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International Global Navigation Satellite Systems Society IGNSS Symposium 2009 Holiday Inn Surfers Paradise, Qld, Australia 1 – 3 December, 2009 Sensitivity Enhancement in WiBro Geo-location System Ji-won Park (1) Department of Information and Communication Engineering Chungnam National University, Korea Tel: +82-42-821-7607, Fax: +82-42-824-6807, jwjsjk@gmail.com Seung-Hun Song (2) Department of Information and Communication Engineering Chungnam National University, Korea Tel: +82-42-821-7607, Fax: +82-42-824-6807, lsphoenix4th@gmail.com Tae-Kyung Sung (3) Division of Electric and Computer Engineering Chungnam National University, Korea Tel: +82-42-821-5660, Fax: +82-42-824-6807, tksaint@cnu.ac.kr ABSTRACT WiBro, a Korean mobile WiMAX, is a wireless broadband internet service based on IEEE (Institute of Electrical and Electronics Engineering) 802.16e. In WiBro system, preamble symbols are broadcasted by RAS (Radio Access Station) at the beginning of each frame. Using the correlator, TDoA (Time Difference of Arrival) measurements can be obtained from the preamble. For two-dimensional positioning, more than two RASs need to be detected. Since WiBro is a cell-based system, neighboring RASs are hard to detect. In order to increase the sensitivity of the receiver to detect the preamble signal from the neighboring RAS, long integration technique is often used. However, due to residual frequency in the carrier, length of the integration is limited. This paper presents a residual frequency estimator used in hybrid integration in WiBro network. WiBro channel model is taken into account based on ITU-R m.1225. By computer simulation, it is revealed that the residual frequency estimation error is less than 2 Hz in multi-path environment with regardless of user position. KEYWORDS: WiBro, hybrid integration, residual Doppler estimation 1. INTRODUCTION LBS (Location Based Service) are becoming essential to our life as the number of mobile terminals is growing up. The LBS provides specific information according the location of the subscriber. The quality of LBS service becomes better as the positioning accuracy is improved. Several positioning methods are used in LBS to estimate the user position. Examples include GPS, Assisted GPS, Cell-ID, Geo-location using cellular network, and dead-reckoning systems. WiBro is an internet service that provides high-speed data communication in mobile. It is capable of providing seamless and stable data communication when moving within the velocity of 60 Km/h. WiBro employs OFDMA (Orthogonal Frequency Division Multiple Access) TDD (Time Division Duplex) technology, and symbol is used as a basic unit in communication. Group of down-link and up-link symbols constitute a frame. A preamble symbol is assigned to the first symbol of each frame, and orthogonal preambles are assigned to RASs to distinguish each other. Since all the RASs are synchronized by GPS clock, OWR (One-way Ranging) TDoA (Time Difference of Arrival) measurements can be obtained at the receiver by measuring relative delays between preambles from RASs. To carry out geo-location in the 2D plane, three or more preambles should be detected at the receiver. However, WiBro is a cellular based system and it is difficult to detect more than one preamble at the receiver. Thus, sensitivity of the receiver needs to be enhanced to detect preambles from neighboring cell. Two integration methods can be used to enhance sensitivity. One is the coherent integration and the other is non-coherent integration. The former method is more effective, but integration loss may take place if there is residual frequency in the carrier. The latter method does not suffer from residual frequency, but the squaring loss becomes critical when the received signal has low SNR. This paper presents a residual frequency estimator in order to enhance the integration gain in WiBro network. The next section outlines the residual frequency estimator in WiBro network. In section 3, based on ITU-R m.1225 channel model, performance of the frequency estimator is analysed in pedestrian test environment. 2. WiBro receiver structure for geo-location system 2.1 WiBro Signal Structure WiBro adopts OFDMA TDD and symbols are used as the fundamental transmission unit. A group of down-link and up-link symbols constitute a frame as shown in Figure 1, and its duration is 5 msec. The first symbol of a frame is used as a preamble. Mutually orthogonal preamble code is assigned to RASs. All the RASs are synchronized by GPS timing and the preamble symbol is transmitted every 5 msec by RASs simultaneously. From the receiver correlator, TDoA measurement is obtained by detecting preamble. 2D plane geo-location using TDoA requires at least 2 differential range measurements. Because WiBro is cell-based system, however, neighboured RAS signals are hardly detected. Therefore, sensitivity of the receiver should be enhanced by accumulating the preamble symbols. Figure 1. Frame structure 2.2 Sensitivity enhancement with hybrid integration Since identical preamble symbols are repeatedly transmitted every 5msec, coherent integration method can be used with the preamble. Theoretically, SNR after coherent integration is proportional to the number of integration. When residual frequency exists in the signal, however, coherent loss occurs that is given by ⎡⎛ 2⎤ sin(πf res NT ) ⎞ ⎥ Coherent Loss[dB] = 10 log10 ⎢⎜ ⎟ ⎢⎜ πf res NT ⎟ ⎥ (1) ⎢⎝ ⎣ ⎠ ⎥⎦ where f res is residual frequency, N is the number of coherent integration, T is the periodic of the signal being integrated. For WiBro, T is 5msec, and coherent integration loss is increased as the number of integration increase. To diminish the loss or enlarge the integration time, residual frequency needs to be estimated accurately. Non-coherent integration method integrates the signal after squaring, thus there is no loss caused by residual frequency. However, squaring operation also influence the noise characteristics and squaring loss occur as ⎡ ⎡ SNR ⎤ 2 ⎤ ⎢ π ⎢ − 4 ⎧⎛ SNR ⎞ ⎛ SNR ⎞ SNR ⎛ SNR ⎞⎫ ⎥ ⎥ ⎢ ⋅ ⎢e ⋅ ⎨⎜1 + ⎟ ⋅ I0 ⎜ ⎟+ ⋅ I1⎜ ⎟⎬ − 1⎥ ⎥ ⎢ 2 ⎢ ⎩⎝ 2 ⎠ ⎝ 4 ⎠ 2 ⎝ 4 ⎠⎭ ⎥ ⎥ Squaring Loss [dB] = 10 log10 [SNR ] − 10 log10 ⎢ ⎣ ⎦ ⎥ (2) ⎢ 2⎥ ⎢ ⎡ − SNR ⎤ ⎥ π ⎧⎛ SNR ⎞ ⎛ SNR ⎞ SNR ⎛ SNR ⎞⎫⎥ ⎢ SNR + 2 − ⋅ ⎢e 4 ⋅ ⎨⎜1 + ⎟ ⋅ I0 ⎜ ⎟+ ⋅ I1⎜ ⎟⎬ ⎥ ⎢ 2 ⎢ ⎩⎝ 2 ⎠ ⎝ 4 ⎠ 2 ⎝ 4 ⎠ ⎭⎥ ⎥ ⎢ ⎣ ⎢ ⎣ ⎥ ⎥ ⎦ ⎦ In the equation, SNR denotes the SNR before squaring, I 0 (•) and I1 (•) are 0th and 1th order modified Bessel function of first kind each. As shown in Figure 2, squaring loss increase exponentially as the signal SNR before squaring becomes small. Figure 2. Squaring loss Hybrid integration scheme using both coherent and non-coherent integration is commonly used in sensitivity enhancement. Figure 3 shows the structure of the hybrid integration. In order to increase SNR, coherent integration is done first. Then, integrated signal is fed into non-coherent integrator. To increase SNR in coherent integration, integration time should be enlarged. This means that residual frequency should be reduced to maintain a certain coherent loss. Therefore, in order to maximize sensitivity of a receiver, residual frequency estimation with high accuracy is an important factor in sensitivity enhancement. Figure 3. Hybrid integration structure 2.3 Residual frequency estimator Using the consecutive preamble symbols, residual frequency in the received signal can be estimated using FFT method. By finding the maximum peak in the FFT of successive correlation profile, residual frequency is estimated. Input data to FFT is prepared as in Figure 4. Then, the FFT result is written as 1 N −1 ki − j 2π X [k , m] = ∑ xi [m]e N (k , i = 0,1, 2,L N − 1) (3) N i =0 where xi [m] is the correlation profile of i th preamble symbol, N is the number of sample, and m is the time index in the correlation. By finding k that has a maximum magnitude of X [k , m] over a threshold, estimated residual frequency is obtained that is given by k max f res = f FR , k max = arg max X [k , m] (4) N k where f FR is the frame rate. Because the frame duration is 5msec in WiBro system, f FR is equal to 200 Hz. Therefore, if 200-point FFT is used with 1sec data, resolution of frequency estimation becomes 1 Hz. x0[m] x1[m] xN−1[m] Figure 4. Residual frequency estimator using FFT 3. Simulation Results 3.1 Simulation Environment Performance of the residual frequency estimation is analysed by computer simulation. Channel model, based on the ITU-R M.1225 document, is used and only path loss and multipath fading is considered. Channel environment is assumed as Outdoor to indoor and pedestrian test environment. The system parameters of the WiBro system are shown in the Table 1. Parameter value Frequency allocated for WiBro 2.3GHz~2.4GHz Cell coverage 500 m Bandwidth of the channel 10 MHz System sampling frequency 20 MHz TDD frame length 5 ms OFDMA symbol time 115.2 us FFT size per symbol 1024 Noise Power Spectrum Density -104 dBm /10 MHz Table 1. System parameters for simulation The cell structure is built up as shown in Figure 5. Figure 5. Cell structure for simulation Based on cell coverage, transmission power of the RAS is set as 14.3 dB as in Eq. (5), where N 0 is the white Gaussian noise, PL is the path loss, Gcorr is the correlation gain, GMar is the margin. PTX [dB] = N 0 + PL − Gcorr + GMar = −104 + 137.8 − 25.5 + 6 = 14.3[dB] (5) Since every RAS are synchronized with GPS clock, each RAS’s residual frequency is assumed same, and is set as 51 Hz. The FFT is used with 1 sec data length. 3.2 Performance of Residual Frequency Estimator In no multipath environment, residual frequency estimation was performed near the centre of a cell, and far at the edge of a cell. The coordinates near the centre was set as (10m, 0m) and the coordinates far at the edge was set as (500m, 0). At each coordinates, the simulation was repeated for 100 times and the estimated frequency histogram was shown as Figure 6. (a) (b) Figure 6. Histogram of an estimated residual frequency in no multipath environment. (a) Near the centre at (10m, 0m), (b) at the edge at (500m, 0m). When there is no multipath, estimated frequency is same regardless of the distance from the centre. This indicates that residual frequency estimator is not influenced by SNR of a received signal, or interference caused from other RAS signals. Figure 7 is the histogram of the estimated frequency, when the residual frequency estimation was performed at (500m, 0) in multipath environment. Figure 7. Histogram of an estimated residual frequency in multipath environment at the edge (500m, 0) In the presence of multipath, additional frequency shift occurred in the residual frequency. In the simulation, frequency shift error appeared be maximum 2Hz. This shows that multipath fading has the effect of producing additional frequency error to the signal. 4. CONCLUSIONS Sensitivity enhancement of the receiver is crucial for detecting more two RASs in WiBro geo- location system. In this paper, residual frequency estimation was shown to enhance the performance of the hybrid integration. It was shown in the simulation that multipath has the effect of providing additional shift in the residual frequency. In conclusion, in multipath environment the residual frequency estimator will have resolution error within 1Hz, and frequency shift error with in 2Hz. With hybrid integration, after residual frequency estimation, it will be able to detect three or more preamble in the most of the cell area. REFERENCES Caffery Jr. JJ (1999) Wireless Location In CDMA Cellular Radio System, Kluwer Academic Publishers, 23-40pp Holmes J (1991) Coherent Spread Spectrum Systems, Krieger Publishing Company Strässle C, Megnet D, and Mathis H (2007) The Squaring-Loss Paradox, ION GNSS 20th International Technical Meeting of the Satellite Division, Fort Worth, TX, Sept. Soliman S, Glazko S, and Agashe P, (1999) GPS Receiver Sensitivity Enhancement in Wireless Applications, Proceedings of the IEEE MTT-S International Tipical Symposium on Technologies for Wireless Applications TTA (2005) Specifications for 2.3GHz band Portable Internet Service (PHY & MAC Layer). Available: http://www.wibro.or.kr/new/standards01.jsp. Accessed 10 Sept 2009