cognitive radio making software radios more personal

8/3/2019 Cognitive Radio Making Software Radios More Personal

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AbstractSoftware radios arc cmcrging as platforms for multiband multimode personal communications systems. Radio etiqucttc is the set of R F bands, ai rinterfaces,protocols, and spatial and temporal patterns that modcrate the use of the radio spectrum. Cognitive radio extends the software radiowith rad io-doma in model-based rcasoning about such ctiq uett es. Cognitivc radio enhances th e flexibility of personal services through aRadio Knowlcdge Representation Language. This language reprcsents knowledge of radio e tiquettc, devices, software modules,propagation, nctworks, user needs, and application scenarios in a wa y that supports automated reasoning about thc needs of the user.This empowers software radios to conduct expressivc ncgotiations among peers about the use of radio spectrum across fluents of space,time, an d uscr context. With RKRL, cogn itivc radio agents ma y actively manipulate the protocol stack to adapt known etiquettes to bettersatis$ the LISCTS nccds. This transforms radio nodes from blind executors of predefined protocols to radio-domain-aware intclligentagents that scarch out ways to dclivcr the services thc uscr wants even if that uscr docs not know how to obtain them.

Softwarc radio [ l] rovides a n idcal platform for th c rcalization of cognitive radio.Cognitive Radio:Making Software Radios More PersonalJ O S E P H M I T O L A 11 1 A N D G E R A L DQ. MAGU IRE , J R .

R O Y A L I N S T I T U T E OF T E CHNOL OGY

G l oba l Sys t em f o r Mobi l eCommunications (GSM) radios equalizer taps reflcct the ch an-nel mult ipath structure. A network might want to ask a hand-set, How many distinguishable multipath com ponen ts are youseeing? Knowledge of thc interna l s ta tes of t he equa l i ze rcould be useful bccause in some reception areas, thcrc may belittle or no multipath and 20 dB of extra signal-to-noisc ratio(SNR ). Software radio processing capacity is wasted running acomputationally intcnsive equalizer algorithm when no cqualiz-er is necessary. That processing capacity could be diverted tobetter use, o r part of the processor might be put to sleep, sav-ing battery life. In ad dition, the radio and network could agreeto put data bits in the superfluous embedded training scquence,enhancing the payload d ata rate accordingly.Two problems arise. First, the network has no standard lan-guage with which to posc a question about cqualizer taps. Scc-an d, the handset has the answer in the t ime-domain structureof its equalizer taps, but cannot access this information. It hasno comp utat ional descr ipt ion of i t s own s t ructure . T hus , i tdoes not know what it knows. Standard s-setting bodies havebeen gradually making such interna l data available to networksthrough specific air interfaces, as the needs of the technologydictate. This labor-intensive process takes ycars to accomplish.Radio Knowledge Represcntat ion Language (RKRL), on theother han d, provides a s tand ard languagc wi thin which suchunanticipated data exchanges can be defined dynamically. Whym i g h t t h e n e e d f o r s u c h u n a n t i c ip a t c d e x c h a n g e s a r is e ?Debugging new software radio downloads might requ ire accessto internal sof tware param eters . Crea t ing personal servicesthat diffcrentiate o ne servicc provider from an other might beenhanced if the provider doe s not need to expose new ideas tothe competition in the stan dards-setting process. And the timeto deploy those personalized services could be reduced.Cognitive radio, through RK RL, knows that the natural lan-

This raise.$ a host of questions about the control of such complex adap-tive agents, network ,stabiliQ, and the like.

guage phrase equalizer taps refers to specific parameters of atapped delay-line structure. This structure may be implementedin an application-specific integrated circuit (ASIC), a field pro-grammable gate ar ray (FPGA), or an algori thm in a softwareradio. Since a cognit ive radio has a model of its own internalstructurc, it can check the model to find out how th e equalizerhas been implemented. It then may retrieve thc register valuesfrom the ASIC (e.g., using a JTAG port) or find the taps in theproper memory locat ion of i t s sof tware implem enta t ion. Aradio that knows its own internal structure to this degree doesnot have to wait for a consort ium, forum, or standards bodyt o de f i ne a level H33492.x7 radio as one that can access i tsequal izcr t aps . Th e network can pose such an unant ic ipatedquestion in (a standard) RK RL, and any RKRL-capable radiocan answer i t . To ena ble such a scen ario, cognitive radio hasa n R K R L m o d el of itself that includes the equalizers struc-ture and function, as illustrated in Fig. 1.In this example, the radio hardware consists of the anten na,the radio frequency (RF) conversion module, the modem, andthe other modules shown in the hardware part of the f igure.Th e baseband processor includes a baseband m odem an d aback-end control protocol stack. In addition, this processor con-tains a cogni t ion cngine a nd a se t of com putat ional models.Th e models consi s t of RKR L f rames that descr ibe the radioitself, including the equa lizer, in the contex t of a comprehensiveontology, also written in RKR L. Using this ontology, the radiocan track th e users environment over t ime and space. Cogni-tive radio, then , matches its internal models to cxternal obser-vations to understand what i t means to commute to and fromwork, take a business trip to Europ e, go on vacation, and so on .Clearly, significant memory, computational resources, andcommunications bandwidth are needed for cognitive radio, soth i s technology might no t be deploya ble for som c t ime. Inaddi t ion, a col lcc t ion of cogni t ivc radios may n o t r e q u i r ehuman intervention to develop their own protocols. Init ial ly,intervention will be required in order to ensurd that networksof such radios remain stab le (or that we know who to blame ifth i s i s not the case) . Networks of such radios ar e complex


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___ - ................ .-........... .. Cognition.I-

Software radioSoftware m odules ..... -. . . .-. ..... ..... __ .... .. .. -.__-----_.-___I_................._________.. . . . .

Figure 1 . Cognitiveradio

- Netw ork recognizes incompatible security modes- Network ne gotiates with handset for 1 kB o0 Cl- Prompts for permission to d ownloa d security algorith- Direct-cash availabe at restaura nt around the corner- Handset prompts user to move near the shop doorway- Destructive multipath is now constructive, enhancing 5

* Need real-time language translation

Figure2. More personalized service concepts.adaptive systems [ 2 ] , he s tudy of which is an cmerging disci-pl ine concerned with the nonlincar behavior of large collec-t i ons of adap t i ve en t i t i e s t ha t have com pl ex i n t e r ac t i ons .Although there are many technical challenges, the opportuni-t ies for enhanced personal services mo tivate the developmentof cogni tive radio. This ar t i c le , thcrcfore , out l ines the keytechnical ideas behind cogni t ive radio, RKRL, and re la tedresearch at the Royal Institute of Technology (K TH ), Sweden.

Personalized Services ScenariosThe services enhancements to hc enabled by cognit ive radioare motivatcd by a sct of use cases [3 ] tha t requi re the radioto have an advanced degrec of undcrstanding of topics illus-trated in Fig. 2. Next -genera tion persona l comm unicat ion sscrviccs (PCS ) will know th e location of ha ndsets and wirelesspersonal digital assistants (PDAs) to within 125 m for emer-gency location reporting. Location-aware research [4] is creat-ing technologies for location -aware services, such as f lcxihlcdi rec tory services [SI. Cogni t ive radio adds local ly sensedrecognit ion of common objects, events, and local R F contcxt .Thus, for example, a cognitive radio can infer thc radio-rclat-ed implications of a request for a taxi to a specific address. Itcan then te l l the network i t s p lan to move f rom i t s presentlocation t o Grev Tu rgatan 16. Th e network then knows thatthis uscr (with high probabil i ty) wil l move across three cel lsi tes into a fourth within the next tcn minutcs. If this uscr isheaded for a confcrence center equipped wi th a local ce l l -phone jammer, it is unlikely to offer the usual load to thc net-w o r k a f t c r t h e t a x i r i d e . S u c h e x c h a n g e s c o u l d r e d u c euncer ta inty about th e load of fered to a nctwork, potent ia l ly

enhanc i ng t he e f fi c iency of t h euse of radio resources.Sof t w ar e r ad i os a s p r e s en t l yc o n c e iv e d c a n n o t h a v e s u c h a nintelligent conversation with a net-work because they have no m odel-b a s e d r e a s o n i n g o r p l a n n i n gcapab i l i t y and no l anguage i nwhich to express these things. Forexam pl c , a s o f t w a r e r ad i o f r omt he U n i t ed S t a t e s m ay have t heRF access, memory, an d process-ing resources to op era te in Swe-den . If it lacks compa tibility withrelease lcvcl G of the host serviceprovid er, it will not w ork. A soft-ware radio cannot discuss its internal structure with the net-w or k t o d i s covc r t ha t i t c an he r econf i gu r ed t o accep t adownload of the required software personality. Cognitive radio,

however, employs a rich set of internal models useful for a widerange of such dialogs. In addition, the space-timc m odels of theuser, network, radio resources, and services personalizc andenhanc e th e consumers experience. Th e analysis of such usccases yielded a large set of models, conceptual primitives, andreasoning schema necessary for cognitive radio. Which com put-er languages should be uscd to express thcsc things?Radio-Related Languages

In addi t ion to natural language, several computer-based lan-guages a r e r e l evan t t o t h e expr e s s i on of r ad i o know l edge( T a b l e 1). T h c I n t e r n a t io n a l T e l e c o m m u n i c a t i o n U n i o n( ITU ) , for example , adopted thc Spcci f ica t ion and D escr ip-t ion Language (SDL) in i t s 2.100 R ecom m enda t i ons . SD Lreadi ly expresses radio s ta t e mach ines , message sequen cccharts, and related d ata dict ionaries. Th e Europea n Telecom-munications Standards Inst i tute (ETS I) recently adopted SD Las the normative expression of radio protocols, so onc cxpectsSD L modeling of radio to continue to expand. S DL, however,lacks primitives for gen eral ontological knowledge neede d, forexample, to reason ab out a travel itinerary.Th e Unified M odcling Languagc (UML) resulted from theuni f ica t ion of diverse object -or iented analys i s , modcl ing,design, and dclivcry methods. This language readily expressessoftware objects, including attached procedures (methods), us ecases, and the p ackaging of software for delivery. In principle,i t can he used to model common-sense knowledge, including

14 IEEE Pcrsonal Communications Auguat 1999


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Table 1 . Radio knowledge languages.

T e l e co m m u n i c a ti o n s ( D E C T ) d a t ac h a n n e l o r t h c G S M g e n e r a l p a c k e tradio scrvicc (GP RS ) while in transit.T h e o n t o l o g y p c r fo r m a t i v e c o u l di nvoke an ex i s ti ng on t o l ogy o r cou l dexpress the local context, as in this case.It normally would b c dcfaulted unlcss itchanged. Th e other declarations are selfcvident, which is on e of the strengths ofKQM L. Like IDL, however, KQML isan i n t e r f ace l anguag e . A l t hough , f o rcxample , one can cxpress rules f rom aknowledac base usine KOML. o ne must-t i ans la te these rules in to a convenicntinternal form (c.g., LISP or PR OL OG )in ordei to usc thcm . In addition, thc expressionof gencral ypatial knowlcdge, such as the thre e-dimensional stru cture of a djaccnt city blocks, ISbe t t c r expr e s s ed i n s t r uc t u r ed a r r ays t han i nKQML. KQ ML could be used to send changesversejversion 0.1") :distance 3522 m

omposing-email)))W Figure 3. The K Q M L eupresnon of aplan.plans , space , t ime, re la t ionships , peo ple - jus t abo ut any-thing. In pract ice, i t has a s trong prcscnce in software designand devc lopment , bu t i s weak in thc m odcl ing of hardwarcdev ice s . I n add i t i on , a l though U M L can p r ov i dc ii des ignf ramework for radio propagat ion model ing, the target l an-guagcs a r e l ikel y t o be C o r F O R TR A N f o r com puta t i onalefficiency in tracing tens of thousands of rays of radio waves.T he . C o m m o n O b j e c t R e q u c s t B r o k e r A r c h i t e c t u r c(COR BA) defines an Intcrfacc Defini tion Languagc (IDL) asan implementat ion-independent syntax for describing objectencapsula t ions . In add i t ion to the 700 com pan i e s t ha t com -prise t h e O b j e c t M a n a g e m e n t G r o u p ( O M G ) , I D L i s b e in gused by th e Sof t w are - D ef ined R ad i o ( SD R ) Fo r um [I21 toreprcscnt interfaces among the internal comp oncnts of SD R s .Since this language is specifically dcsigned to dcclare encapsu-lations, it lacks the computational power of gencral languagessuch as C or Java. IDL excels at architecturc integration (e.g.,the interface t o an cqualizer ASIC), but not a t expressing thefunctions and contributions of a component (e.g., the cnhance-ment of bit error rate, BER, at low SNR).Th e hardwarc description languages (HDLs), primarily V er-i log H DL and VH DL , rcadily express the internal structurc ofASICs and the personalities of FPGAs. H owcver,cognit ive radio does n ot ncc d the levcl of detai lp r c s c n t i n m o s t H D L d a t a s e t s . M o r e o v e r , i tneeds to know the funct ions a nd coi i t ribut ions r-

to such arrays, however.Th c know l edge i n te r change f o r m a t ( K I F)provides an axiomat ic f ramework for genera lknowlcdgc including sets, rclat ions, t ime-depcndent quanti-t ies , uni ts , s implc geomet ry, and oth er domain- indcpe ndentconccpts. Its main contribution is strong axiomatization. It hasa LISP-like structure an d, l ike ID L and KQML, is not specifi-cally dcsigned fo r internal use, like C o r Java.F i na ll y , m os t r ad i o know l edge i s r ep r c s cn t ed i n na t u r a llanguage. I t l acks preci s ion, b ut in som e sense has ul t imatcexpressive power, part icularly if on e i nc l udcs g r aph ic s andmultimedia in natural language. Natural languag e suffers fromambiguit ies and complexity that at present l imit i ts use as aformal l anguage. RK RL v. 0.1 was created to fill th e voids inthc expressive power of compu ter languagcs while enforcing amodicum of structure on the usc of natural languagc.

Cognitive Radio as nChess Gam eRKR L is supposed to represent the domain of information scr-vices that use software radios for mobile connectivity. Since asoftware radio has a choice of RF bands, air interfaces, data pro-tocols, and prices to be paid, in com petition with o ther uscrs, the

so that i t can mak e trade-offs, create plans, andreprogram itself. While the documentation pack-age associa ted wi th HD L may providc some ofthis insight, the information is not in a computa-tionally accessible form.T h e K n o w l c dg c Q u e r y a n d M a n i p u la t io nL a n g u a g c ( K Q M L ) , o n t h e o t h e r h a n d , w a sexplici tly de signed to faci l i tate th c exchange ofsuch knowlcdge. Based o n per format i ves such astell and a s k , KQ ML readily expresses the dialogabout equalizer taps and mult ipath by introduc-ing a fcw new t ags . T h e K Q M L p l a n t o t a k c at ax i f r o m t h e i n f o r m a t io n k i o s k t o G r c v T u r -ga t an 16 uses the te l l per format ive to t e l l t hcnetwork of the plan, as shown in Fig. 3. In th i sexample , the radio a l so warns the network thati t s u s e r is com pos i n g s om e e - m a i l and so willn e e d e i t h e r a D i g it a l E u r o p e a n C o r d l e s s

c erwbe

Figure 4. Meao-world wucture of cognitive radio.


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Soutn Am er icaTable 2.An KkXL lume asserting thut the glohul plane corrtuins Suutli Aniwicrr.

.Physical wor ld model/dn,verre,RURL 0 1

-- --/ns / I s- -..____ 1-..< C o n t r o l > < S h i f t > S ,ContainslModels/Universe/RKRL/

_ ~C on ta i nsC on ta i ns Models,Universc/RKRLNersioii 0.1

- - .-. .___ __ ... - -I M o d e l s i Universe/RKRVVe I

domain is analogous to a clicss gamc. The network may orchcs-tratc the gamc, or in some hands (e.g., th c U.S. industrial, scicn-tific, and mcdical band) cognitive radios will simply compctc withcach o ther, hopefully with some radio ctiqucttc. The gamc hoartlis the rad io spec trum with a variety of 111:band s, air intcrfrices,smart an tenn a patterns, tcmpo ral patterns, and spatial locationsof infrastructurc an d mohilcs. RKRL providcs a consistcnt wayof dcscribing this gamc board. The future wireless PDAs arc th cgam e pieccs. Which moves ar c Icg;il? flo w will onc m o w impactothers in thc neighborhood? If a gamc piccc cxprcsses its futureoecds o r plan [or use of scrvices to the network, can th e networkbc t t c r o r chcs t r a t c t he use of radio rcsourccs? Arid to wh atdcgrcc should the way in which spcctrum is uscd over physicalspwx, codc space, power, paraincter space, and time hc dcfincdby the mobile units thcmsclvcs'? N o om knows the answers tothese quest ions because software radios are just cmcrging, butt h e n c c d to addr e s s t hem i n t he l u t u r e s eem s clear. R K K I .cxprcsscs the gamc board a n d the Icgal moves.Davis [13] def ines micro-worlds as per formance domainsfo r naive phys ics . Cogni t ive radio cons i s t s of the mul t iplemicro-worlds (the me.wworld) reprcscnted in Fig. 4.T h e m c s o -w o r ld o f R K K L 0.1 coiisists of t he 41 m i c r o -worlds sunitnarizcd in Fig. 5. F a c h is structured according t oformal models , and descrihed in ii kiiowlcdgc hasc . Coinpc-t cnce comes f r om thc pat tern matching an d plan genera t ioncapahilities 0 1 a cognition cycle, mcdiatccl by the rclatctlinfcrcncc cngincs. RKRL includes syntax and ontological

reasoning as follows. RKRI, is a paral-Icl framc language. hkh RKHL s ta tc-mcnt is a framc: = [ < h a n d l e > , < m o d e l > ,

The iratnc cxprcsscs ii rclat ionshipbctwccn the handlc aiid body, in a givencontcxt. The pa r t def ines theexact rclationship heirig cxpresscd. Man-dlcs should he thought of as iianics fo rthings. If a thing contains othe r things,it can I)c viewed as an object. I1 not, it isa term inal consta nt. l 'ranics ar c iiiter-p r c t c d i n p;irallcl, l i k e th c cc l l s in asprcadshcct. For cxarnplc, the followingRKRL statement says that South Amer-ic a is p a r t o f t h e g l o h a l p l a n c in thephysical world inodcl of thc iiiiivcrsc ofR K R L 0.1. A ddi t i ona l f i - am cs assertE u r o p e a n d the rest i n t o t h e g l o b alplanc. Sii icc the global planc is par t ofthe univcrsc, i t ca n bc thought o f 21s an

< l > ody> , I.

attribute of universe, with a value that is a se t of regions of theworltl. Ilowcver, it can also bc thought of a s j u s t a list o f t h eiianics of coontrics. 'These semantics (ohjcct, list, etc.) arc notp u t o f thc scmant ics of I lKRl ,. I n s t cad , th c s e m a n t i c s areexplicitly tleclarcd and codctl in RK KL using formal computa-tional modcls (l'able 2).Fo r cxaniplc, the word contirins is a vcrh from natural Ian-guagc , uscd in an o bvious way. But contains is also a Cormalmo del dcl' ined i n t h c model's micro-wor ld us ing the s ta tc-mcnts in Table 3.Cont; i ins, the modcl , is defined in terms of a < d o m a i n >(the micro-world of sets), a < r a n g e > , a < tes t> for mcmbcr-ship, and a fo r finding inenibcrs in a local context.The l i n t f r a m c sa ys t h a t C o n t a i n s h a s a < p r o c e s s > callcdSctAccumulatc . The four th line says t ha t Con tains is clcfincdove r se ts (which is a c o m p l e t e m i c ro - w o rl d ). l h c i t em s in arc defined i n thc mct;i micro-world. The process consists o f :I chunk o f Excel Visual Basic for Applica-tions (VBA) macro language that will tcst ii fram c with a stan-d a r d b i nd i ng ( m odc l V ar i s bound to the model pa r t o f t h cf r a m c ) . T h c s c s t r in g models t e l l t h e R K R I , i n t e r p r e t e r(cmhryonic a t prcscnt) tiow to use chunks of codc to constructprograms that crc;itc and nianipiilatc ot?jccls, perform inodcl-IJWXI reasoning, a n d othcrwisc cont rol t l i c sof tware radiopla t form. To attach an existing VU A macro to m entity, o n e

-information. Parsing an KK RI, statciiieiit inclutlcs intcr-preting that statcmcnt in tcrins of the RKR I, radio o n t o l -ogy aiid knowledge base. Thus, words, including KQ MI,tags , have a mca ni i ig that i s f ixcd in a given context(al though a single word ca n liavc diffcrcnt meanings i ndifferent contcxts) . Thus, thc scope of RKRL includesthe formal modcls , knowledge hasc , in lercncc c i iginc,multiple syntaxes, and a radio ontology.The cxpr c s si on of syntax in RK RI , permi t s on e toembcd knowlcdgc from external rcprcsentat ioos (espc-cial ly S D L and U ML) . R K K L m ay now h c dcscr ihcdsyntactically.

R K R LIns tcad of at tcmpt i i ig to replacc SDL, U M L , IDI,, o rK Q M L , l1KRL in tegia tcs them t hr ough model -based

rence,engine, meta, cogni t ion,

niverse. self, concepts, models, time, space, user,Global, Satcom. regional , metro, local, Aprlori : Ik now l edgeFunctions, air , internal , hardware, software,CORBA, UML ODP, MPI.Mo dem , dem odula tor , equal izer.' memory,:Protocol , physical , data l ink, network, segmentation, messages,Prooaaat ion '

H rigure 5. K K R L micro-world,


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s t c ~ t c \line 2, ,iblc 3) t h a t i t \ I , x c c l m o d c l I\ S, th e a\aocl,itccl kcybodi diiiucio In atltlition, one m ay tedclinc contain\ ui\omc o t h c i context . If it I C untlctincd i n locnlc o n t e x t , tlic i n L c i p i c t e i \c,ilcIics t h e m i c i o -woi Id\ a\cciitling tlic context hicrritcliy, and thenl oo k s x i o \ \ m i ci o -w o il d \ unt i l i t citlicr i i ndst \ 'Igoal ot getting 21 tlcfiiiitioii InRKR1 , o Get indudes Lo Cicatc (tllrougli d c r -cncing) 'ind t o Inquire (e .g. , o f tlic i i ~ c i i n e t -

Kn owl~dqc Dou t Zq ualizrrsWOlk)

Ia b l e 4 . T ~ i e p h a i ~ i t a lorld inference hierarchy; I f K SW: knrd/sojtworeFor ii more radio-oriciitctl cxainplc, consider. thca d ip l i vc c(Iu a l i z c r . R K < L k n o w s a hou t t 1 ccqualizcr running on i ts owti platform from thc following coli-t ex t : ~ : , q ~ i ~ i l i z c r /D c i i i o t l u l a to r i M o t l c m i i i i cSc;iIc/I ini i icdiatc/Loc;i l /Mctropoli t~ui/Rcgionallane/ClobalPl;inc/Physical World Model/ Uiiiversc/l


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Model MatchingD et a i l ed m ode l s of r a d i o f u n c t i o n s a r ee m b e d d e d i n R K R L 0.1 f o r each m i c r o -world in which compcten cc has been devel-oped . A s a n exam pl e , Tab l e 5 shows anexecutable model of the segmentation of amessage into packets (from the segmen ta-tion micro-world).If a cognitive radio sets the packet num-

Message

Payload bytesPacket numbe rPayload E ME S

. . . ... . .~ ITable 5. An Excel model of a

cognitive. This go al may be very far off, ormay emerge from th e current research pro-gram. Cognitive radio approaches the soft-w a r e r a d i o as a m i cr o - w or l d , B u t r ad i oenginee ring is such a largc, complex worldthat it will requirc much effort to describc itin com putationally accessible, useful ways.The present research is therefore offcred asa merc baby step in a potcntiallv interestingher to 0, the payload becomes SAM PL, the message beingparsed intopacket research dikction . ~first five octets of the outgoing message. To

tocol, the system first copies the values ofthe model to t emporary RKRL frames , th eparameters to to its protocol (e.g., toa 7-hvte uavload). Finallv. it comn ares the values of the mo dcl

-PaYload~s.

determine thc impact of changing the pro- References[I]. Mitola, Software Radio: Wireless Architecture f orthe 21st Century, [email protected], Mitola's STATISfaction,ISBN 0-9671233-0-5.121 S. Kaufman. A t Home In The Universe, N ew York: Ox ford U niv. Press,1995.

~~ - , - . a I ,lto the previously stored values to detcrmine how th e change ofprotocol will change the payload. It can thus independently rea-son abou t the correctness of a downloaded packetization mod-ule.The Cognition CycZe

RK RL su ppo rts the cognit ion cycle i l lustrated in Fig. 6. T h eoutside world provides st imuli . Cognit ive radio parses thesestimuli to extract the availablc contextual cues necessary forthe pe rform ance of i ts assigned tasks. I t might analyze GPScoordinates plus light and tempe rature to d etermine whether itis inside or outside a building. This type of processing occursin the observe stage of the cognition cycle. Incoming and out-going messages are parsed for content , including the c ontentsupplied toiby the user. This yields contextual cues necessaryto infer the urgency of the communications and related inter-nal tasks. This task is akin to topic spotting in natural languageprocessing. Even relatively high word erro r rates can rcsu lt inh i gh p r obab i l i t y o f de t ec t i o n and l ow f a l s e a l a r m r a t e i ndetecting ordina ry events. Thus , the radio "knows" it is goingfo r a taxi ride (with some probability) if the user packets at th ewireless information kiosk order a taxi. If the main battery hasjust been rem oved, however, thc orient stage immediately actsto save data necessary for a graceful s tar tup and to shu t thesystem down. Loss of carrier on all available links (e.g., du e toentering a building) can result in urgent steps to restore con-nectivity, such as scanning for a n in-building PCS or R F LA N .Most o t he r normal events might n ot requ ire such t ime-sensi-tive responses, resulting in the plan-dccide-act cycle. The actstcp consists of allocating computat ional and radio resourcesto subordin ate (convcnt ional radio) sof tware and ini ti a t ingtasks for specified amo unts of t ime. RKR L also includes somcforms of supervised and unsupelvised learning.Conclusion

Software radios provide a vastuntapped potential to personal-ize services, but the contemporary process of modifying rad ioetiquettes is extremely labor-intensive. In part this is becauset h c r c i s n o g e n e r a l l y a c c e p t c d w ay of r e p r e s e n t i n g r a d i oknowledgc. This limits the flexibility an d responsiveness of ther a d i o t o t h e n e t w o r k a n d u s e r . R K R L m a y p r o v id e s o m e

I31 J. Mit ola . "Cog nitive Radio," Lic entiate proposal, KTH, Stockholm, Sw e-den, Dec. 1998.[41Locat ion-Aware Compurlng and Communicat ions Home Pages, KTH.Sweden. and Wollongong University. Australia: www.elec.uow.edu.aulDeoDle/staff/beadle/badae/location aware.html151h. Henning, "Loca t ionAw are Mo-bile A pplicat ions Based on Directory[61 IT U 2.100 Recs.. "SDe cificat ion and Descripti on Lanauaue," Geneva,Services," Mobicom '97, 1997. - -Switzerland, 1991[7lEriksson and Penker, UML Toolkit, N ew Yor k Wiley. 1998.181 Mo wbr ay and Zehavi. The Essential CORBA, Obj ect Mana gem ent Group,[91Verilog. Object GEODE, Paris, France, 1998.[lo1 . Finin, "KQML - A Language and Protocol for Knowledge and Infor-matio n Exchange," Int'l. Conf. Building and Sharing of Very Large-scaleKno wle dge Bases," Toky o, Japan, Dec. 1993.[l 1 Genesereth and Fikes. "Knowledge Interch ange Format Version 3.0Reference Manual," Logic Group Rep. Logic 92-1, tanford Univ., PaloAlto, CA, 1992.

New York Wiley. 1995.

[121SDR Forum Web Site, www.sdrforum.org 1131 E. Davis, "The Nalve Physics Perplex." A/ Ma g., M enlo Park, CA, Winter 1998.I141 Cohen et al., "Neo: Learning Conceptual Know ledge by SensorimotorInteraction with an Environment," Proc. Autonomous Agents '97. 1997,www.acm.orgBiographies

JOSEPH MITOLA11 ( jmito [email protected]) is a consulting scientist w it h the MITRECorporat ion. He has been a principal architect o f the m igrat io n of b i l l ionsof dollars of legacy telecommunicat ions and information processing sys-tems to commercially based, software-programmable, and highly interoper-able open architecture systems of the future. At present, he is participatingin an executive exchange progra m wi th the U nited States Department o fDefense, where he is a progra m m anger for t he Defense Advance ResearchProjects Agency (DARPA). He is interna tionally recog nized as the "Godfa-ther" of the software radio, having coined the term in 1991 to signal theshif t in radio technology from d igita l radio with "80 percent hardware and20 percent software" t o radios in which 80 percent of the value added of theradio is in the software. In addit ion to having published the f irst paper onsoftware radios in 1992, e writes and teaches extensively on th is technolo-gy. Prior to join ing the MITRE Corporation in 1993, e was the chief scientistof Electronic System. E-Systems Melpar D ivision (no w Raytheon, Falls Church),where he was responsib le f o r research and techno logy deve lopment fo radvanced communicat ions and electronic warfare systems for the UnitedStates De partm ent of Defense. He previously held posit io ns of technicalresponsibility w it h Harris Corporation, Advanced Decision Systems, and ITTCorporation. He began his career as an engineering student assistant withthe United States Department of Defense in 1967.He holds a BSc. degree inelectrical engineering from Northeastern University (highest honors) and aMaster's in degree engineering from Johns Hopkins University. He is presentlya Ph.D. candidate a t KTH, the Royal Technical Institute, Stoc kholm. Swede n.GERALD . [email protected]) is head of the Computer Comm unica-tions Systems Laboratoly of the Royal Technical Institute (KTH). Stockholm, Swe-. _illsights into how to better automate this process, Cognit iveradio, buil t o n RKRL, is envisioned as a competence system

Over domain Of rad io and protocols. I ts agentden, where his research interests include environmentally aware computing(location-aware plus computer awareness of temperature, doors, heating andair conditioning, etc.) and fourth-g enera tion wireless sewices and commun ica-tions svstems. Durina 1991 and 1992. e was Droaram director for e xuerimentalknowledge and inference mechanisms a re under development, systems with the U,?. National Science Foundation. Directorate for 'Computeras is the initial critical mass definition of RKRL.Finally,~m~s designed to be used by software agents thathave such a high level of competence, driven in part by a largeand Information Science and Engineering, Division of Microelectronic Informa-tion Processing systems. From 1984 o 1993 he was an assistant professor atColu mbia Unive rsity. He received a Ph. D., c ompu ter science, fro m the U niversityof Utah in 1983; n M.S. in computer science, University of Utah, 1981; nd astore of a priori knowledge, that they m ay accurately be called B.A.. magna cum laude. physics. Indiana University of Pennsylvania. 1975

18 IEEE Personal Communica t ions * A u g u s t 1999
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cognitive radio making software radios more personal

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