Proc. of Int. Conf. on Recent Trends in Information, Telecommunication and Computing, ITC
Performance and Analysis of Spectrum Sharing in Cognitive Radio using Common Control Channel Jignesh A. Nathani1 and Arjav A. Bavarva2 1 RK University, Rajkot, India Email: jigneshnathani9@gmail.com 2 RK University, Rajkot, India Email: arjav.bavarva@rku.ac.in
Abstract— Spectrum requirement is the biggest issue in the field of communication. Because of new technology and applications expansion bandwidth becomes more crucial. Many methods and techniques are used to solve this problem. One of them is bandwidth sharing cognitive radio technique. This paper shows bandwidth sharing in cognitive radio using common control channel. For this purpose after spectrum sensing, actual work spectrum sharing is done. New secondary user comes into the network and checks spectrum availability by using one of the spectrum sensing techniques, if spectrum is free than spectrum sharing technique assigns available channel to new user without harming existing primary users. This is done through first come first serve bases. Priority is given to the primary users. If existing spectrum band contains secondary users and new primary user comes into the network when no more spectrum band is free then one of the secondary user needs to vacant the band and that spectrum band is allocated to new primary user. In this paper simulation results have been described which gives exact idea of spectrum sharing. Index Terms— bandwidth sharing, cognitive radio (CR), spectrum mobility
I. INTRODUCTION The latest technology uses radio devices; this every device uses the terms and policies of Federal Communication Commission (FCC) [2]. Cognitive radio is a technique which changes its parameters like operating frequency, modulation technique, transmission power etc. according to requirement for spectrum sharing purpose [4]. Fig.1 shows whole spectrum utilization [4] in which some frequency portions heavily used and some frequency portions are medium used. Remaining frequency portions are wastage. To solve this problem spectrum sharing in cognitive radio technique is required. Main feature of cognitive radio is re configurability that means devices have a capability to change parameter according to requirement. Below mentioned parameters are essentials for perfect cognitive radios [2, 4], • Operating Frequency: - CR is capable to changing operating frequency according to information based on a network for establish proper communication [4]. • Modulation: - CR is capable to reconfigure modulation techniques according to user requirement for a perfect communication [4]. • Transmission power: - CR is competent to reconfigure a transmission power according to user’s requirement and without interfering of neighbor users. They uses low transmission power but DOI: 02.ITC.2014.5.555 © Association of Computer Electronics and Electrical Engineers, 2014
Figure 1. Spectrum utilization [4]
efficient, as per requirement in this way more user can share a bandwidth [4]. • Communication technology: - CR has a capability to operate any device in communication network like universal device [4]. CR networks combine four processes; spectrum sensing, spectrum management, spectrum sharing and spectrum mobility [4, 13]. • Spectrum sensing: - In this process, CR user sense the availability of spectrum. Three main techniques; energy based detection, matched filter based detection and cyclostationary based spectrum sensing are used in cognitive radio. • Spectrum management: - In this process, CR network manages free unused portion of the spectrum. • Spectrum sharing: - In this process, after free spectrum portion sensing new CR user called secondary user uses that portion of spectrum without affecting primary user. Many techniques like game theory based, OFDM based, memo turbo coder based spectrum sharing etc., are used. • Spectrum mobility: - In this process, priority is given to the primary user, if they want to use spectrum then immediately vacant that spectrum portion which is used by secondary user [4, 7]. Spectrum sharing is a technique of cognitive radio to acquire a portion of bandwidth which is not used by primary users during that time. A. Classification of Spectrum Sharing in Cognitive Radio Basically spectrum sharing in cognitive radio is classified as internetworking architecture, intra network based spectrum sharing and spectrum access schemes [4, 12]. Which are shown in Fig. 2.
Figure 2. Classification of spectrum sharing in cognitive radio [4]
1. Internetworking Architecture based Spectrum Sharing:- This section further divided in two type centralized internetworking based spectrum sharing and distributed internetworking based spectrum sharing [4]. 474
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Centralized internetworking based spectrum sharing: - In this type of sharing, one centre entity gets all the information about network. Each user in the network gives information to central entity. According to this information central entity takes certain decisions. All the users coordinate with central entity using broadcasting messages on CSCC (Common Spectrum Coordination Channel). Distributed internetworking based spectrum sharing: - This type of spectrum sharing is beneficial where infrastructure based networking is not used. Each user is responsible for allocation of bandwidth which is based on local policies. In this spectrum sharing, data and control channel are separated which is main drawback of this network as it requires detach common control channel [4].
2. Intra Network Spectrum Sharing:-This type of network further divides in two types cooperative based and non-cooperative based intra network spectrum sharing [4]. • Cooperative based intra network spectrum sharing: - This spectrum sharing remedy considers effect of communication of user in the network with other user in network. Centralized based solution also regard as a cooperative based solution. In this network, clustering technique is proposed so according to this manner each group of user uses same control channel. A user group is reorganize and used another control channel when this required channel used by primary user. • Non-cooperative based intra network spectrum sharing: - This is based on opportunistic spectrum sharing based scheme. Here all user acquires a channel is based on interference information of neighbor’s user. Here spectrum sharing protocol for ad-hoc networks, (AS-MAC) is proposed, which gives the concepts of the RTS-CTS exchange and Network Allocation Vector (NAV) of the IEEE 802.11 MAC protocol. Transmitter and receiver handshaking is done trough common control channel [4, 12]. 3. Spectrum Access Technique based Spectrum Sharing:-This technique is mainly divided into two types overlay spectrum sharing and underlay spectrum sharing, • Overlay spectrum sharing: - For minimize interference with neighbor user; secondary user occupies only those bands of a spectrum which is not used by primary user. So in this way, this technique is very beneficial when interference between neighboring users is high. • Underlay spectrum sharing: - In this technique, ones user got the information regarding spectrum then user starts a communication, without harming primary user. This technique requires precise spread spectrum sharing techniques. Main drawback is it requires more bandwidth compare to overlay spectrum sharing technique. [4, 9] This paper is organized as follows. First section is introduction, second section is related work, problem statement and methodology is covered in third section and fourth section is about simulation results. II. RELATED WORK Many different techniques are executed by researchers from solving a problem of bandwidth shortage. In this research first Dr. J. Mitola found technique called software defined radio in 1991 [1, 6]. The author proposed cognitive radio approach for unlicensed uses. The author used policy based sharing in cognitive radio [3]. Game theory based model approach showed spectrum sharing in cognitive radio where two techniques static cournot game for Nash equilibrium and dynamic cournot game for secondary user were proposed [5]. This scheme gives two fair spectrum allocation algorithms max–min fair maximum throughput bandwidth allocation (MMBA) and lexicographical max–min bandwidth allocation (LMMBA) with fair and efficient spectrum allocation in wireless mess network with cognitive radio [8]. Auction based spectrum sharing scheme where secondary user bids a spectrum and primary user allocate the band without harming itself [10]. This scheme shows fair, efficient and power optimized (FIPO) spectrum sharing scheme in cognitive radio which better then MMF scheme. FIPO scheme uses less transmission power compared to MMF with same file size [11]. Learning based spectrum handoff scheme introduced where user predict the channel status, which is helpful to reduce spectrum handoff time [16]. Spectrum sharing scheme for telecommunication proposed where user senses the range of CR nodes [17]. The author proposed Adaptive multiple rendezvous control channel (AMRCC) based on frequency hopping scheme for bandwidth sharing among CR users. This scheme shows continuously connectivity between CR users with presence of primary users [15]. Novel strategy based cognitive radio scheme for enlarging bandwidth utilization and minimize interference introduced which normally occurred during acquisition of channel in cellular system [14]. Spatial coding based scheme used adaptive beam forming and null steering proposed for spectrum sharing between CR users without harming 475
PUs [19]. Power allocation with random removal scheme discussed which solved optimization problem in cognitive radio network (CRN) [20]. Resource allocation optimization framework for a CRN discussed in the presence of PU activities [21] and intelligent mobile agents in wireless networks proposed which manages fair distribution of network resource and bandwidth sharing among CR users [18]. III. PROBLEM STATEMENT AND METHODOLOGY This paper is mainly focused on spectrum sharing for TV channels using common control channel in which overlay CCC is used. Fig. 3 shows flow chart of spectrum sharing process.
Figure 3. Flow chart of spectrum sharing process
In this paper, five carrier frequencies 100 MHz, 200 MHz, 300 MHz, 400 MHz and 500 MHz; and 12 MHz sampling frequency is used. Assume that spectrum sensing is done before spectrum sharing takes place. When user enters into the network, test condition checks whether user is primary (PU) or secondary (SU). If PU is there then network vacant that spectrum band which is used by SU in first in first out manner (FIFO). After vacant that band, network is handed over that free band to the PU. Another condition is shown, if user is SU. Test condition checks whether any free spectrum band available or not. If yes, then allocate that free band to SU in first come first serve manner. Another condition is no free available spectrum band then SU need to wait for vacancy. IV. SIMUMATIONS AND RESULTS Simulations and their results are shown in below figures, 476
Figure 4. 200 MHz and 300 MHz bands are free
Figure 5. 200 MHz band occupied by new secondary user
Figure 7. Occupied 200 MHz band is vacant for primary user
Figure 8. Previously vacant 200 MHz band is shared by primary user
Figure 6. 300 MHz band occupied by another new secondary user
Figure 9. Impact on user presence when 20 dB noises are present
All results shows power spectral density (PSD) Vs frequency graphs. Higher level of PSD shows presence of user on that particular frequency. Fig. 4 shows primary users 1, 4 and 5 are present and they occupied 100 MHz, 400 MHz and 500 MHz TV channel frequencies. At this stage 200 MHz and 300 MHz frequency portions are empty and wasted as no one is using those bands. Fig. 5 gives clear cut idea about first come first serve base spectrum allocation. Spectrum sensing shows 200 MHz and 300 MHz frequency bands have lower PSD values compare to threshold value, so they are free bands. When new secondary user comes into the 477
Figure 10. Impact on user presence when -20 dB noises are present Figure 11. Impact on user presence when signal attenuated by 15%
network, it should be allocated 200 MHz band immediately as it is the first free slot in spectrum band. Later on if another secondary user comes into the network, it should be allocated on 300 MHz slot. This process is shown in Fig. 6. This is the situation where no any free slots are available and used slots include three primary users (on 100 MHz, 400 MHz and 500 MHz) and two secondary users (on 200 MHz and 300 MHz). In this case if new primary user demands for frequency band, existing secondary users need to vacant the slot for upcoming primary user as primary user has highest priority. Whether 200 MHz slot or 300 MHz slot should be free for upcoming primary user that depends on usage time. Slot should be free on FIFO base. In this simulation work 200 MHz slot was allocated first thus this slot should be vacant for upcoming primary user. This whole dynamic spectrum allocation process has been shown in Fig. 7. Fig. 8 shows 200 MHz frequency band is allocated to new primary user and secondary user used this band previously will loss the communication. Fig. 9 and Fig. 10 demonstrates how the noise affects this simulation results. When 20 db noises are present in channel, simulation results are same as fig. 8 which is shown in Fig. 9. It clearly revels that user information is easily detectable. If -20 db noises are added, heavy degradation in signal power is observed and even presence of user is not identified which is shown in Fig. 10. When signals are attenuated by 15 %, signal power is degraded extremely and this result is shown in Fig. 11. It clearly shows that users’ information is scrambled. V. CONCLUSION AND FUTURE WORK Spectrum sensing senses available spectrum band in the network and on the bases of that dynamic spectrum allocation for TV channel has been done. Check condition runs on control channel to find out new user is primary or secondary. Primary users have highest priority to accommodate in the spectrum band. Secondary user may need to leave the spectrum on FIFO bases and loss the communication if primary user demands for channel. Simulation results demonstrate spectrum sharing process step by step. Results also show effect of noise, heavy degradation in signal power has been observed when -20 db noise is added in the channel and it is completely destroyed if signal is attenuated by 15%. Work can be extended for faded channel in which more than -20 db noise is present. The effect of spectrum sharing can be associated with Doppler shift. ACKNOWLEDGMENT The authors are very thanking full to RK University for providing valuable resources and research platform. REFERENCES [1] J. Mitola, "The Software Radio Architecture", IEEE Communications Magazine, Vol. 33, No. 5, May 1995, pp. 2638. [2] FCC, ET Docket No 03-222 Notice of proposed rulemaking and order, December 2003. [3] L. Berlemann, S. Mangold, B.H. Walke, “Policy-based reasoning for spectrum sharing in cognitive radio networks”, in: Proc. IEEE DySPAN 2005, November 2005, pp. 1–10.
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[4] I.F. Akyildiz, W. Lee, M. Vuran, S. Mohanty, “Next generation/dynamic spectrum access/cognitive radio wireless networks: A survey”, Elsevier, Computer Networks 50 (2006) pp. 2127–2159. [5] D. Niyato, E. Hossain, “A game-theoretic approach to competitive spectrum sharing in cognitive radio networks”, IEEE Wireless communication and networking conference, March 2007, pp. 16-20. [6] Q. Yuan, P.Tao, W. Wen-bo, L. Shi-feng, “Cyclostationary signature design for common control channel of cognitive radio”, Elsevier, April 2009, 16(2): pp. 42–46. [7] I.F. Akyildiz, W. Lee, K. Chowdhury, “CRAHNs: Cognitive radio ad hoc networks”, Elsevier, Ad Hoc Networks 7 (2009), pp. 810–836. [8] J. Tang, R. Hincapie, G. Xue, W. Zhang, R. Bustamante, “Fair bandwidth allocation in wireless mesh networks with cognitive radios”, IEEE transactions on vehicular technology, vol. 59, no. 3, march 2010, pp. 1487-1496. [9] M. Khoshkholagh, K. Navaie, H.Yanikomeroglu, “Access strategies for spectrum sharing in fading environment: overlay, underlay and mixed”, IEEE Transactions on mobile computing, vol.9, No.12, December 2010, pp. 17801793. [10] X. Wang, Z. Li, P. Xu, Y. Xu, X. Gao, H. Chen, “Spectrum Sharing in Cognitive Radio Networks – An Auction based Approach”, IEEE Transaction, vol.40, Issue.3, June-2010, pp. 587-596. [11] S. Aslam, K. Lee, “Fair, efficient and power-optimized spectrum sharing scheme for cognitive radio networks”, Springer, EURASIP Journal on Wireless Communications and Networking 2011, 2011:201. [12] B. Lo, “A survey of common control channel design in cognitive radio networks”, Elsevier, Physical Communication 4 (2011) pp. 26–39. [13] L. Lu, X. Zhou, U. Onunkwo, G. Ye Li, “Ten years of research in spectrum sensing and sharing in cognitive radio”, Springer, EURASIP Journal on Wireless Communications and Networking 2012, 2012:28. [14] J. Raiyn, “Spectrum Efficiency Improvement Based on the Cognitive Radio Management, Scientific Research, Int. J. Communications, Network and System Sciences, March 2010, pp. 280-288 [15] C. Cormio, K. R. Chowdhury, “Common control channel design for cognitive radio wireless ad hoc networks using adaptive frequency hopping”, Elsevier, Ad Hoc Networks , August 2010, pp. 430–438 [16] C. Feng, W. Wang, and X. Jiang, “Cognitive Learning-Based Spectrum Handoff for Cognitive Radio Network”, International Journal of Computer and Communication Engineering, Vol. 1, No. 4, November 2012,pp. 350-353. [17] R. Kaniezhil and C. Chandrasekar, “Performance analysis of wireless network with opportunistic spectrum sharing via cognitive radio nodes”, Journal of electronic science and technology, vol. 10, no. 4, December 2012, pp. 342351. [18] N. Eric-Nwonye and O. Ekabua, “Spectrum Sharing and Spectrum Mobility in Cognitive Radio Networks using Intelligent Mobile Agents”, International Journal of Computer Applications (0975 – 8887) ,Volume 70– No.10, May 2013, pp. 5-12. [19] S. A. Hussain, A. N. Malik and I. M. Qureshi, ”Spectrum Sharing in Cognitive Radio Based on Spatial Coding”, Research Journal of Information Technology 5(2), June 2013, pp. 55-61. [20] D. Kakkar, A. khosla and M. Uddin, “Power Allocation with Random Removal Scheme in Cognitive Radio System”, Proceedings of the World Congress on Engineering 2011, Vol. 2, ISSN: 2078-0966 (Online), July 2011. [21] Y. Tachwali, B. F. Lo, I. F. Akyildiz and R. Agust´ı, “Multiuser Resource Allocation Optimization Using Bandwidth-Power Product in Cognitive Radio Networks”, IEEE, Vol. 31, No. 3, March 2013, pp. 451-463. J. A. NATHANI1 graduated B. E. in Electronics and Communication Engineering with distinction from RK College of Engineering and Technology, Saurashtra University, India, in 2010. He is pursuing M.Tech. degree in Electronics and Communication Engineering form School of Engineering, RK University, India.
A. A. BAVARVA2 has received his degree of B. E. in Electronics & communication Engineering from C. U. Shah College of Engineering & Technology, Wadhwan, India in 2005 and degree of M. E. professional in IT & Telecommunication from Deakin University, Australia in 2008. Currently he is working as Asst. Professor in Department of Electronics & communication, RK. University, Rajkot, with teaching experience of more than 3 years
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