COGNITIVE RADIO ARCHITECTURE STRUCTURES RADIO SKILLS in Java

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8.1.2.3 Verbose, Ef cient, or Optimized Load Modules The AACR functional components could have <Verbose/>, <Ef cient/>, and <Optimized/> forms. The verbose form would be expressed in RXML as de ned in (an evolved version of) CRA <Self/>. The functions might be interpreted rather than compiled for maximum exibility in new situations with a mix of canonical knowledge and autonomous goal-directed experimentation. The ef cient form typically would access bands and modes for the general user in general RF environments from rural vacationing to rush hour in an emergency. The ef cient SDR personality would be balanced with functionality in DSP versus FPGA. The optimized form would be realized in ASICs and FPGAs to optimize power and capability per physical resource (interconnect bandwidth and MIPs). Optimized radio-domain capabilities may be described by a <Verbose/> version for exible reasoning about the SDR waveform. This same strategy of verbose, ef cient, and optimized implementations applies to the user sensory-perception component because of the computational burden of 3D visual perception. 8.1.3 Radio Skills and the Cognition Cycle
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The top level relationships among the functional components, ISAPIs and CogAPIs, the Cognition cycle, and radio skills is summarized in Expression 8-2. Expression 8-2 Radio Skills and the Cognition Cycle <Cognition-cycle> <Observe> <Sense> <User/> <RF> <SDR> <Band/> <Mode/> <Environment/> </SDR> <Known/> <Novel/> </RF> </Sense> <Perceive> <User/> <RF> <Connectivity> <GoS/> <QoS/> </Connectivity> <Backup/> </RF> <Scene/> </Perceive> </Observe> <Orient> <Self/> <User/> <Scene/> <SDR-waveform> <State/> </SDR-waveform > </Orient> <Plan> <Information-services/> <Game-theory/> <RF> <Radio-skills> <Physical-access> <Bands> <HF/> <LVHF/> <VHF/> <UHF/> <SHF/> <EHF/> <THz> </Bands> <Modes> <SDR-subsystem> <RF-sensing> <Signals/> <Noise/> </RF-sensing> <SDR-waveforms/> </Modes> </SDR-subsystem> </Physical-access> <Knowledge> <Physical> <Frequency/> <Wavelength/> <Bandwidth/> <Canonical/> <Self> <Transmitter> <Receiver> <Antenna/> <RF-conversion/> <Baseband/>
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<Bitstream/> <Security/> <Sources/> <Sinks/> </Transmitter> </Receiver> <Channel/> <Path/> <Re ection/> <Refraction/> <Doppler/> <Propagation> <Link-budget/> <2D/> <3D/> <Propagation> <Signal-in-space> <Channel-symbol/> <Multiple-access/> <Stream/> </Signal-in-space> </Physical> <Logical> <Connectivity> <Grade-of-service/> <Quality-of-service/> </Connectivity> <Protocol-stack/> </Logical> </Self> </Knowledge> </Radio-skills> <Collaborate/> </RF> </Plan> <Decide> <User-criteria/> <Regulatory-criteria/> <Resources/> </Decide> <Act> <Radio-skills> <Skill> <Connect> <Transmit/> <Receive/> </Connect> <Transfer-data/> <Disconnect/> <Bridge/> <Skill/> </Radio-skills> </Act> <Effectors/> <Learn> <RF/> <User/> </Learn> </Cognition-cycle> RF support functions of the Observe phase include sensing the radio s band(s), mode(s), and environment (e.g., for available backup channels) through the SDR functional component, supported by the CogAPI. The RF perception function of the Observe phase interprets GoS and QoS data from the SDR component, also identifying the available backup bands and modes to enhance QoI. XG stresses RF environment sensing via the RockwellCollins MBMMR XG sensors [194]. As ad hoc networks proliferate, the importance of RF sensing increases. In the Orient phase immediate RF action mitigates catastrophic <State/> change in a current wireless connection. The Observe and Orient phases structure the behavior of current SDR systems, expanding RF sensing, but not fundamentally changing the nature of the radio. The Plan phase, however, implements a quantum leap in behavior since the <Self/> knowledge about <User/> QoI and the <RF/> <Scene/> drive <Goals/> in this phase. Today s radios don t plan. They do what they are told by the user and the host network. AACRs plan. They sense available spectrum, identify QoI enhancement opportunity, allocate resources, and enhance QoI <Goals/> within <User/> and <RF/> constraints. Instead of merely initiating a SDR personality with a xed set of parameters, the AACR s radio skills are more re ned, connecting to evaluate an available mode, but not necessarily using the mode. When transferring data, the AACR may adapt content to the changing RF environment, increasing error protection as fading parameters change. In addition
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to losing network connectivity, the AACR politely defers access to primary users when sharing spectrum. Bridging bands and modes yields uninterrupted conversation as the iCR switches from cellular to VoIP on the corporate wireless LAN. Collaboration among peer AACRs includes goal-oriented planning. Thus, the implementation of radio skills focuses mostly on the use of embedded knowledge via the Plan phase. The comprehensive scope of planning is re ected in the RXML of Expression 8-2. 8.1.4 Radio Skills Implementation Strategy
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The strategy of radio skill implementation applies Occam s Razor to technology insertion. The simplest technology that accomplishes the use case is preferred. Thus, the chapter begins with the simplest methods of storing and applying radio knowledge and progresses to the more complex but more capable methods. The place to start embedding knowledge into AACR is the traditional database. Next are the rule bases and knowledge bases from eBusiness products, many of which have been assimilated into conventional database packages, like Oracle (e.g., 9i eBusiness rules are well beyond mySQL). In addition, conventional (nonintelligent) radio propagation modeling tools supply radio knowledge, particularly if calibrated to the <RF/> environment by the AACR or CWN. The format of radio knowledge differs with band, mode, and time through AACR evolution. The major conventional knowledge representations are databases, rule bases (including logic programming), object-oriented knowledge bases, agent systems, and domain-speci c computational models. Each of these is a candidate for radio skill to observe, orient, plan, decide, act, and learn. The inadequacies of the simpler approaches lead one to formal computational ontologies and the Semantic Web. In one approach, spectrum management is a multiplayer game [195] with heterogeneous knowledge representation. Microworlds organize scene-level knowledge and partition skills within speci c task domains that are formally modeled, supported by axioms, a knowledge base, a rule base, and a domain-speci c language [219]. <RF/> microworlds constrain AACR inferences to context for ef cient, focused problem solving. Finally, even these approaches do not fully support AML for iCR, which led to the specialized Radio Knowledge Representation Language (RKRL) [145], an extensible domain-speci c language that is intentionally not Turingcomputable and thus achieves nite introspection. This book realizes RKRL principles in RXML.
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