Spectrum Sensing for Efficient Sharing of LTE and DVB-T Systems

Spectrum Sensing for Efficient Sharing of LTE and DVB-T Systems Sara Sangtarash, Horace L. King College of Engineering and Science, Victoria University P.O. Box 14428, Melbourne, Victoria, 8001, Australia ABSTRACT This paper addresses a problem of spectrum sharing and coexistence between Long Term Evolution (LTE) systems and Digital Video Broadcasting-Terrestrial (DVB-T). Previous studies have shown that coexistence of LTE and DVB-T without protection guard may cause interference. However by applying Cognitive Radio (CR) access technique, the probability of interference will decrease and the available spectrum can be used more efficiently. The main objective in spectrum sensing in a given band is to optimize the performance of the LTE as secondary network. This performance can be tested using a statistical analysis tool incorporating Monte Carlo and Spectral Emission Mask (SEM) technique. In addition, the CR access technique is used to sense the spectrum over the primary users (P u s) band to detect the existence/absence of a P u and use the free spectrum for LTE system as a secondary system. In this study coexistence of two different configurations was examined. The simulation results show that based on power level allocated to the secondary transmitter and in a given configuration, varying protection distances will be needed. Furthermore, tuning the transmission power levels and incorporating protection distances, can lead to more spectrum usage opportunities without harmful interference to the P u (DVB-T receiver). Keywords: Cognitive Radio, White Space Devices, LTE, Secondary User 1. INTRODUCTION Recent advances in technology design have led to rapid development and deployment of wireless communication systems resulting into a congested radio spectrum. However, it has been estimated that 70% of licensed spectrum in some countries is not utilized efficiently across time and space [1, 2]. Since the next generation mobile networks promise to provide broad area coverage and very high data rates, it is predicted that the required data rate in 2020, will be 100 to 1000 times as high as the currently available rates [3, 4]. Consequently improved spectrum utilization is critical to satisfy the increasing user demand for wireless capacity, coverage and quality of service. Currently universal TV broadcasting systems are switching from analogue to digital hence improving quality of TV broadcasting and the efficient usage of the spectrum. Consequently a significant amount of precious spectrum will be available in the UHF band as an interleaved spectrum or TV White Spaces (TVWS) [5]. These white spaces are considered as a particular band of interest as this band is currently being opened up for opportunistic channel access in many areas of the world [1, 6 9]. The advantages of this frequency band are that the spectrum located between 200 MHz up to 1 GHz is very valuable in terms of coverage and bandwidth with fewer base stations and at a lower cost needed to cover high traffic. For instance, instead of 80 enode B s for an area of 624 Km 2 at 2.6 GHz band, An LTE system only requires 4 enode B s in the 700 MHz band [6]. Moreover, better signal-to-noise ratio (SNR) at lower frequency causes an increase in the system s capacity and performance [10]. Therefore, in urban areas, particularly in concrete made buildings, the LTE on TVWS can improve indoor coverage due to propagation conditions at these frequencies that are compatible with this kind of environment [6]. In an attempt to improve the utilization of currently underutilized spectrum bands, CR is a highly promising technique to implement [11 13]. In CR systems, the spectrum usage can be enhanced by making secondary users (S u s) adapt their transmission patterns to opportunistically access any free spaces (holes) in the spectrum. Spectrum holes appear in time and frequency where the P u s were originally allocated but switched to a different band. The critical point is how to maximize the S u rate while maintaining an acceptable level of interference to P u s [6, 14 17]. The objective of this paper is to investigate the interference of coexistence and sharing of DVB-T and LTE systems. Using a sensing strategy in CR systems can significantly decrease the interference and improve the QoS and optimize system performance. Three major approaches have been employed to achieve the set spectrum sharing objectives. The first approach is an analytical model to evaluate performance of the systems in both Cognitive and non-cognitive networks. This is followed by simulating the probability of interference of different LTE transmission power vs. distance. Finally, key design parameters are proposed and used to achieve minimum guard distance for a DVBT receiver and LTE transmission taking into account the trade-off between spectrum efficiency and energy efficiency. Results prove that our proposed CR approaches are able to achieve significantly lower outage and higher throughput, compared to non-cr. The rest of the paper is organized as follows: Sections 2 and 3 describe spectrum sharing and interference probability without CR. Section 4 presents the spectrum sensing scheme and the system model with CR. Discussion of throughput of CR and non-cr in networks and comparison of simulation results are covered in Section 5. Section 6 concludes this work. 166

2. SPECTRUM SHARING AND INTERFERENCE PROBABILITY WITHOUT COGNITIVE RADIO 2.1 Basic Scenario and Methodology Radio spectrum management is very important for coexistence and sharing between radio communications systems in the same or adjacent frequency bands. One of the radio compatibility criteria is the difference in levels between the desired and the interfering signal at the victim receiver (V r) input. This value is used to derive a guard distance for the victim and interfering systems in a geographical space or frequency domain hence allowing the design of systems with more efficient spectrum utilization. One way of estimating inter systems interference is to use SEAMCAT (Spectrum Engineering Advanced Monte- Carlo Analysis Tool) the statistical simulation mode which has been developed based on the Monte-Carlo method [18]. 2.2 Interference Calculation Using Fig. 1 the victim is a DVB-T broadcasting system and interference is from LTE system with spatially distribution nodes modeled according to the homogeneous Poisson process. Assume we have nodes (LTE system) inside a region of interest M, with a specific area A M. The probability of the nodes being in the region of interest becomes: qa s = M qa P s in M e M s 0 1 s! where is a constant depicting a spatial density of interfering nodes per unit area. To calculate the actual probability of interference, the Interference Calculation Engine (ICE) compares the samples of wanted: desired Received Signal Strength (drss) and unwanted: interference Received Signal Strength (irss) signals against the relevant signal-to-noise criteria such as carrier-to-noise (C/N), carrier-to-noise plus interference (C/N+I) etc [18]. In this work the C/N margin specified is 18.7 db for Digital Video Broadcasting (DVB) from [19]. In the interference scenario we consider two different received signals as described as follows: drss is the signal transmitted by the Wanted transmitter (W t) or transmitter of the primary system (DVB-T transmitter) to the V r. irss is the signal transmitted by the Interfering transmitter (I t) or secondary system (LTE transmitter) and received by the V r [20]. The interfering signal and desired received signal strength can be measured at V r, and therefore the interference probability can be obtained by comparing the ratio between signal strength levels of the interference and the desired signal, carrier-tointerference (C/I) with a pre-defined protection ratio. If C/I trial is greater than C/I target, then the probability of the DVB-T being interfered with is very low. If C/I trial is less than C/I target, then the probability of the DVB-T being interfered with is very high. After a cycle of N all events involving C/I and N good events for the required C/I: Overall P Interference 1 N good / N all 2 Therefore the probability of interference (P I) of the V r is: P I = 1- P NI 3 where P I is the interference probability of the V r, P NI is the probability of Non Interference (NI) of the V r. P NI is defined as follows [20]: drss ( ) 4 irss composite r P NI P C I drss sensitivity v where therefore: is the victim receiver sensitivity and drss P ( C I ), drss sensitivity vr irsscomposite P NI P drss sensitivity vr 5 with where is the number of interferers (i.e. active LTE transmitters). The desired received signal strength (drss) can be calculated as: drss pw g w V pl w V g t t r t r Vr wt 6 where is the maximum power to primary transmitter, is path loss between DVB-T transmitter and the V r, is antenna gain of DVB-T transmitter in the V r direction and is antenna gain of V r in the W t direction. Figure 1: Interference scenario involving DVB-T and LTE-BS 3. FURTHER INTERFERENCE ANALYSIS 167

Consider the power (P Rx) received at a distance D from a transmitter: P = P Q D 2n Rx Tx k k where P Tx is the average power measurement at a reference distance (e.g. 1m, 2m, 3m,...) away from the transmitter. In this case the amplitude loss exponent is n, while the power loss exponent is 2n. are independent random variables, according to propagation effects such as fading and shadowing, accounts for the far-field path loss. Where n=1, we are dealing with free-space propagation [21]. For : represents path loss only., where where denote a gamma distribution with mean and variance : path loss and Nakagami-m fading. where, the term has a log-normal distribution, where σ is the shadowing coefficient: path loss and log-normal shadowing [22]., with and with path loss, Nakagami-m fading and log-normal shadowing. denote a Gaussian distribution with mean μ and variance. In time, the received signal is: (7) k Q k Rt n ht, X t d (8) D where is the kernel and is the time-varying impulse response of the multi path channel and is the transmitted signal. Since accounts for multi path fading, we can express a canonical example using a tapped-delay time model such that: j f t h t ha t e a t a c (9) where f c is the carrier frequency; and are time varying amplitude and delays respectively associated with the multipath; is the Dirac-delta function. Equation (8) sufficiently allows characterization of interference in a given scenario. The interference representation and distribution is done by considering an aggregate interference (AI) at the DVB- T by specifying a random vector M of arbitrary dimension N b [23]. Let. Hence the aggregate interference M is expressed as: M ( Z n i D i ) ( Z, D ) (10) i 1 i i 1, (A, r) ( Ar, ) 0, otherwise (11) And representing an arbitrary random quantity associated with interferer i. includes multipath fading and shadowing. allows choosing of all contributing nodes to the aggregation interference based on and D i. Note If: α = { } then M represents the AI resulting from all the nodes inside the region described by. And if: ( ), where p th represents path loss threshold, M represents the AI resulting only from the nodes receiving power below a given threshold. The irss is normally the aggregate of the spurious signals from interferers and can be calculated as in [18]: irss unwanted 10 log in 10 10 irssunwantedi 1 where the interferer signal is defined as: irss emission I ( f, f ) 13 unwanted t i It Vr g I V ( f V ) pl I V ( f V ) t r r t r r g V I ( f V ) r t r 10 12 where is the path loss between the transmitter and the DVB-T receiver, is antenna gain of I t in V r direction and is antenna gain of V r in I t direction. Therefore by simulation of current scenario as illustrated in Fig. 1, the probability of interference in a frequency band of DVB-T can be demonstrated. In our simulation we calculated the probability of interference as a function of Transmitter power of the I t and protection distance and using the parameters from Table 1 and Table 2 [19, 24, 25]. Table 1: Systems Parameters Parameter LTE DVB-T Frequency Band (MHz) 662 ~ 742 470 ~ 790 Channel bandwidth (MHz) Base station transmitted power (dbm) 10 8 30 ~ 46 72.15 BS antenna height (m) 30 100 Noise figure of receiver (db) 5 7 Modulation 64 QAM 64 QAM Allowable C/I (db) N/A 24.7 Noise power (inc.nf) over link BW(dBm) N/A 98.17 Table 2: Frequency relative to center of DVB-T channel: 8 MHz channel, non-critical cases 168

Relative Frequency MHz Relative Level db -12.0-110.0-6.0-85.0-4.2-73.0-3.9-32.8 +3.9-32.8 +4.2-73.0 +6.0-85.0 +12.0-110.0 4. THE SPECTRUM SENSING SCHEME AND INTERFERENCE PROBABILITY WITH COGNITIVE RADIO A combination of spectrum sensing and CR technique is one of the best ways to mitigate interference in coexistence scenarios. However, one concern in CR systems is how the S u s detect whether the spectrum is underutilized by P u s or not. Therefore, spectrum sensing becomes critical in CR systems [26]. Two CR access scheme are taken into account. In cooperative CR, radios of different systems switch over common information based on time of the spectrum usage and the frequency. So a protocol is required to communicate. The noncooperative spectrum sensing scheme is based on sensing the environment and deciding by itself, without contact with other spectrum users. Therefore S u s should efficiently use the limited power to achieve maximum performance due to the energy constraints [6, 27]. The non-cooperative spectrum sensing, which is used in our modelling, a sensing signals transmitted by the W t and is received by the I t. The sensing signal will send the power of the W t signal level so if the received signal by I t is less than the threshold the White Space Device (WSD) or I t can send the signal but if it finds the signal more than the Detection threshold (D t) the WSD will be idle. CR is the way to find unused and under-utilized band and based on the it makes a decision to use the spectrum [28]. 4.1 Calculation of the sensing Received Signal Strength The sensing Received Signal Strength (srss) which is transmitted by W t is described in [29]: 14 srss dbm Pw dbm g w I dbi t t t g I w dbi L t t db where is the transmit power from, is the antenna gain of the W t, in the direction, is the antenna gain of I t in the direction and L is the path loss between the I t and the W t. The power that must be sensed by WSD, can be derived by considering the frequency, the antenna gain of the device, and the polarization loss, resulting from misalignment between the antenna of the white space device and the polarization of the primary signal to be detected [30]. Such that: where: and, sense / 15 20log fsense MHz G db L db Psense dbm E dbmv m 77.2 sense pol / / 16 Esense dbmv m E dbmv m med sensesense / / 17 E dbmv m E dbmv m med med, plan L HDVB T HWSD For sensing at WSD height (HWSD), the important parameters are the median electric field strength at that height, E sense and the standard deviation of the signal variation, σ sense. For calculating the for WSD, first we need to calculate the DVB-T field strength at the WSD receiver antenna E med, which is obtained by subtracting the height loss from HDVB-T to HWSD (L HDVB-T- HWSD) from the planned DVB-T field strength. The height loss L HDVB-T-HWSD can be calculated according to the prescription given in [31]. In which the detection threshold can be defined as in Table 3. Table 3: Detection threshold for Outdoor WSDs [30] DVB-T Fixed Outdoor WSDs, @30m E med,plan 56.21 L HDVB-T-HWSD -9.84 E med 66.05 Sensing reliability 99.99% σ 1.5m 5.50 μ sense 3.72 μ sense x σ 1.5m 20.46 f sense 650.00 G sense 0.00 L pol 3.00 E sense 45.59 P sense -90.86 4.2 Identification of the available channels To identify the available channel for S u, the WSD, will sense the channel to measure the power received from the W t (srss). 169

Therefore: If srss is greater than the then WSD will be idle and no transmission therefore no interference. If srss is less than the then WSD is active, then interference is possible [32]. So if the received power at the same operating frequency as the DVB-T device is above the (Fig. 2) and the WSDs are sensing over several channels, the adjacent channels to the channel used by the DVB-T will be considered [29]. Figure 2: Illustration of sensing feature over several channels of WSDs [29] With reference to Fig. 2, for channel 5, the power sensed by WSD1 is above the threshold level, which means the channel is not available. WSD2 detected the power in channel 3 is below the threshold and channel 3 is identified as available. Consequently the WSDs can sense the power of all the channels identified for the DVB-T to find possible available channels [29]. 5. RESULT OF SIMULATION 5.1 Probability of interference and throughput of our systems in non-cr in networks The following defines the probability of interference due to unwanted and blocking effects on the victim DVB-T receiver. In this scenario the relative positioning of the interfering link relative to the victim link is variable. Two configurations for the simulations are considered. 5.1.1 Probability of Interference Derivation Our simulations aimed to investigate the probability of interference for various separation distances for a specific frequency and the power limitation per different distance. To determine the interference probabilities SEAMCAT checks if the calculated ratio is greater than the C/I target. Using Fig. 3 the drss is desired Received Signal Strength from transmitter of the primary system or W t (DVB-T transmitter), and irss is interference Received Signal Strength from transmitter of the secondary system or I t (LTE transmitter). To achieve our C/I target we consider different distances for different powers, this is done by changing the distance between the I t and V r (DVB-T receiver). Figure 3: (a) desired Signal Strength: drss (dbm) and interfering Signal Strength: irss (dbm) per event, (b): Cumulative Probability of drss and irss; at 1km guard distance between Interference transmitter and Victim receiver, without CR. 5.1.2 Configuration 1 The Victim receiver and LTE-BS are located at the edge of the coverage area of the DVB-T and with constant distance between Victim transmitter and receiver. Worst case scenario for coexistence was simulated in order to evaluate LTE-BS interference on DVB-T reception. DVB-T receiver is located at the edge of the coverage of DVB-T Tx, the received power is minimum value also the LTE Tx located close to the DVB- T receiver has the maximum power at the edge of DVB-T coverage. Low probability of interference as a fundamental parameter needs a very large guard distance. When the V r is located at the edge of coverage of the DVB-T system, at the distance more than 10 km between V r and I t, interference is below 2% and C/I is more than target value (24.7 db), therefore without using any mitigation technique we must have a large guard distance (10 km for 30 dbm LTE Tx Power and 22 km for 46 dbm LTE Tx Power). Fig. 4 gives the results obtained for LTE non-cr with 30-46 dbm Transmitter power. 170

5.2 Probability of interference and throughput of our systems in CR in networks 5.2.1 Probability of Interference Derivation In Fig. 6 the interferer is fixed WSD transmitter (LTE-BS). With spectrum sensing, the interfering devices try to detect the presence of primary system in each of the potentially available channels. Therefore is the key parameter in spectrum sensing CR systems. Figure 4: Probability of interference without CR using different power levels and distance of configuration 1. 5.1.3 Configuration 2 The LTE-BS is located at the coverage area of the DVB-T and with uniform distribution between Victim transmitter and receiver. The V r and S u s are located randomly at the coverage area of the DVB-T. The signal strength of DVB-T Tx is different for Victim receivers and the average signal strength is considered for calculating the interference. Figure 5: Probability of interference without CR using different power levels and distance of configuration 2. Fig. 5 illustrates the probability of interference when the V r and Interference system have uniform distribution and the interference probability is calculated randomly. However by applying the protection distance the output is improved. Our simulation results show that large protection distance (10 km for 30 dbm LTE Tx Power and 16 km for 46 dbm LTE Tx Power) is required between two services to decrease the probability of interference at the same frequency band. Figure 6: (a) Desired signal strength: drss (dbm) and Interfering signal strength: irss (dbm) per event, (b): Cumulative Probability of drss and irss; at 1km guard distance between Interference Transmitter and Victim Receiver, with CR. 5.2.2 Configuration 1 The LTE-BS is located at the coverage area of the DVB-T and with constant distance between Victim transmitter and receiver. As results show in Fig. 7, by using CR technique the probability of interference is dramatically decreased and we can achieve our target margin with a guard distance of less than 1 km. 171

minimization of interference is achieved by using CR technique and the interference improved by a factor of 25. 6. CONCLUSION Figure 7: Probability of interference with CR using different power levels and distance of configuration 1. 5.2.3 Configuration 2 The LTE-BS is located at the coverage area of the DVB-T and with uniform distribution between Victim transmitter and receiver. Fig. 8 shows that when configuration 2 is considered the probability of interference is much less than configuration 1, in addition the result verifies that we improved the capacity by decreasing the interference using CR technique. The goal of this article is to study the potential increase in available TVWS for S u s in the DVB-T bands, considering low interference and acceptable C/I levels with and without CR. The simulation results of this work show that the large protection distance is needed for low probability of interference as a fundamental parameter in coexistence of DVB-T and LTE systems. However the probability of the interference of the LTE transmitter will decrease when the sensing signal is used and therefore will increase the spectrum efficiency. In addition depending on the power of LTE transmitter and configuration considered, the outage and system capacity will be changed. REFERENCES [1]. Lehne P.H., MacKenzie R., Noguetand D., Berg V., and Grøndalen O., Mapping cognitive radio system scenarios into the TVWS context, WInnComm, 2012. [2]. ET Docket No. 02-135, Report of the spectrum efficiency working group, 2002. [3]. Xiaofeng T., Xiaodong X., and Qimei C., An overview of cooperative communications, Communications Magazine, IEEE, vol. 50, no. 6, pp. 65 71, 2012. [4]. You XH., and Gao X.Q., Development of beyond 3g techniques and experiment system: An introduction to the future project, ICT Shaping the World: A Scienti_c View, 2008. [5]. Kalogirou V.P., Velivasaki T.-H.N., and Capsalis C.N., Performance measurements of a dvb-t system affected by 5-MHz generic adjacent channel interference, Progress In Electromagnetics Research C, Vol. 17, 1-15, 2010. Figure 8: Probability of interference with CR using different power levels and distance of configuration 2. 5.3 Remark The simulation results show that the biggest losses in DVB-T reception are incurred in configuration 1, where V r is located at the edge of coverage of the DVB-T and close to the LTE-Base Stations. 10-22 Km is a very large protection distance and further network optimization approaches should be made in order to decrease the protection distance and interference probability. The results show that without mitigation techniques it is difficult to share the same frequency channel between LTE and DVB-T services due to required large guard distance. Using CR improves the coexistence and sharing performance. The [6]. Sangtarash S., Sadeghi H., Hassan W.A., King H.L. and, Rahman T.A., Using cognitive radio interference mitigation technique to enhance coexistence and sharing between dvb-t and lte system, FutureNetw, 2012. [7]. Ghasemi A., and Sousa E.S., Spectrum sensing in cognitive radio networks: requirements, challenges and design tradeoffs, Communications Magazine, IEEE, vol. 46, no. 4, pp. 32 39, 2008. [8]. Lee W.Y., and Akyildiz I.F., Optimal spectrum sensing framework for cognitive radio networks, Wireless Communications, IEEE Transactions on, vol. 7, no. 10, pp. 3845 3857, 2008. [9]. Xiang J., Zhang Y., and Skeie T., Medium access control protocols in cognitive radio networks, Wireless Communications and Mobile Computing, vol. 10, no. 1, pp. 31 49, 2010. 172

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