Basics of Cognitive Radio Networks with examples of CR-oriented protocol design

Transcription

1 Basics of Cognitive Radio Networks with examples of CR-oriented protocol design Loreto Pescosolido Corso di Reti Avanzate a.a

2 Spectrum occupancy with current technologies Current wireless networks, operating in eir licensed or unlicensed bands, almost occupy entire available spectrum for nowadays commercial communication technologies. Yet demand for spectrum is constantly increasing, pushed by availability of new services, eir entirely new, or formerly thought for wired networks. It is a fact, however, that in most licensed bands, actual percentage of spectrum usage is under 5%, or in some cases, in order of % Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 2/38

3 Spectrum occupancy with current technologies Fixed Spectrum Assignment: Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 3/38

4 Spectrum occupancy with current technologies Effective bandwidth usage: PSD (Power Spectrum Density GHz Freq (GHz ~ ~2 2~3 Utilization(% ~4 4~5 5~ Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 4/38

5 Cognitive Radio Networks Question: Is re a way to improve spectrum usage, both in licensed and unlicensed bands (irrespective of different networks and technologies that already operate in those bands? A possible answer is given by Cognitive Radio ( A radio or system that senses and is aware of its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly. [ITU (Wp8A working document 5], and Cognitive Radio Networks. One flavor of Cognitive Radio Networks is represented by Dynamic and Opportunistic Spectrum Access networks. Such networks have capability to use or share spectrum in an opportunistic manner. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 5/38

6 Cognitive Radio Networks Spectrum Band Unlicensed Band Primary Network Access CR User Licensed Band I CR Ad Hoc Access Spectrum Broker Primary User Primary Base-station CR Network Access CR Base-station Licensed Band II Or Cognitive Radio Networks Primary Networks Cognitive Radio Network (Without Infrastructure Cognitive Radio Network (With Infrastructure Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 6/38

7 Sketch of main functionalities What are main functionalities that a cognitive network should implement and that are not implemented by conventional networks/ users? Identify current opportunities for spectrum (or channels utilization! Spectrum Sensing! Spectrum Decision! Spectrum Sharing Be able to vacate that spectrum (or channel if a licensed user wants to use that resource.! Spectrum mobility Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 7/38

8 Sketch of main functionalities Identification of opportunities, also termed spectrum holes, for channel use from cognitive network.! Spectrum sensing The capability of a cognitive terminal (or of a set of cognitive terminals to monitor spectrum bands and distinct channels in which cognitive network is supposed to operate, to detect presence of primary users in each channel, and overall primary users activity in each ub-band. Spectrum sensing can be, depending on scenario, distributed or centralized, cooperative or non-cooperative.! Spectrum decision Given set of candidate available bands, obtained through sensing and long term statistics, cognitive users determine best spectrum band to use. The choice can be driven not only from channel quality, but also from internal or external policies.! Spectrum sharing - ultiple CR users try to access spectrum CR network access should be coordinated in order to prevent multiple users colliding in overlapping portions of spectrum. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 8/38

9 Sketch of main functionalities Capability to vacate a spectrum (or channel currently used by a cognitive terminal if a licensed user wants to use that resource.! Spectrum mobility When a channel, or an entire band, that is being currently used from cognitive radio network is accessed by a licensed (or high priority user, that resource must be vacated from CRs on fly and in shortest possible time. This should be done preserving connectivity of cognitive users " spectrum handoff.! Different levels of granularity - The above procedure could be implemented at channel level within same band, or at band level, i.e. between entire portions of spectrum " same as spectrum decision spectrum sharing. Idle spectrum band Occupied by primary users Frequency(Hz Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 9/38

10 Cognitive cycle Transmitted Signal Spectrum obility Spectrum Sharing Radio Environment Decision Request Primary User Detection Spectrum Hole Channel Capacity RF Stimuli Spectrum Sensing Spectrum Decision Spectrum Characterization Primary User Detection Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 /38

11 Impact on protocol stack Application Control Application QoS Requirements Handoff Delay, Loss Transport Reconfiguration Spectrum obility Function Routing Information Link Layer Delay Spectrum Sharing Network Layer Link Layer Routing Information/ Reconfiguration Scheduling Information/ Reconfiguration Spectrum Decision Function Sensing Information Physical Layer Spectrum Sensing Sensing Information / Reconfiguration Handoff Decision, Current and Candidate Spectrum Information Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 /38

12 Reconfigurability Spectrum decision, sharing, and mobility, require a high level of reconfigurability of radio interface of cognitive users. They should be able to co-exist with different wireless communication technology. It is advisable for cognitive network transmission technology to have a high degree of self-reconfiguration. Reconfigurable parameters:! Operating Frequency! odulation! Transmission Power! Communication Technology Air interfaces developed following a unified framework, e.g., for different access schemes (TDA, CDA, OFDA, have potential to obtain a high degree of self-reconfigurability at a lower cost with respect to a system that implements, in parallel, different radio interfaces designed for used with a single transmission technology. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 2/38

13 Spectrum Sensing The operational band of a cognitive network is composed by several system bands of traditional wireless networks, each band is composed of many channels Spectrum sensing characterizes, in real time, spectrum usage from licensed or high priority networks/users both at channel level and at band level. Its outcomes serve as an input to spectrum decision and sharing modules. Different techniques involving different knowledge of primary technology, known or estimated. If band of interest is too wide, monitoring whole set of channels with a battery powered device could be impossible: solutions for observing different subsets of channels at different nodes could be necessary also related to primary users activity. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 3/38

14 Different approaches: Spectrum Sensing Centralized vs decentralized: with a decentralized approach sensing and sharing are performed at a local level: in principle it is simpler, but not always applicable, e.g. for spectrum decision it is better to collect and process information at a sink node. Cooperative or non-cooperative: Cooperative sensing and decision on channel occupancy yield best performance in terms of accuracy, but y demand for exchange of measured data, or local decision, among nodes, which is band-, and time-consuming, hence it could be impractical if scenario demands for a quick system response. Reactive or proactive: With a cooperative approach, depending on cognitive network traffic load, sensing functions eir can be activated only when a users requests for a transmission, or can be performed independently, in such a way that system gives a quicker respons when a user makes a request to transmit. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 4/38

15 Spectrum decision The entire spectrum where cognitive users operate can be very wide, and involving different system bands with different technologies. Depending on selected scenario, it could be impractical, or even impossible, for a single user to handle spectrum access and mobility over entire available spectrum An external controller could be demanded to choose band for CRs to operate, n inside that band, access and mobility are performed at a local level. This choice is usually performed on basis of long-term statistics, where available capacity is most important, but not only one, aspect to take into account. In particular, or factors, such as QoS requirements of cognitive network, or economical considerations, come into play in this step. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 5/38

16 Spectrum decision with different CR networks If multiple CR networks, with possibly different kind of services, operate in same area and in same spectrum, problem of coexistence among m, and with licensed networks, arises. One way to face this problem is presence of a spectrum broker, i.e., a central network entity that plays a role in sharing spectrum resources among different CR networks. It can be connected to each network and can serve as a spectrum information manager to enable co-existence of multiple CR networks. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 6/38

17 Spectrum sharing Deals with on--fly channel assignment to different CR users. The primary function is to take into account presence of licensed or high priority users operating on same set of channels. A channel for a CR users has not necessarily same badwidth of a channel for primary users Based on sensing results performed at channel level, it identifies an appropriate subset of channels to use. Contention among different CR users can be solved eir in a coordinated manner, or with a random access protocol. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 7/38

18 Spectrum sharing At this level, degree of self-reconfigurability of air interfaces plays a major role. Existing solution in literature provide means for reducing interference caused to primary users, and among CR users, in a completely decentralized way. Decentralized design often use Game Theory as a basic tool. Accurate modeling of licensed users activity is a key point in design of efficient spectrum sharing protocols. Jointly optimized spectrum sensing-sharing are a possible solution when a single node can monitor and/or access only a subset of available channels Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 8/38

19 Spectrum mobility and handoff Spectrum handoff is a multi-step process, including: PU Detection (Sensing issue PU Notification Power Spectrum Handoff Frequency Spectrum holes Channel Switching (Hardware issue Resuming communication (Sharing issue Sensing issue Sharing issue Spectrum occupied by Licensed users Time Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 9/38

20 otivation Decoupling sensing and actuation: otivation Power consumption, observable bandwidth Given a sensing technology, time and power required for sensing a channel, or a set of channels, is proportional to overall channel bandwidth It could be impractical, due to strict time constraints and excessive power consumption, to let a cognitive users sense whole spectrum. On or hand, sensing a larger amount of spectrum clearly allows for a larger number of transmission opportunities, or spectrum holes. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 2/38

21 Decoupling sensing and actuation: otivation otivation Geographic related problems we must make a distinction between two possible scenarios: a The coverage radius of cognitive terminals is comparable with coverage radius of primary users, and service area of primary network. E.g.: an indoor wireless LAN with a single AP cohexisting with bluetooth devices. " With this scenario, hidden terminals and radio footprint are not an issues. Primary Base Station CR User CR User CR User CR User Cognitive Radio (CR Base Station CR User Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 2/38

22 Decoupling sensing and actuation: otivation otivation Geographic related problems we must make a distinction between two possible scenarios: b The service area of primary network is much larger than coverage radii, e.g., a cellular network as a licensed network and a WLAN as a cognitive network. Primary Network Primary Base-Station CR Base-station Dynamic Spectrum Access Primary User CR User Primary User CR User Cognitive Radio Network Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 22/38

23 Decoupling sensing and actuation: how to do it Proposed solution: Given problem of monitoring a large spectrum, and in particular in scenario b, a separate sensor network dedicated to spectrum sensing can be deployed in parallel with primary and cognitive networks. The problems of hidden terminals, especially in case of unknown positioned primary receivers, would be solved, since sensor network could provide information on spectrum occupancy to CR network not only at a given spot, but on entire radio footprint of transmitter, thus allowing for minimal interference with licensed users. Furrmore, sensors would provide a finer spatial resolution on spectrum occupancy, and, most important, can be grid-powered, i.e. with capability to employ more sophisticated sensing algorithms and to monitor larger bands. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 23/38

24 Sensor network for spectrum sensing Furrmore: sensor network can serve different cognitive networks, with different requirements, thus optimizing efforts dedicated to spectrum sensing. It could be part of infrastructure of a spectrum broker Challenges: Sensor network dimensioning Sensor network architecture design Decentralized-vs-centralized Cooperative or non-cooperative algorithms Proactive or reactive Protocol design for inter-sensor communication interface with CR networks Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 24/38

25 Conclusion (Part Cognitive radio can be an effective way to improve efficiency in spectrum usage with respect to nowadays standards. Architecture and protocol stack design are affected at different layer by presence of additional network functionalities to manage dynamic and opportunistic spectrum access and spectrum mobility. There is a variety of possible scenarios, that may lead to a variety of solutions. The presence of a third part entity, called spectrum broker, is an option when considering coexistence of more than one CR network Furrmore, presence of a separate sensor network for spectrum sensing functions Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 25/38

26 Joint AC and Routing Protocol Designs in Cognitive Radio Ad Hoc Networks (CRAHNs Based on Interference aps Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 26/38

27 A Decentralized routing, AC, and scheduling protocol for CRAHNs Problem setup: A CRAHN coexists with a Primary Network which operates on a set of N parallel frequency channels The Pnet gerates random traffic on licensed channels In CRAHN, re is a set of end-to-end multihop flows. Each node can realy traffic for multiple flows, besides those originating at it. Time is organized in periods. In each period, secondary nodes pick one of ir outgoing links a (also specifying a channel and transmit data on that link. Channel access is regulated through a CSA algorithm. The selection is performed relying on a set of link availability parameters that are fed periodically to seconday nodes Flows always have data to transmit aturation regime. Goal: to maximize secondary throughput under constraint that outgoing link selection is performed in a decentralized manner, exchanging only local information. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 27/38

28 A Decentralized routing, AC, and scheduling protocol for CRAHNs We assume that network connectivity graph is given, i.e., we are not pursuing topology optimization, power control issues, etc For simplicity, we assume that each channel has same capacity. The protocol should select channels not in use, or less used, by Pnet. How to do it? Provide a means for each node to obtain channel availability parameters on each outgoing link Seek optimal rule for Snet nodes to decide which link to schedule for transmission, and on which channel, in each period. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 28/38

29 We find it convenient to define a normalized queue length A Decentralized routing, AC, and scheduling protocol for CRAHNs positive system-wide constant. Network Utility aximization Problem (NU B. Secondary Nodes Protocols Stack A utility function is defined which assigns a utility to each value of data rate which network grants to each flow The SNet operates on basis of channel availability inf and on network flow queues. We assume availability o The global utility is sum of utilities for each flow Channel (CCC outside band of cognitive operation, i.e., fr A NU problem represents search of optimal system parameter settings (basically, selection of links on which to transmit to achieve maximum utility for a given set of assumptions. Our proposed protocols can be regarded as a distributed sol ciated to Network Utility aximization (NU problem traffic utility U(x = P f2f U f(x f as objective function. Th well-known backpressure scheduler [7] with a modified ve Where f idicates a flow and x f its rate Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 ay 3, 23 29/38

30 ink (n, m exponential backoff rate link (n, m exponential backoff rate robability of transmitting on link (n, m channel c probability of transmitting on link (n, m network. channel cwe obtain x (j f =[U f (q (j s(ff A Decentralized routing, AC, and scheduling protocol ]x. For instance, c for U(x 9]. Such protocols are described below, f =log(+x whereas CRAHNs ir f, which ensures proportional fairness, we d in [39]. Such protocols are described below, whereas ir formal formal 8 n IV. Protocol description Section IV. x q s(ff apple x >< + tgoing traffic traffic from each fromtraffic each traffic source source node node is constant is constant during during each each At beginning of epoch j, for each flow f, x f = source q s(ff node s(f <q x + s(ff hf epoch j, for j, each for recomputes flow each f, flowf, source outgoing source node node s(f traffic s(f rate recomputes x f as >: maximizer of imizer maximizer of of function function U f (x f U f (xq f s(ff qx s(ff f in in x f ininterval interval [,x [,x ], ], where q q s( f f is s(ff > lized normalized queue length of flow f at its origin. eue length queue length of flowoffflow at its f at source its source node, b node, Scheduling: i.e., it i.e., represents it represents Scheduling is based on well known application layer on node s(f for flow f but not yet injected into ation layer on node s(f for flow[7]: f but scheduling not yet injected decisions into are taken based on flow differ Each node schedules for each of its links (n,m transmission (q (j s(ff ]x f (q (j s(ff. For ]x link instance,. For instance, belonging considering considering to log utility log utility flow function function ore precisely, at with beginning maximal of epoch differential j, each node n 2 ch res ensures proportional proportional backpressure fairness, fairness, weon readily we readily link. obtain: obtain: 8 schedules for transmission flow fnm with maximal differen 8 x x q >< q s(ff apple s(ff apple x +fnm = argmax f2f q (j nf q (j mf. The packets of flow fnm ar x >< + x f = q s(ff q s(ff <q <q x + s(ffduration apple. of epoch (unless(2 queue empties first, in which x + s(ff apple. (2 >: >: q s(ff > q s(ff > j =[U f ay 3, 23 duling is Seminario based presso on il Dipartimento well known di Informatica, backpressure Sapienza Università scheduler di Roma, 23/5/23 paradigm is based on well known backpressure scheduler paradigm are taken based on flow differential queue length across links. 3/38

31 A Decentralized routing, AC, and scheduling protocol for CRAHNs Protocol description continued AC: packets of different links are transmitted by each node through a CSA protocol: channel to use for each packet is selected randomly using a probability vector (p n,m,,,p n,m,n. backoff intervals are inverse of quantities R nm Both (p n,m,,,p n,m,n and R nm are computed for each epoch taking into account differential queue length and channel availability, which is acquired through spectrum monitoring. Finally, an RTS-CTS mechanism is implemented to avoid collisions due to hidden terminal problems or propagation delays. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 3/38

32 A Decentralized routing, AC, and scheduling protocol for CRAHNs Primary protection: it is obtained through CSA mechanism and through selection of less used channels Secondary flows throughput: proposed protocol has been proved to achieve maximum throughput under assumptions of negligible propagation delays and absence of collisions Practical considerations: neverrless, after a careful parameter selection and implementation of RTS-CTS mechanism, it achives very good performance. Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 32/38

33 A Decentralized routing, AC, and scheduling protocol for CRAHNs How to obtain channel availability information for each link: This is achieved through spectrum monitoring, i.e., collection of short-term channel occupancy statistics. Spectrum sensing can be done Locally by Snet nodes Cooperatively by Snet nodes Cooperatively by a dedicated network of nodes which provides and updates an interference map, and feeds it to Snet nodes -> tradeoff between spatial accuracy and time resolution of statistics Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 33/38

34 A Decentralized routing, AC, and scheduling protocol for CRAHNs Simulation environment Built using ns2-iracle framework Includes Pnet (as a cellular network, CRAHN Snet, and a network for spectrum monitoring. Includes both communication and control aspects BS S Sensor SU Cell Cell 2 4 Flow Flow Cell 3 7 Cell Flow 3 Flow 4 Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 34/38

35 A Decentralized routing, AC, and scheduling protocol for CRAHNs Performance evaluation (comparison with a predefined routing scheme with random channel selection Interference caused at primary receivers under different Pnet traffic load (3% and 5% of total capacity, respectively Percentage of total realizations Percentage of total realizations Interference power [dbw] - PU traffic load 5% Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/ Conventional solution Optimal solution Interference power [dbw] - PU traffic load 3% Conventional solution Optimal solution /38

36 A Decentralized routing, AC, and scheduling protocol for CRAHNs Performance evaluation (comparison with a predefined routing scheme with random channel selection Number of corrupted bits (for primary packet of Percentage of total realizations Percentage of total realizations... Number of corrupted bits - PU traffic load 5% Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 36/38 Conventional solution Optimal solution Number of corrupted bits - PU traffic load 3% Conventional solution Optimal solution

37 A Decentralized routing, AC, and scheduling protocol for CRAHNs Performance evaluation: CRAHN flow rates 29 Flow Rates Flow Rates Rate (bytes/s Flow Flow 2 Flow 3 Flow 4 Flow 5 Flow Rate (bytes/s Flow Flow 2 Flow 3 Flow 4 Flow 5 Flow Time Time (a No Pnet traffic (b 5% Pnet traffic Rate (bytes/s Flow Flow 2 Flow Rates Flow 3 Flow Time Flow 5 Flow 6 (c 3% Pnet traffic Seminario Figure 6. presso Flowil Dipartimento Rates. (a Without di Informatica, PNet - (b Sapienza 5% traffic Università load - (c di Roma, 3% traffic 23/5/23 load. 37/38

38 A Decentralized routing, AC, and scheduling protocol for CRAHNs Performance evaluation: impact on Pnet packet error rate PNet Packet Error Rate (%.. PNet + Optimal SNet PNet Alone PNet + Conventional SNet Primary Traffic Load - ean Channel Occupation (% Seminario presso il Dipartimento di Informatica, Sapienza Università di Roma, 23/5/23 38/38

39 Goodput aximization in Opportunistic Spectrum Access Radio Links with Imperfect Spectrum Sensing and FEC-based Packet Protection aurizio A. Bonuccelli! Donatella Ermini Loreto Pescosolido Chiara Petrioli

40 Overview! otivation: AC and Link-level adaptation in opportunistic channel access (OSA networks! Goodput maximization " Perceived PU activity " SU packet transmission rate " SU Packet Error Rate! Results! Conclusion IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 2/8!

41 AC and Link Level adaptation in OSA networks In conventional Wireless Networks: # Channel variations due to fading/mobility # ulti User Interference: may be combated with CA, orthogonal channel access emphasis on maximizing own performance # Service type In OSA networks: # Channel availability due to Primary Users (PU channel use " Need to limit interference towards PU, preserving its performance " PU channel use modeled as a stochastic process with its own characteristics and time scales " SUs rely on spectrum sensing to detect PUs IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 3/8!

42 AC and Link Level adaptation in OSA networks PUs leaves unused resources to SUs in an unpredictable way (at least deterministically SU should use resources in a way that maximizes its throughput while avoidig using same resources as Pus Packet: an atomic unit that can be decoded if and only if received entirely. Overhead + Payload PU! SU! In conventional networks: packet size is limited by coding delay, link stability, and U considerations In OSA: presence of PU has to be taken into account IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 4/8!

43 AC and Link Level adaptation in OSA networks SU packet overhead:. Headers: non-application SDU data (IP addresses, AC, ecc 2. FEC redundancy 3. Spectrum sensing " Items 2 and 3 involve a tradeoff: # Reduction of payload, but # Decrease of packet error probability 2. -> more bit errors are corrected 3. -> less miss detections/false alarms in sensing phase " FEC and PS may require to be jointly optimized for goodput maximization " PU channel use statistics play a role IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 5/8!

44 AC and Link Level adaptation in OSA networks Our assumptions: SU slots: sensig + data transmission If during sensing PU activity is detected, packet trasmission is aborted Slotted channel access even for PU SU packets formed by time-slots IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 6/8!

45 that packet error probability (25 is lower bounded by P e, since it corresponds performance in absence of PU signal in all time-slots. Goodput maximization n or hand, an upper bound on PER can be obtained by bounding probabilit i, i =,...,2, with value, i.e. P e i <. The expression for up GOODPUT = R TX * (-PER * (-OH lower bound R TX : is hence SU packet transmission rate: how often SU manages P e to 6transmit P e (K, in =P consecutive e p + slots X 2 i= P e i p i It depends on perceived PU traffic <P OH: overhead: includes e headers, p + X 2 i= p spectrum sensing i resource reservation, =P FEC redundancy e p +( p. ( PER: Packet error rate. Depends on FEC and on an be seen that posterior upper bound probability depends on that posterior sequence conditional of probability of transmission interval channel was indeed not uence s, which is used given by PU p = p (x = s, y = s, ( p (y = s ere p (y = s is overall probability that a sequence of steps in chain y IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 7/8! responds to consecutive zero states, and p (x = s, y = s is joint probabi

46 Goodput maximization GOODPUT = R TX * (-PER * (-OH Goal: find out best FEC code and packet size in given channel conditions (SNR and PU traffic statistics (with given spectrum sensing performance IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 8/8!

47 Goodput maximization GOODPUT = R TX * (-PER * (-OH " Computation of transmission rate R TX # SUs observe channel through imperfect spectrum sensing PU!traffic! Sensing!performance:! iss!detec?on!prob.!p md! False!alarm!prob.!p fa! Example:!arkov!chain! perceived!pu!traffic! q ij! =!f(p ij,!p fa,!p md! Transi?on!probaili?es!of!!observed!states! Transi?on!probaili?es!of!!actual!states! IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# 9/8!

48 Goodput maximization GOODPUT = R TX * (-PER * (-OH " Computation of transmission rate R TX # How much often does SUs observes a sequence of consecutive idle slots? R Tx = q q ( q ( q q + q # Remember that this result embeds both PU traffic statistics and sensing performance q ij = f(p ij, p fa, p md IEEE#ASS#22,#Las#Vegas,#NV,#USA,#Oct.#882,#22# /8!