmission duration. However, for many infostation scenarios, timevariation is expected due to the mobility of one of the communication terminals/scatterers. Hence,the existing channel models cannot be used to describe this new target scenario where terminalmobility is expected.Time-varying channels are often modeled as stationary random processes using the conceptof the wide-sense stationary uncorrelated scattering (WSSUS) assumption [4]. Unfortunately, intime-varying UWB channel, the WSSUS assumption is invalid. The nature of the time-varyingchannel is such that the spatial structures of the multipath components, i.e., their number, time-of-arrivals (TOA), angle-of-arrivals (AOA) and magnitudes, change with time and location, leadingto nonstationary statistics. Hence, non-WSSUS characterization [5, 6] of the channel is required.For the UWB channel, the fine time resolution implies narrow delay bins which enable paths tomove fast from one tap to another [7]. Hence, the time evolution of the UWB channel cannot bedecomposed into the time evolution of the individual taps, but of the individual paths.In this article, we present the measurement and the descriptions of channel parameters forthe time-varying Infostation UWB channel. We also consider how such parameters can be usedto improve system performance in terms of combating ICI in the case of multiband OFDM andmismatch in channel estimation.The rest of this paper is organized as follows. In Section 2, the basic system model is specified.The Infostation UWB channel measurement setup is presented in Section 3. Section 4 is devoted todescribing the post processing of the measurement data and the description of the how the channelparameters can be used to improve system performance in terms of optimally combating ISI andICI in the case of multiband OFDM.2. SYSTEM MODELChannels can be characterized by their response function in time and/or frequency domain sayP(t, f). The variation among the statistics of the measured channel responses taken over a givenappreciable interval is assumed to be insignificant (stationary) in the WSSUS case. Unfortunately,in time-varying UWB channel this is not the case as the channel is non-WSSUS. In essence, non-WSSUS scattering function can be viewed as a set of evolutionary functions that are more or lessthe instantaneous responses P(t, f)i, i = 1, 2, 3, . . . , I of the channel to an input. Although thecoherence parameters of these instantaneous channel realizations vary from one to another, forpractical rationality we consider channel coherency only with respect to the reference channelsresponse regard as being WSSUS say P(t, f)1. The coherency of P(t, f)1 is ensured by restrictingProgress In Electromagnetics Research Symposium Proceedings, KL, MALAYSIA, March 27–30, 2012 1477(a)  (b)Figure 1: (a) Illustration of measurement setup. (b) Real measurement setup.the measurement sampling time Jv at Jv = λ/2. All other sets of Ψ = {P(τ, s)i : {i 6= 1} ∈ Z}are defined only by stationarity the parameters. Hence, the non-WSSUS channel is completelycharacterized by the coherence time Tc and bandwidth Bc [8], and the stationarity time Ts andbandwidth Bs [5].3. INFOSTATION UWB CHANNEL MEASUREMENTThe complex channel response is measured with a vector analyzer (VNA) R&S R©ZVL13. Mea-surements were carried out at various locations along a path way within the vicinity of WirelessCommunication Centre (WCC) complex Universiti Teknologi Malaysia, as shown in Fig. 1 for thefrequency range 3.1–3.628GHz. The speed of the mobile is about 2m/s, and measurements weretaken at each location marked A1 − A8. At each location, the measurement is repeated 50 times.The VNA records the variation of 1001 complex tones within the band. This recording is doneby sweeping the spectrum in about 20× Jv time interval. Apart from the mobile antenna, all theobjects (potential scatterers) are kept stationary throughout the duration of the measurement. Theantennas (monopoles) are of the same height, 1.5m and the transmit power is −42 dB for all mea-surements. The signal from the receiving antenna is passed through a low noise amplifier (LNA)with a gain of 24 dB. The distances between the locations are, A1 −A2 = 40 cm, A2 −A3 = 40 cm,A3 −A4 = 40 cm, A4 −A5 = 40 cm, A5 −A6 = 40 cm, A6 −A7 = 40 cm and A7 −A8 = 40 cm.4. MEASUREMENT DATA PROCESSING AND PARAMETER DESCRIPTIONThe description of the post processing and parameter description for the channel measurement datais given in this section. Since the velocity of the mobile is constant throughout the measurementrun, and LOS propagation exists for all measurements, the coherence time for all measurement isapproximately constant. Hence, the values of Ts/Tc at A1, A2, A3, A4, A5, A6, A7 and A8 areinfinity as long as constant velocity is maintained and LOS propagation exists.The VNA effectively receives a channel output Y (t). In order to obtain the statistical modelof the time-variant response from the measured complex channel responses, we apply the autore-gressive (AR) model proposed in [9]. Let Y (fp, t;A) be the time-varying complex received signmeasured at a location A and time t. Then the first and second order statistics of the measuredchannel are captured by the model: Y (fp, t;A) =N∑n=1an Y (fp−n, t;A) + V (fp), where V (fp) is acomplex white noise process and an is the function representing the nth time-varying AR coeffi-cient. We take the inverse fast Fourier transform (IFFT) of Y (t) to arrive at the passband timedomain response of the system. We choose 215 — point IFFT which ensures an oversampled periodT of 6.1035 ps, which is many times oversampled compared to the Nyquist rate. This oversamplingis critical to our analyses as it allows us to accurately approximate the delay version of the receivedsignal as a delay of indices in its sampled version. At a threshold of −10 dB, the measured responsesare sampled at the interval of 1/(2BT ), where B = 528MHz is the bandwidth of the system. Thenormalized PDP for the positions A1, A2, A3, A4, A5, A6, A7 and A8 are shown in Fig. 2.From Fig. 2, the coherence bandwidth value of 7.56MHz is computed by assuming that theresponse at the reference position A1 upholds the WSSUS assumption. The computed Bs for the1478 PIERS Proceedings, Kuala Lumpur, MALAYSIA, March 27–30, 2012Figure 2: Normalized PDP (in watts) for positions A1, A2, A3, A4, A5, A6, A7 and A8.positions A2, A3, A4, A5, A6, A7 and A8 (non-WSSUS) are approximately 33.47MHz, 36.6MHz,91.7MHz, 1711.33MHz, 114.6MHz, 76.88MHz and 306.22MHz, respectively. These Bs valuesare computed at −10 dB threshold. The implication of the ratio Bs/Bc can be observed in thecase of multiband orthogonal frequency division multiplex (MB-OFDM) UWB. Let us consider theMB-OFDM system designed with Ns number of subcarriers and subcarrier spacing of FsMHz. Inorder to combat fading in MB-OFDM, the bandwidths of the subcarriers should be equal or lessthan the Bc to avoid ISI. However, the choice of small value for Fs implies that the system will bemore susceptible to ICI. Hence, the choice of the value of Fs should be optimal between combatingfrequency selective fading and ICI. If we consider a total bandwidth of 528MHz, the value of Fs for128, 64 32 and 16 subcarriers are 4.125MHz, 8.25MHz, 16.5MHz and 33MHz, respectively. Hence,the choice of 128 subcarrier ensures good ISI performance but with increased error due to ICI, andthe choice of 16 subcarriers ensures good ICI performance but with increased susceptibility to ICI.The optimal choice will be to choose the number of subcarriers such that kFs = Bc, where the valueof k should be chosen to take care of the time-varying nature of Bc. Conventionally, k is chosento be fixed and of low value, which implies a fixed number of subcarriers. The SNR degradationcaused by ICI is given by [10]:D ∼= 10ln 1013(pifeFs)2(1 +EsN0)(1)where fe is the frequency offset. If we consider the above channel measurement, then the SNRdegradations for 128, 64, 32 and 22 subcarriers are shown in Fig. 3.Figure 3 shows that the SNR degradation for 22 subcarriers (k = 1) is better than the perfor-mance at k < 1 (128, 64 and 32 subcarriers). However, when k is greater than unity, ISI degradationsets in. This implies that instead of a fixed value for k, some form of adaptive subcarrier bandwidthcan be employed. The value of stationarity bandwidth can provide information that can be usedto adjust k for optimal performance. The values of Bs/Bc at A1, A2, A3, A4, A5, A6, A7 andA8 are approximately, ∞, 4.4, 4.8, 12.13, 226.5, 15.2, 10.2, 40.5, respectively. We can define thebandwidth utilization parameter U by: U ∼= −B−1co (((=Bco)/=− 1)−Bco), where, = = Bs/Bc andBco is the reference coherence bandwidth. Hence, the values of U at A1, A2, A3, A4, A5, A6, A7and A8 are approximately, −18.42%, 26.02%, 8.98%, 0.44%, 7.06%, 10.90% and 2.41%, respectively.The negative sign in U indicates that k is greater than 1 by the given percentage and the positiveProgress In Electromagnetics Research Symposium Proceedings, KL, MALAYSIA, March 27–30, 2012 14790 2 4 6 8 10-10-5051015202530Frequency offset (Hz)Degradation D (dB)  128 subcarriers64 subcarriers32 subcarriers22 subcarriersFigure 3: SNR degradation as a function of subcarrier spacing.sign in U indicates that k is less than 1 by the given percentage. Therefore, this nonstationarityinformation can be employed to adjust the values of k in order to optimize the system performanceat any time instant.5. CONCLUSIONThe measurement and parameter description for the time-varying UWB Infostation channel is pre-sented. The analysis emphasized on the nonstationary properties of the UWB due to the movementof the mobile terminal. Coherence and stationarity parameters were obtained and used to analyzethe performance of the measured channel with respect to ICI and ISI in MB-OFDM. From resultsit implies that some form of adaptive technique using the joint knowledge of the coherence andstationarity parameters will greatly improve the performance of the Infostation channel in termsof combating ICI and ISI.ACKNOWLEDGMENTThe authors thank the Ministry of Higher Education (MOHE), Malaysia for providing financialsupport for this work through the Grants (4D040 and Q.J130000.7123.02H31) managed by theResearch Management Center (RMC), Universiti Teknologi Malaysia (UTM). We also thank thereviewers of this manuscript for their constructive remarks.REFERENCES1. Goodman, D. J., J. Borras, N. B. Mandayam, and R. D. Yates, “Infostation: A new sys-tem model for data and messaging services,” Proc. IEEE 47th Vehicular Technology Conf.,May 969–973, 1997.2. Rajappan, G., et al., “Mobile infostation network technology,” Proc. SPIE on Wireless Sensingand Processing, Orlando, 2006.3. Chowdhury, H., J. P. Mekela, and K. Pahlavan, “Statistical information transfer in randomcrossing of infostation coverage,” Proc. 2005 Finnish Signal Processing Symposium, Kuopio,Finland, August 2005.4. Bello, P., “Characterization of randomly time-variant linear channel,” IEEE Trans. Commun.,Vol. 11, No. 4, 360–393, 1963.5. Matz, G., “On non-WSSUS wireless fading channels,” IEEE Trans. Wirel. Commun, Vol. 4,No. 5, 2465–2478, 2005.6. Chude Okonkwo, U. A. K., et al., “Time-scale domain characterization of nonstationarywideband vehicle-to-vehicle propagation channel,” Proc. IEEE APACE 2010, 1–6, Malaysia,November 9–10, 2010.7. Tse, D. and P. Viswanath, Fundamentals of Wireless Communications, Cambridge UniversityPress, New York, 2005.8. Molisch, A. F., Wireless Communications, 2nd Edition, John Wiley, New Jersey, 2005.9. Howard, S. J. and K. Pahlavan, “Autoregressive modelling of wideband indoor radio propaga-tion,” IEEE Trans. Commun., Vol. 40, No. 9, 1540–1552, 1992.10. Pollet, T., M. Blade, and M. Moeneclaey, “BER sensitivity of OFDM systems to carrierfrequency offset and wiener phase noise,” IEEE Trans. Commun., Vol. 43, No. 2/3/4, 191–193,1995.View publication stats

Measurement and parameter description of time-varying ultra-wideband infostation channel

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Measurement and parameter description of time-varying ultra-wideband infostation channel

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