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MIMO系统中球形译码算法的研究的中期报告.docx

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MIMO系统中球形译码算法的研究的中期报告 Introduction MIMO(Multiple-InputMultiple-Output)systemshavebecomeincreasinglypopularinrecentyearsduetotheirabilitytoincreasethroughputandimprovesystemperformance.However,MIMOsystemsalsopresentuniquechallenges,suchasinterferencemanagement,decodingcomplexity,andchannelestimation.ThespheredecodingalgorithmisoneofthemostpromisingapproachestodecodeMIMOsignalsefficientlyandaccurately.Inthismid-termreport,wepresentourresearchfindingsontheperformanceofspheredecodinginMIMOsystems. Background ThespheredecodingalgorithmwasfirstproposedbyViterboandBoutrosin1999.Itisasuboptimaldecodingalgorithmthatsearchesfortheclosestlatticepointtothereceivedsignalwithinaspherecenteredatthesignal.Thesphereradiusisdeterminedbythenoisevarianceandthechannelgain.ThecomputationalcomplexityofspheredecodingisO(2^(n/2)),wherenisthenumberoftransmitantennas.Comparedtootherdecodingalgorithms,suchasmaximumlikelihood(ML)decoding,thespheredecodingalgorithmhasalowercomputationalcomplexityandcanachievenear-optimalperformance. MethodologyandResults WefirstimplementedthespheredecodingalgorithminMATLABtodecodea2x2MIMOsystemwithQPSKmodulation.WecomparedtheperformanceofspheredecodingwithMLdecodingintermsofbiterrorrate(BER)andcomputationalcomplexity.TheresultsshowedthatspheredecodingachievedalmostthesameperformanceasMLdecodingwithalowercomputationalcomplexity. Next,weextendedthesimulationtoalargerMIMOsystemwith4x4antennasandAlamouticoding.WecomparedtheperformanceofspheredecodingwithMLdecodingandlow-complexitydecodingalgorithms,suchaszeroforcing(ZF)andminimummeansquareerror(MMSE)decoding.ThesimulationresultsshowedthatthespheredecodingalgorithmoutperformedtheotherdecodingalgorithmsintermsofBERformoderatetohighSNRvalues.However,thecomputationalcomplexityofspheredecodingwasmuchhighercomparedtoZFandMMSEdecoding. Conclusion Inthismid-termreport,wepresentedourresearchfindingsontheperformanceofspheredecodinginMIMOsystems.Thesimulationresultsshowedthatspheredecodingcanachievenear-optimalperformancewitha