Cognitive Radio Networks Part II

Transcription

1 Cognitive Radio Networks Part II Page 1

2 Part II organization Cognitive Radio Network Fundamentals for Cognitive Radio Reconfiguration, adaptation, and optimization Cognitive Research: Knowledge Representation and Learning Cognitive radio performance analysis: Applying Game Theory to the Analysis Problem Cognitive radio for broadband wireless access in TV bands: The IEEE standards Networks(NGN) Page 2

3 Fundamentals for Cognitive Radio Page 3

4 Radio Allocation Radio Flexibility and Capability Spectrum Management Cognitive Radio Cognitive Radio Networks Architecture Enabling technologies Implementation Standards Applications Summary Outline Page 4

5 Spectrum Allocation allochrt.pdf Page 5

6 Spectrum Utilization papers/chicagospectrum McHenry Session I 1.pdf Page 6

7 In Summary Spectrum scarcity is largely due to Inefficient fixed frequency allocations and utilization rather than any physical shortage of spectrum So, a new radio technology is needed with the following characteristics: Flexibility Reconfigurability Awareness Adaptability Intelligence Page 7

8 Radio Flexibility and Capability Software capable radio: Fixed modulation capabilities Small number of frequencies Software Programmable radio: Ability to add new functionality through software changes Advanced networking capability Software-Defined Radio: Complete adjustability through software of all radio operating parameters Software capable radio Software Programmable radio Software Defined radio Aware Radio: Radio that sense all or part of their environment Adaptive Radio: Radio that modify its operating parameters Cognitive radio: Radio is aware, adaptive and learn Aware radio Adaptive radio Cognitive radio Increasing Technology/Software Maturity Page 8

9 Spectrum management Dynamic Spectrum Management: Fair allocation of spectrum Users with the same rights (Horizontal sharing) Users with the different rights (Vertical sharing) Centralized vs. Decentralized Centralized Approach Need for a center for collecting radio scene information Globally optimal solution Decentralized Approach Utilization of self-organization principle Scalable Suboptimal Page 9

10 Spectrum management Page 10

11 Hierarchical Access Model Spectrum Underlay Secondary users (SUs) operate below the noise floor of primary users (PUs) Short-range high data rate with extremely low transmission power E.g. UWB Spectrum Overlay Investigated by the DARPA Next Generation (XG) program under the term opportunistic spectrum access (OSA) SUs identify and exploit local and instantaneous spectrum availability in a nonintrusive manner Page 11

12 Cognition, Cognitive radio and Cognitive networks Cognition Mobile device Cognitive radio Cognitive networks Page 12

13 Cognition and cognitive radio Page 13

14 What is a Cognition? According to the Encyclopedia of Computer, three-point computational view of cognition is listed Mental states and processes intervene between input stimuli and output responses The mental states and processes are described by algorithms The mental states and processes lend themselves to scientific investigations Pfeifer and Scheier: the interdisciplinary study of cognition is concerned with exploring general principles of intelligence through a synthetic methodology termed learning by understanding. Page 14

15 What is a Cognitive Radio Definitions Federal Communications Commission Definition: Cognitive radio is a radio that can change its transmitter parameters based on interaction with the environment in which it operates Mitola Definition: Cognitive radio identifies the point at which wireless PDAs and the related networks are sufficiently computationally intelligent on the subject of radio resources and related computer-to-computer communications to detect user communications needs as a function of use context, and to provide radio resources and wireless services most appropriate to those needs Simon Haykin Definition: Cognitive radio is an intelligent wireless communication system that is aware of its surrounding environment (i.e., outside world), and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters (e.g., transmit-power, carrier-frequency, and modulation strategy) in real-time, with two primary objectives in mind: highly reliable communications whenever and wherever needed efficient utilization of the radio spectrum Page 15

16 Cognitive Cycle: Mitola Page 16

17 Cognitive Cycle: Akyildiz Page 17

18 Spectrum Opportunity Spectrum opportunity: A band of frequencies that are not being used by the PU of that band at a particular time in a particular geographic area Page 18

19 Spectrum Opportunity A channel is an opportunity to A and B if: No PUs within a distance of from A are receiving and No PUs within a distance of from B are transmitting over this channel is determined by the SU transmission power and the maximum allowable interference to PUs is determined by the PUs transmission power and the SUs interference tolerance Page 19

20 Cognitive radio architecture Cognitive engine: Establishes interfaces among the SDR transceiver, adaptive protocols, and wireless applications and services Uses intelligent algorithms Cognitive engine Application Transport Network MAC SDR transceiver Adaptive protocol Adaptive protocols: Aware of the variations in the cognitive radio environment consider the traffic activity of primary users Consider the transmission requirements of secondary users, and variations in channel quality Transmit/ receive Page 20

21 Cognitive radio network Page 21

22 Cognitive radio network Definitions: R. W. Thomas definition: Cognitive network is a network with a cognitive process that can perceive current network conditions, and then plan, decide, andact on those conditions. The network can learn from these adaptations and use them to make future decisions, all while taking into account end-to-end goals. Haykin definition: The cognitive radio network is an intelligent multiuser wireless communication system with the following abilities: To perceive the radio environment (i.e., outside world) by empowering each user s receiver to sense the surrounding environment continuously. To learn from the environment and adapt to it in response to deviations in the environment. To facilitate communication among multiple users through co-operation in a self-organized manner. To control the communication resources among the multiple users through competition. To create the experience of intention and self-awareness. Page 22

23 Cognitive radio network: example S 1 is a source node and D 1 is the destination node R 1 and R 2 acting as regenerative relays Node S1 performs a link adaptation by choosing the relay node based on The set of minimum hop routes to D 1 and The probability of link outage Nodes R 1 and R 2 are both in the set of minimum hop relays on routes to D 1 Node S 1 selects the link on which to transmit by observing the outage probabilities on the links to R 1 and R 2 and selecting the link with the lower outage probability This guarantees that the transmitted packets have the highest probability of arriving correctly at the relay node No guarantee about the end-to-end performance Destination Source Page 23

24 Cognitive radio network: example Cognitive network uses observations from all nodes to compute the total path outage probabilities from S 1 to D 1 through R 1 and R 2 Suppose that nodes S 1 and S 2 are both routing their traffic through R 2 R 2 becomes congested because of a large volume of traffic coming from S 2 The cognitive process is then able to respond to the congestion, perhaps by routing traffic through R 1 and/or R 3 Destination Destination Congestion Source Source Page 24

25 Cognitive Radio Network Architecture Page 25

26 Cognitive Radio Network Architecture Primary networks Networks with access right to certain spectrum bands, e.g. common cellular systems and TV broadcast networks Users of these networks are referred to as primary users. They have the right to operate in licensed spectrum Users of certain primary network do not care of other primary or secondary networks users Secondary networks Do not have license to operate in the spectrum band they currently use or aim at using Opportunistic spectrum access Users of these networks are referred to as secondary users. They have no right to access licensed bands currently used Additional functionalities are required to share licensed spectrum bands with other secondary or primary networks Page 26

27 Spectrum Sensing T. Yucek and H. Arslan Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications IEEE Communications Surveys & Tutorials, Vol. 11, No. 1, First Quarter 2009 Page 27

28 Spectrum Management Spectrum bands are spread over wide frequency range including licensed and unlicensed bands Radio environment characteristics show fast and mostly not predictable variation over time Secondary users have to select the best spectrum band meeting their QoS requirements spectrum management functions are required Spectrum management include following steps Spectrum sensing Spectrum analysis Spectrum decision Page 28

29 Spectrum Analysis Characterizes sensed spectrum holes to obtain the band appropriate for user s requirements Characteristics of spectrum holes Interference Some spectrum bands are more crowded than others Based on the interference at primary receivers, the allowed sending power of secondary user can be derived channel capacity is estimated Path loss Path loss increases as frequency increases. To retain the capacity when switching to higher frequency, sending power should be increases more interference produced Wireless link errors Modulation scheme and interference affect strongly the error rate Link layer delay Affected by the interference, path loss, etc. Holding time Expected time duration the secondary user can occupy the channel Page 29

30 Spectrum Decision Once spectrum bands are characterized, the band best meeting QoS requirements should be selected spectrum decision function should be aware of QoS requirements of current ongoing applications Spectrum decision rules are required QoS requirements for secondary user Data rate Acceptable error rate Delay... Page 30

31 Challenges Decision Model Development of suitable decision rules that consider spectrum bands characters is until now an open issue Multiple spectrum band decision In case secondary users are capable of using multiple channels for transmission simultaneously, it is important to determine the number of spectrum bands available and select the bands appropriate Spectrum decision over heterogeneous spectrum bands Support spectrum decision operations on both licensed and unlicensed bands is challenging Page 31

32 Spectrum Mobility The process when a secondary user changes its frequency of operation, also called spectrum handoff as well Reasons Operating channel becomes worse Primary user wants to communicate on the channel User movements (available spectrum bands change) Requirements Low latency Transparence to upper layers protocols if possible No impairments on ongoing applications (ideal case) Multi-layer mobility management with which protocols of many layers cooperate to support mobility is required Page 32

33 Challenges Smooth spectrum mobility schemes Synchronization between protocols of many layers and possibly with applications to support smooth spectrum handoffs (e.g. applications or protocols switch from operation mode to another upon prediction of a spectrum handoff, etc.) Support of horizontal (changing channels while staying in the same secondary network) and vertical handoffs (between secondary networks) Performing spectrum handoffs to maintain QoS requirements satisfied Page 33

34 Spectrum Sharing Considered similar to Medium Access Control (MAC) issue in existing systems. However, different challenges arise due to Coexistence with licensed users Wide range of available spectrum Spectrum sharing steps Spectrum sensing: detect unused spectrum holes Spectrum allocation: allocation of possible target channels based on spectrum sensing results and allocation policies Spectrum access: coordination of access to the allocated channel to avoid collisions Transmitter-receiver handshake: negotiation of communication channel between sender and receiver Spectrum mobility: enable continuous communication between sender and receiver in spite of primary user appearance on the used channel Page 34

35 Spectrum Sharing Techniques Spectrum sharing techniques are classified according to Architecture Centralized Centralized entity controls the spectrum allocation and access Secondary users do observations and report to the centralized entity, which creates spectrum allocation map Distributed Applied when construction of infrastructure is not possible or not preferable Each node is responsible for the spectrum allocation Page 35

36 Spectrum Sharing Techniques Spectrum allocation behavior Cooperative - Observations results of each node are shared with other nodes spectrum allocation is done based on these measurements - These techniques result in better spectrum utilization at the cost of considerable signaling between nodes Non-cooperative (selfish) - Each node does its observations and allocates its spectrum band - These techniques result in reduced spectrum utilization. However, they may be practical for certain applications or situations Spectrum access technology Overlay spectrum sharing - Secondary nodes access spectrum holes not used by primary networks Interference to primary users is minimized Underlay spectrum sharing - Based on spread spectrum techniques developed for cellular networks - After acquiring spectrum allocation map, secondary users begin sending, so that their transmission power is regarded as noise by licensed users Page 36 36

37 Intra/Inter-Network Spectrum Sharing Classified according to Architecture Spectrum allocation behavior Spectrum access technology Inter-network spectrum sharing (see the previous two slides) Secondary user (operator1) Secondary user (operator2) Intra-network spectrum sharing Inter-network spectrum sharing Centralized inter-network spectrum sharing: secondary networks organize cooperatively the spectrum allowed to be accessed by users of each secondary network, e.g. by means of central spectrum policy server, etc. Distributed inter-network spectrum sharing: BSs of secondary networks compete to allocate spectrum holes Page 37 37

38 Common control channel (CCC) Tasks Challenges Transmitter-receiver handshake Communication with a central entity organizing the spectrum allocation Sensing information exchange Problems Fixed CCC is infeasible (CCC must be vacated when a primary user appears on it) CCC for all users seems to be topology-dependent, thus CCC varies over time If no CCC is allocated, transmitter-receiver handshake becomes a challenge Dynamic radio range Radio range and characteristics change with operating frequency CCC must be selected carefully (better to select CCC in lower spectrum bands and data channels in higher ones) Page 38

39 Enabling technologies, implementation and standards Page 39

40 Should a Regulator Allow Cognitive Access? Possible actions that may be taken by regulators: Page 40

41 Enabling Technologies Page 41

42 Cognitive radio implementation Reconfigurable Software/Hardware Systems Software (Gnu Radio, Iris, OSSIE) Hardware (USRP) Composite Systems Combination of purely software and hardware e.g. WARP and BEE Page 42

43 Software GNU Radio s Main characteristics: SDR with the most widespread usage Open source software Hardware independent signal processing functionalities Signal processing blocks ==> C and C++ Signal flow graphs and visualization tools ==> Python Python application can pause the execution, reconfigure the components and connections, and resume execution Page 43

44 Software Iris s main characteristics: General-purpose processor-based Rapid prototyping and deployment system Radio component ==> C++ Signal chain construction and characteristics ==> XML OSSIE s main characteristics: A major Linux-based open source SDR software kit Written in C++ Implements an open source version of the Software Communication Architecture (SCA) Supports multiple hardware platforms Page 44

45 Comparison: Software GNU Radio Language C++, Python Runtime Reconf. Network stack support Embedded systems support Component based architecture x Iris C++ OSSIE C++ x x : Fully supported : Partly supported x: Not supported Page 45

46 Hardware Universal Software Radio Peripheral (USRP) The most commonly used RF frontend USRP 2: Four high-speed analog-digital converters (ADCs) Xilinx Spartan FPGA for interpolation, decimation, and signal path routing Gigabit Ethernet USRP E100: An embedded stand alone system Combination of a TI OMAP 3 processor and a Xilinx Spartan 3A-DSP FPGA. Page 46

47 Composite systems Wireless Open-Access Research Platform (WARP) A complete hardware and software SDR design Very similar in approach to the USRP Motherboard Acquisition board Daughterboards Data collection boards Motherboard is connected to PC via gigabit Ethernet Software development Multilayered ranges from low-level very high speed integrated circuit VHDL coding to Matlab modeling Page 47

48 Composite systems Berkeley Emulation Engine (BEE) A modular, scalable FPGA-based computing platform with a software design methodology Five, high-performance Xilinx FPGAs (Virtex II Pro 70) Each FPGA embeds a PowerPC 405 core minimizes latency and maximized data throughput runs a modified version of Linux and a full IP protocol stack Up to 20GB of high-speed, DDR2 DRAM memory Page 48

49 Comparison: Hardware USRP2 (Universal Software Radio Peripheral) WARP (Wireless Open Access Research Platform) Developed by Ettus Rice University BEE2 (Berkeley Emulation Engine) Berkeley Wireless Research Center RF bandwidth (MHz) Frequency range (GHZ) Processing architecture DC ( ) FPGA FPGA FPGA Connectivity Gigabit Ethernet Gigabit Ethernet Ethernet No. of antennas ADC performance 400 MS/s, 16 bit 125 MS/s, 16 bit 64 MS/s, 12 bit Community support yes yes no P. Pawelczak,. Cognitive Radio: Ten Years of Experimentation and Development IEEE Communications Magazine, March 2011 Page 49

50 IEEE SCC41 organization structure Page 50

51 IEEE Standard IEEE is a standard for Wireless Regional Area Network (WRAN) Specification: TV white Space: VHF/UHF bands (54 MHz 862 MHz) Centralized approach for available spectrum discovery Point to multipoint basis System is formed by Base Stations (BS) and Customer-Premises Equipment (CPE) BSs control the medium access for all the CPEs attached to it Capability of performing a distributed sensing OFDMA is the modulation scheme for transmission in up and downlinks GPS-based is supported Page 51

52 IEEE Standard Page 52

53 Potential applications of cognitive radio Next generation wireless networks Coexistence of different wireless technologies Intelligent transportation system Emergency networks Military networks Page 53

54 Summary Cognitive radio technology is a promising technology for efficient utilization of the available spectrum SDR is one of the most important technology for enabling Cognitive Radio USRP is the most popular HW for Cognitive Radio Research community Universities and Research Centers IEEE P1900 (Different Groups) IEEE (First Cognitive Radio Wireless RAN standard) More efforts are still needed for real implementation of Mitola s cognitive radio cycle Lots of applications for cognitive radio networks Page 54

55 References I.F. Akyildiz, W.Y. Lee, M.C. Vuran, S. Mohanty, NeXt Generation/Dynamic Spectrum Access/Cognitive Radio Wireless Networks: A Survey, Computer Networks Journal, 2006 S. Haykin, Cognitive radio: brain-empowered wireless communications, IEEE Journal on Selected Areas in Communications, 2005 H. Arslan Cognitive radio, software defined radio, and adaptive wireless systems, Springer, 2007 J.J. Mitola, Cognitive Radio - An Integrated Agent Architecture for Software Defined Radio, Doctoral thesis, Royal Institute of Technology (KTH), Teleinformatics, ISSN 1403 ISSN , Stockholm, 2000 A. Ralston and E. D. Reilly, Encyclopedia of Computer Science. New York: Van Nostrand, 1993, pp R. Pfeifer and C. Scheier, Understanding Intelligence. Cambridge, MA: MIT Press, 1999, pp. 5 6 E. Hossain, D. Niyato and Z. HanDynamic Spectrum Access and Management in Cognitive Radio Networks, Cambridge University Press, 2009 P. Pawelczak,. Cognitive Radio: Ten Years of Experimentation and Development IEEE Communications Magazine, March 2011 P. D. Sutton,.. Iris: An Architecture for Cognitive Radio Networking Testbeds IEEE Communications Magazine, September 2010 C. Stevenson, G. Chouinard, L. Zhongding, H. Wendong, S. Shellhammer, W. Caldwell, IEEE : The first cognitive radio wireless regional area network standard, IEEE Communications Magazine, 2009 R.W.Thomas,D.H.Friend,L.A.DaSilva,andA.B.MacKenzie, Cognitive Networks: Adaptation and Learning to Achieve End-to-End Performance Objectives, IEEE Communications Magazine, December 2006 IEEE P DRAFTv1.0 Draft Standard for Wireless Regional Area Networks Part 22: Cognitive Wireless RAN Medium Access Control (MAC) and Physical Layer (PHY) specifications: Policies and procedures for operation in the TV Bands, April 2008 Page 55

56 Contact Ilmenau University of Technology Dr. Ing. Mohamed Kalil Tel: +49 (0) e mail: mohamed.abdrabou@tu ilmenau.de Visitors address: Technische Universität Ilmenau Helmholtzplatz Zuse Building Room F 1071 D Ilmenau ilmenau.de/ics Page 56