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1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [Interference Management and Coexistence for WSN/MBANs] Date Submitted: [November, 2008] Source: [Saied Abedi] and [Hind Chebbo] Company [Fujitsu] Address [Hayes Park Central, Hayes, Middlesex, UK] Voice:[+44(0) 20 8606 4809 ], FAX: [:[+44(0) 20 8606 4539], E-Mail:[Saied.Abedi@uk.fujitsu.com], E-Mail:[hind.chebbo@uk.fujitsu.com] Abstract:[Interference Management and Coexistence for WSN/MBANs ] Purpose: [ To discuss Interference Management and coexistence between MBANs and its applicability to MBAN] Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15. Slide 1

2. Content • Problem of interference and coexistence in WSN/BANs • Existing approaches • Proposed Interference and coexistence Management Approaches • Dynamic Semi-Distributed • Centralized Gateway • Gateway to Gateway Coordination • Simulation Results • Conclusion

3. Problem of Interference and Coexistence in WSN/BANs A Futuristic Scenario: Spectrum regulation bodies consider new scenarios for allocation of new radio spectrum for medical services Soon we may have medical BANs that operate in a radio band that other non-medical applications are also present Under such scenario and considering the limited transmission power of the medical sensors, they are going to be vulnerable to the interference from the radio devices such as Wireless LAN or other wireless office incumbent applications

4. Existing Interference Management Existing interference management and radio channel allocation techniques: Distributed Centralised Pros: More Accuracy of Interference Management Pros: Less Signalling Overhead Cons: Less Accuracy of Interference Management Cons: More Signalling Overhead Considering the limited resource and capabilities of WSNs/MBAN which one of the algorithms is more suitable for WSNs/MBANs?

5. Assumptions and Interference Analysis (1) • A cell/picocell/MBAN consists of a fixed Number of sensors which communicate to a base station BS or sink; • Radio network consists of J sink/BSs mobile or fixed. Each sink/BS is associated with a particular MBAN • Sinks are distributed uniformly in a square region of dimension LxL • N MBAN/MBAN sinks form a cluster • Each cluster has a leader sink • Radio channels are shared between sinks • Sink listen to a number of channels and measure the interference received • P sub channels available in the radio spectrum • Each sink can transmit on M channels (M<P) Direct communications between the sensors and sink/base station

6. Assumptions and Interference Analysis- A Generic Interference Model (2) • Interference from sink i on sink j at radio channel Sm: • Interference inflicted on sink i from sink j at radio sub- channel Sm: Where interference function with sinks i and j are both transmitting over the m-th channel m otherwise transmission power of Sink i Overall transmission gain associated with the link from sink i to j

7. The overall interference received on sink i from all other sinks in the cluster The overall interferenceinflicted by sink ion other base stations in the cluster The interference inflicted on all sinks within a cluster The Total traffic loads handled by a sink i Where k is kth buffer of the sink K number of buffers of sink i The Signal to interference ration of sink i Where Si signal power received at sink i Assumptions and Interference Analysis- A Generic Interference Model(3)

8. Content • Problem of interference and coexistence in WSN/BANs • Existing approaches in the literature • Proposed Interference and coexistence Management Approaches • Dynamic Semi-Distributed • Centralized Gateway • Gateway to Gateway Coordination • Simulation Results • Conclusion

9. Dynamic Semi-Distributed Approach • Rational • To overcome the problem of distributed interference management • Takes advantage of both centralized and distributed interference management to improve the QoS while keeping the complexity of sensor low • Three scenarios considered • Scenario 1: Dynamic Cluster BasedInterference management • Scenario 2: Merging clusters in critical conditions • Scenario 3: Reducing the centralization effect by breaking down to smaller clusters

10. Dynamic Semi-Distributed-Scenario 1 Proposed protocol

11. Dynamic Semi-Distributed-Scenario 1 Examining the sub-channels to get the best combination for minimum interference

12. Dynamic Semi-Distributed Scenario 2 • Merging cluster in critical situation Interference experienced by the red cluster can not be handled by the leader of the affected cluster Leader of “Red” cluster asks leader of “Blue” cluster to consider a potential merger to perform a joint radio sub-channel allocation process

13. Dynamic Semi-Distributed Scenario 2 A Cauterized Approach Blue cluster leader informs all the member sinks of upcoming change and triggers the merging process of clusters

14. Dynamic Semi-Distributed - Scenario 2 Merged Cluster of MBANs Transforming the entire cluster to a blue cluster

15. Dynamic Semi-Distributed- Scenario 3 Reducing the effect of centralisation by breaking into clusters • The situation described in Scenario 2 is only temporarybasis. • When the entire cluster is blue the cluster may be split back to the original clusters configuration. • The leader of joint cluster might ask former cluster leaders to examine their interference level. • If all the former clusters are out of “red” the cluster leader would ask for breaking into clusters and give the autonomous decision-making capability back to the cluster leaders.

16. Dynamic Semi-Distributed- Simulation Results • Topology considered: • Random topology of MBANs consisting of four interfering sinks. • Results are theoretical only; no real measurement has been performed • Traffic • An extreme case is considered where all the transmitting sinks and their associated sensors are in transmission mode continuously • Same transmission power for all sensors • Assigned number of MBANs to a cluster is assumed • BER = 10-3 • Reed-Muller channel code RM(1,m), coding rates combinations and the corresponding SIR target requirement are similar to [10]

17. Dynamic Semi-Distributed- Simulation Results Before completion of radio channel allocation process After completion of radio channel allocation process Significant reduction of interference level for a cluster of BAN/MBANs at sub-channel level is observed, for each sink transceiver, narrow blue line bar represents the interference inflicted on other transceivers on current sub-channel, red bold line bar represents the interference inflicted from other sinks in current sub-channel, INT2 represents the overall interference inflicted on other Sinks from sink of interest, Diamond stands for Sink/BS

18. Content • Problem of interference and coexistence in WSN/BANs • Existing approaches in the literature • Proposed Interference and coexistence Management Approaches • Dynamic Semi-Distributed • Centralized Gateway • Gateway to Gateway Coordination • Simulation Results • Conclusion

19. Centralised GateWay Approach • Rational • To overcome interference in scenarios of heavy loaded scenarios and using the semi distributed approach • Resort into centralised approach; this requires the existence of interfaces between lower radio entities (sink/BSs) and a central entity such as gateway • Focus on novel trigger mechanisms and protocols to create an efficient interaction between the distributed and centralised interference management

20. Centralised Gateway Approach- Triggering Mechanisms • Trigger 1:Overwhelming number of conflicts in a mass sensor deployment scenario • Trigger 2: The joint clustering process reaches its maximum size and despite that it is still in red. • Trigger 3: Initialization before the semi-centralized dynamic sub-channel allocation process

21. Centralised Gateway Approach- Trigger 1 Large number of clusters of WSNs (e.g.MBAN or BAN) is in “red” (i.e. high interference conditions) • Addition of a Gateway that centrally assigns radio channels to sinks • Gateway centralized scheme is to reshuffle the radio sub-channels for better conditions in terms of the inflicted interference.

22. Centralised Gateway Approach - Trigger 2 The joint clustering process reaches its maximum size and despite that it is still in red.

23. Centralised Gateway Approach- Trigger 3 Initialization before the semi-distributed dynamic sub-channel allocation process • Creates a better starting point in terms of inflicted interference for each one of the future potential clusters. • After a successful channel allocation process, the centralized GW gives a localized autonomous power and decision making capability to the clusters involved.

24. Centralised Gateway Approach- ProposedProtocol

25. Centralised Gateway Approach-Simulation Results

26. Content • Problem of interference and coexistence in WSN/BANs • Existing approaches in the literature • Proposed Interference and coexistence Management Approaches • Dynamic Semi-Distributed • Centralized Gateway • Gateway to Gateway Coordination • Simulation Results • Conclusion If hybrid of distributed and centralized interference management fails to solve the problem of high interference from other wireless system with more aggressive power, we propose a dialogue between medical BAN/WSN and those radio system to clear the sub-channels that make problem for medical system or consider new sub-channel allocations which is less problematic for MBAN/WSN systems and ongoing crucial life saving medical procedure.

27. Inter System Dialogue: Gateway to Gateway Coordination (1) • Rational • Due to severe interference, WSNs/MBANs may fall victim to another wireless system with much higher transmission power as shown in the Figure below. • In this case the inter-system interference management will play a crucial role in guaranteeing the required Quality of Service for the victim system such as MBAN Victim

28. Cluster 1: Dynamic Fast Sub-Channel Allocation Second Attempt (Red) Cluster 1: Dynamic Fast Sub-Channel Allocation First Attempt (Blue) Gateway Centralized Sub-Channel Allocation and Interference Mitigation Joint Cluster : Dynamic Fast Sub-Channel Allocation Attempt (Red) Cluster 2: Dynamic Fast Sub-Channel Allocation Second Attempt (Red) Cluster 2: Dynamic Fast Sub-Channel Allocation First Attempt (Blue) Gateway Centralized in Red Only Occasional Triggering to Reshuffle the Radio Channels Going in reverse order, means giving back the autonomous capability to each cluster of MBAN/BAN Call GW-to-GW Coordination Time Progress Inter System Dialogue: Gateway to Gateway Coordination (2)

29. Gateway to Gateway Coordination- Protocol(1)

30. Gateway 1 WSN Gateway to Gateway Coordination - Protocol (2)

31. Gateway to Gateway Coordination - Simulation Results Results of GW-to-GW coordination for interference management and channel allocation process, significant reduction of interference level for a cluster of BAN/MBANs at sub-channel level is observed, for each sink transceiver, narrow blue line bar represents the interference inflicted on other sink transceivers on current sub-channel level, red bold line bar represents the interference inflicted from other sinks in current sub-channel, INT2 represents the overall interference inflicted on other sinks from each sink of interest, Diamond stands for Sink (MBAN or BAN).

32. Discussions and Relevance to IEEE802.15.6 • Although the proposed protocols for interference management and coexistence seems to be at higher layers of 15.6, the following exchange of information is required from 15.6 layers: • Semi-distributed protocol • Traffic load/buffer occupancy of sensors are required by the sink to determine the required number of sub-channels for a particular MBAN • Radio Sub channels for a sensor to be acquired by the sink as Sink assigns them to sensors • Go ahead signal from sink to sensor to test transmit in order to determine the interference caused by one MBAN on other MBANs • Centralised protocol • List of transmission powers used by sensors and sinks to be sent to the Gateway • Go ahead signal from sink to sensor to test transmit in order to determine the interference caused by one MBAN on other MBANs • GW-to-GW coordination • Go ahead signal from sink to sensor to test transmit in order to determine the interference caused by one MBAN on other MBANs

33. Content • Problem of interference and coexistence in WSN/BANs • Existing approaches in the literature • Proposed Interference and coexistence Management Approaches • Dynamic Semi-Distributed • Centralized Gateway • Gateway to Gateway Coordination • Simulation Results • Conclusion

34. Conclusions • If MBAN/WSNs are allowed to share the bandwidth with other radio networks, due to life saving nature of some medical application and the required high reliability, they will need more robust interference management and radio channel allocation techniques. This is to protect them against radio networks with more aggressive and much higher transmission powers • Therefore, hybrid of distributed and centralized interference management and channel allocation techniques is preferred and proposed • If hybrid of distributed and centralized interference management fails to solve the problem of high interference from other wireless system with more aggressive power, we propose a dialogue between medical BAN/WSN and those radio system to clear the sub-channels that make problem for medical system or consider new sub-channel allocations which is less problematic for MBAN/WSN systems • In order to make the proposed protocols feasible in real life applications, it is necessary to include the necessary signaling middleware for radio incumbentsystems that are going to share spectrum with MBANs under future and emerging standards such as IEEE 802.15.6.

35. References (1) • [1] Saied Abedi, Methods for Interference Management in Medical Wireless Sensor Networks accepted for publication in Journal of Communications Software and Systems (JCOMSS), Special issue on Medical Applications for Wireless Sensor Networks • [2] IEEE Standard for Information technology Telecommunications and information exchange between systems- Local and metropolitan area networks- Part 15.3:Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for High Rate Wireless Personal Area Networks (WPANs) • [3] David Davenport, “Medical Body Area Network Application”, GE Global Research, Contribution to IEEE Standard Working Groups, IEEE 802.15-08-0108-01-0006, • [4] IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)[3] Saied Abedi, “Interference Management in Wireless Sensor Networks, Part I: Dynamic Semi-Distributed Mechanisms”, IEEE SENSORCOMM 2008, 24-30 August2008, Cap Esterel, France, in conference proceedings. • [5] Tau Wu, Subir Biswas , “Reducing Inter-Cluster TDMA Interference by Adaptive MAC Allocation in Sensor Networks”, Proceedings of the First International IEEE WoWMoM Workshop on Autonomic Communications and Computing (ACC'05) - Volume 02, Pages: 507 – 511. • [6] Tau Wu, Subir Biswas, “Minimizing inter-cluster interference by self-reorganizing MAC allocation in sensor networks”, Wireless Networks, Volume 13, Issue 5 (October2007), Pages: 691 – 703. • [7] IEEE Standard for Information technology Telecommunications and information exchange between systems- Local and metropolitan area networks- Specific requirements. Part 15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs) • [8] X. Xinsheng; L. Qilian, “Packets Transmission in Wireless Sensor Networks: Interference, Energy and Delay-Aware Approach”, Wireless Communications and Networking Conference, 2007.WCNC 2007. IEEE 11-15 March 2007Page(s):2501 – 250 • [9] F. Nekoogar, F. Dowla, A. Spiridon, “Self organization of wireless Sensor networks using ultra-wideband radios”, Radioand Wireless Conference, 2004 IEEE, 19-22 Sept. 2004Page(s):451-454.

36. References (2) • [10] T. Jenn Yue, H. Yajun; T. Khong, “Interference-Minimized Multipath Routing with Congestion Control in Wireless Sensor Network for High-Rate Streaming ”,IEEE Transactions on Mobile Computing, Volume PP, Iss Sensor 99, 2003, Digital Object Identifier10.1109/TMC.2008.24. • [11] F. Ordonez, B. Krishnamachari, “Optimal information extraction in energy-limited wireless Sensor networks”, IEEE Journal on Selected Areas in Communications, Volume 22,Issue 6, Aug. 2004 Page(s):1121 – 1129 • [12] G. Cimatti, R. Rovatti, G. Setti, “Chaos-Based Spreadingin DS-UWB Sensor Networks Increases Available Bit Rate”,IEEE Transactions on Circuits and Systems I: Regular Papers,Volume 54, Issue 6, June 2007 Page(s):1327 – 1339.[12] Jenn Teo, Ha Y Ue Tham Yajun, Khong Chen ,“Interference-Minimized Multipath Routing with Congestion Control in Wireless Sensor Network for Multimedia Streaming”, IEEE MILCOM 2007. 29-31 Oct. 2007 Page(s):1-7 • [13] N. Nie, C. Comaniciu, “Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks”, Proceedings of IEEE DySPAN, November 2005. • [14] A. Mpitziopoulos, D. Gavalas, G. Pantziou, C.Konstantopoulos, “Defending Wireless Sensor Networks from Jamming Attacks”, Personal, Indoor and Mobile Radio Communications, 2007. PIMRC 2007, IEEE 18thInternational Symposium on Publication Date: 3-7 Sept. 2007On page(s): 1 - 5 Number of Pages: 1 – 5 • [15] Muhammad Adib Haron, Sharifah Kamilah Syed Yusof,Norsheila Fisal, Sharifah Hafizah Syed Ariffin, Adel Abdallah,;“Performance Study of the Coexistence of Wireless Sensor Networks (WSN) and Wireless Local Area Networks (WLAN)”, International Conference on Modeling &Simulation, 2008. AICMS 08. Second Asia 13-15 May 2008Page(s):475 – 479 • [16] Fatiha Djemili Tolba, Damien Magoni, Pascal Lorenz,“Energy Saving and Connectivity Trade-off by Adaptative Transmission Range in 802.11g MANETs”. ICWMC 2006[17] Fatiha Djemili Tolba, Damien Magoni, Pascal Lorenz, “AStable Clustering Algorithm for Highly Mobile Ad Hoc Networks”, ICSNC 2007

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