ŗ ʼnʭőʭÝ ŐŞ˙Ĕă ŏŘŞğťŗĖŎ ĦŞĔĤă ʼnʭŒâŞğ ęĕ ãʭŕ ˮĕùŘőʭē ěù

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ŗ ʼnʭőʭÝ ŐŞ˙Ĕă ŏŘŞğťŗĖŎ ĦŞĔĤă ʼnʭŒâŞğ ęĕ ãʭŕ ˮĕùŘőʭē ěù
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
ãʭŕʼnʭŒâŞğ ęĕ ŏŘŞğťŗĖŎ ĦŞĔĤă ŗ ʼnʭőʭÝ ŐŞ˙Ĕă
ęĕ ťʭý ŔþăĚŎ ŏʭáęʭŎí ěù ˮĕʭŀĄğù ʭý MQAM ˮĕùŘőʭē
ˮĚŞĠŎĖŒ× àŒŰĖŞĿ äăùĚýʭĔŎ ãʭŕʼnʭőʭÝ
äÝĜŞý äńŊʭē ŐŞĠď ʯ ęŘÐőʭýĚŃ ùĚŕě
ÜŞőŗĚĄÞŊùŗ ŁĚý ˫ĖÞĤőùĕ -ĚĄģù ÜŊʭŎ äĄĸŒħ ˫ʭâĤőùĕ
(z_ghorbanpour, bizaki) @yahoo.com
ŔÞŒŰù Ŕý ŔċŘă ʭý ĂŕʭþģĚý äŒĄþŎ ġŗę ęĕ .( FBˀ)äáĜŰŗ ûʭĔĄőù Ěý äŒĄþŎ
ĦŞĔĤă ŔŊʭĠŎ ʯĖģʭþŞŎ ŔĄēʭŒģʭő ãʭŕĚĄŎùęʭÏ ˛Ŏʭģ äĄĿʭŰęĕ ʼnʭŒâŞğ
ŏí ˛ď ˫ùę ŔÝ ĕĕĚáäŎ ˛ŰĖþă üÝĚŎ ĩĚĿ ŏŘŎěí ŔŊʭĠŎ ÜŰ Ŕý ŏŘŞğťŗĖŎ
ęŘį Ŕý .ĕŘģäŎ ĮþăĚŎ ʼnʭŒâŞğ ŌŘŋĸŎʭő ãʭŕĚĄŎùęʭÏ ŏĕŘ˙ő ʼnĖŎ ˫ŘĐő Ŕý
ŏùŘăäŎ üÝĚŎ ĩĚĿ ŏŘŎěí ŔŊʭĠŎ ˛ď ĂŖċ ˫Ė˙ķ ÜŞŒÞă Ŕğ äŋÝ
(ALRTˁ) ãʭ˙ŒĄğęĕ ĂþĠő ŐŞâőʭŞŎ ŏŘŎěí ʯ ʼnŗù ŏŘŎěí .[ʴ]ĕŘ˙ő äĿĚĸŎ
ãʭŕĚŞļĄŎ ŏùŘŒķ Ŕý ʼnʭŒâŞğ ŗ ʼnʭőʭÝ ŔĄēʭŒģʭő ãʭŕĚĄŎùęʭÏ ŏí ęĕ ŔÝ . Ăğù
Ŕý Ăŕʭþģ Ķýʭă ŗ ĖőŘģäŎ ĩĚĿ ŌŘŋĸŎ ʼnʭ˙Ąďù äŊʭâ× Ķýʭă ʭý äĿĕʭĨă
-äŎ ŔþğʭĐŎ ʼnʭ˙Ąďù äŊʭâ× ĶýùŘă ŐŰù ãŗę Ěý ãĚŞáĮğŘĄŎ ŔŋŞğŗ
ʯĂğù (GLRT˂) äŰʭ˙ŒĄğęĕ ĂþĠő ŔĄĿʭŰ ōŞ˙ĸă ŏŘŎěíʯ Ōŗĕ ÜŞŒÞă.ĕĕĚá
ʼnŘŖČŎ ʭŎù Ăýʭć ŗ äŒŞńŰ ãʭŕĚŞļĄŎ ŏùŘŒķ Ŕý ŔĄēʭŒģʭő ãʭŕĚĄŎùęʭÏ ŏí ęĕ ŔÝ
-ŏí Ŕý ĂþĠő ãěʭğĚĈÝùĖď ŔŋŞğŗ Ŕý Ăŕʭþģ Ķýʭă ŗ ĖőŘģäŎ ŔĄĿĚá ĚĴő ęĕ
ĮŋĄĔŎ äŰʭ˙ŒĄğęĕ ĂþĠő ŏŘŎěí ʯŌŘğ ÜŞŒÞă .ĕŘĤŞŎ ŔþğʭĐŎ ʭŕ
äŋÝ ęŘį Ŕý .ĖģʭýäŎ Ōŗĕ ŗ ʼnŗù ÜŞŒÞă ŗĕ ěù äþŞÝĚă ŔÝ Ăğù (HLRT˃)
ŏĕŘ˙ő ō˙ŞŒŞŎ äŰʭőùŘă ĖŰʭģ Ăŕʭþģ Ěý äŒĄþŎ ãʭŕġŗę Ăŀá ŏùŘăäŎ
ęʭŞĠý äáĖŞØŞÏ ãùęùĕ äĿĚįěù äŊŗ ĖŒģʭý ùęùĕ ùę ĦŞĔĤă ãʭİē ʼnʭ˙Ąďù
.ĖŰʭ˙őäŎ ęùŘģĕ ùę ʭŕŏí ěù ˫ĕʭŀĄğù ŔÝ ĖŒĄĠŕ
ęʭÝĕŘē ĦŞĔĤă ŔŊʭĠŎ ˛ď ãùĚý äķŘŒĄŎ ãʭŕōĄŰ ęŘâŊù ŏŘŒÝʭă
.Ăğù ˫ĖŰĕĚá Ŕ÷ùęù MQAM ˫ĕùŘőʭē ãʭŕʼnʭŒâŞğ ęĕ ŏŘŞğťŗĖŎ
àŒŰĖŞĿ ʼnʭőʭÝ ʭŰ ŗ AWGN ãʭŕ ʼnʭőʭÝ ãùĚý ʭŕōĄŰęŘâŊù ŐŰù ĚĈÝù
ĂŃĕ ěù ˫ĚŞĠŎĖŒ× àŒŰĖŞĿ ʼnʭőʭÝ ęĕ ŗ Ėőù˫Ėģ äďùĚį ˫ĚŞĠŎ Üă
ŏŗĖý ŔÝ ˫Ėģ Ŕ÷ùęù ä˙ĄŰęŘâŊù ŔŊʭńŎ ŐŰù ęĕ .ĖŒĄĠŞő ęùĕęŘēĚý äþğʭŒŎ
ʭý ùę ˫ĚŞĠŎ ĖŒ× àŒŰĖŞĿ ʼnʭőʭÝ üŰùĚī ʯʼnʭőʭÝ ěù äăʭķŦįù ŐĄģùĕ
ŏí ěù ĞÏ ŗ ĖőěäŎ ŐŞ˙Ĕă ŌęʭŖ× ŔþăĚŎ ŏʭ˙Ŏ Ü˙Ý Ŕý ŗ ťʭý ĂŃĕ
ŌęʭŖ× ŔþăĚŎ ĂŒŊŘŎŘÝ Ü˙Ý Ŕý ùę äĄĿʭŰ ęĕ ʼnʭŒâŞğ ŏŘŞğťŗĖŎ ĵŘő
ŐŰù ĮğŘă ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă Ėħ ęĕ .ĖŰʭ˙ŒŞŎ ĦĔĤŎ
āʭķŦįù ŔÝ Ăğù äİŰùĚģ ęĕ ĂŞńĿŘŎ Ėħ ęĕ ʭý ĚýùĚý ōĄŰ ęŘâŊù
ãťʭý ĂŃĕ ĚâőʭŞý ĕŘē ŐŰù ŗ Ėģʭý ĕŘċŘŎ ʼnʭőʭÝ üŰùĚī ěù äŋŎʭÝ
.Ăğù ʼnʭőʭÝ üŰùĚī ŐŞ˙Ĕă ęĕ ãĕʭŖŒĤŞÏ ōĄŰ ęŘâŊù
ĖŒ× àŒŰĖŞĿ ʼnʭőʭÝʯŏŘŞğťŗĖŎ ĦŞĔĤă µ ãĖŞŋÝ āʭ˙ŋÝ
ĂŒŊŘŎŘÝʯ˫ĚŞĠŎ
ŔŎĖńŎ -ʴ
ęĕ äőùŗùĚĿ ãʭŕĕĚýęʭÝ ãùęùĕ (AMCʾ) ŏŘŞğťŗĖŎ ęʭÝĕŘē ĦŞĔĤă
ľŞį ĂŰĚŰĖŎ ŗ ęùĜĿùŌĚőŘŰĕùę ĖŒőʭŎ ãęʭČăĚŞĻ ŗ ãęʭČă ãʭŕ ŔħĚķ
Ŕý ŏŘŞğťŗĖŎ ĦŞĔĤă ōĄĠŞğ ÜŰ .Ăğù ÜŞőŗĚĄÞŊù àŒċ ŗ äĠőʭÝĚĿ
ʼnʭŒâŞğ ġěùĕĚÏĢŞÏ ŔŋďĚŎ -ʴ :Ăğù˫Ėģ ˛ŞÞĤă ŔŋďĚŎ ŗĕ ěù äŋÝ ęŘį
ęĕ .ŏŘŞğťŗĖŎ ĵŘő ĦŞĔĤă ōĄŰęŘâŊù ãěʭğ˫ĕʭŞÏ ŔŋďĚŎ -ʵ äĄĿʭŰęĕ
ěʭŞő ãĚĄ˙Ý ġěùĕĚÏĢŞÏ ŔÝ ä˙ĄŰęŘâŊù ʯęʭÝĕŘē ĦŞĔĤă ōĄĠŞğ ÜŰ
.Ăğù ęùĕęŘēĚý ãĚăťʭý ġěęù ěù Ėģʭý ŔĄģùĕ
Ăğù äáÚŰŗ Ěý äŒĄþŎ ĕĚÞŰŗę ʯ ŏŘŞğťŗĖŎ ĦŞĔĤă ęĕ Ōŗĕ ĕĚÞŰŗę
ęĕ .Ăğù ˫Ėģ ˛ŞÞĤă ŘâŊù ĦŞĔĤă ŗ äáÚŰŗ ĉùĚĔĄğù ŔŋďĚŎ ŗĕ ěù ŔÝ
ŏŘŞğťŗĖŎ ĵŘő ˫Ėģ ġěùĕĚÏ ãʭŕäáÚŰŗ ěù ˫ĕʭŀĄğù ʭý ĕĚÞŰŗę ŐŰù
Ěý äŒĄþŎ ġŗę ʭý ŔĠŰʭńŎ ęĕ äáÚŰŗ Ěý äŒĄþŎ ġŗę .ĕĕĚáäŎ ĦĔĤŎ
ãʭŕäáÚŰŗ ûʭĔĄőù ŗ äďùĚį āęŘħ ęĕ äŊŗ ĂĠŞő ŔŒŞŖý Ăŕʭþģ
ŗĕ Ŕý ŏùŘăäŎ ùę ŏŘŞğťŗĖŎ ęʭÝĕŘē ĦŞĔĤă ãʭŕġŗę ˛Ý ęĕ
ĕĚÞŰŗę -ʵ (LBʿ)Ăŕʭþģ Ěý äŒĄþŎ ĕĚÞŰŗę -ʴ :ĕŘ˙ő ōŞĠńă ĕĚÞŰŗę
ʶ
Feature Base
ʷ
Average Likelihood ratio Test
ʸ
Generalized Likelihood Ratio Test
ʴ
Automatic Modulation classification
Hybrid Likelihood Ratio Test
ʵ
Likelihood Base
ʹ
۷۵۰
‫ اﻧﺠﻤﻦ ﻋﻠﻮم ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬،۱۳۹۴©
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
ʭý ŗ ĦĔĤŎʭő ãÙĚőù ʭý äŊʭğęù ãʭŕʼnŘþ˙ğ ʭý ĚýùĚý x(n) ŏí ęĕ ŔÝ
ʯĖŒģʭþŞŎ ĚâŰĖÞŰ ěù ˛ńĄĠŎ ŗ ŏʭĠÞŰ ĵŘŃŗ ʼnʭ˙Ąďù
ŗ Ăğù L ʼnŘį Ŕý ʼnʭőʭÝ üŰùĚīʭý ĚýùĚý h ( n ) , n 0,1,..., L 1
ŗ Ěŀħ ŐŞâőʭŞŎ ʭý (AWGN) ˫ĖőŘģĶ˙ċ ĖŞŀğ äğŘá ĜŰŘő g ( n )
ãĚĄ˙Ý äáĖŞØŞÏ ěù äĿĚį ěù ŗ Ăğù ŔŒŞŖý Ŕý ÜŰĕĜő äŰùęʭÝ ãùęùĕ üğʭŒŎ
ŔþăĚŎ ŏʭáęʭŎí äăùĚýʭĔŎ ãʭŕʼnʭŒâŞğ äŰʭŕäáÚŰŗ ŏʭŞŎ ęĕ.Ăğù ęùĕęŘēĚý
.ĖŒĄĠŕ äőùŗùĚĿ ĕĚýęʭÝ ãùęùĕ ŗ ˫ĕŘý ęùĕęŘēĚý ãù˫ÚŰŗ ĂŞ˙ŕù ěù ťʭý
ěù ˫ĕʭŀĄğù ʭý ŏŘŞğťŗĖŎ ĦŞĔĤă ŔŒŞŎě ęĕ ãù˫ĕĚĄĠá ãʭ೪ńĐă ŏŘŒÝʭă
Ŕý ŗ ŌęʭŖ× ŔþăĚŎ ĂŒŊŘŎŘÝ ěù ˫ĕʭŀĄğù ʭý [ʵ] ęĕ .Ăğù ˫ĖŰĕĚá Ŕ÷ùęù ŏʭáęʭŎí
ŏŘŞğťŗĖŎ ĦŞĔĤă ŔŊʭĠŎ ˛ď Ŕý AWGN˄ ĮŞĐŎ ęĕ äþŞăĚă āęŘħ
ĚýùĚý ęĕ ŏĕŘý ŌŗʭńŎ ˛ŞŊĕ Ŕý äĤēĚ× ãʭŕĂŒŊŘŎŘÝ .Ăğù ˫Ėģ ŔĄēùĕĚÏ
˫ĕʭŀĄğù ʭý ĢőùęʭÞ˙ŕ ŗ ĚőŘÐğù ʯ ĖŒĄĠŕ äŰťʭý ĂŞ˙ŕù ãùęùĕ äőʭŎě ĚŞēʭă
ĵŘő ĦŞĔĤă Ŕý AWGN ĮŞĐŎ ęĕ ōĤģ ŔþăĚŎ äĤēĚ× ĂŒŊŘŎŘÝ ěù
˛ď ãùĚý äķŘŒĄŎ ãʭŕōĄŰęŘâŊù ˫Ěýŗĕ ōőʭē .[ʶ]ĖŒĄēùĕĚÏ ŏŘŞğťŗĖŎ
˫ĕŘ˙ő Ŕ÷ùęù ĂĔă àŒŰĖŞĿ ŗ AWGN ʼnʭőʭÝ ęĕ ŏŘŞğťŗĖŎ ĦŞĔĤă ŔŊʭĠŎ
ãʭŕĂŒŊŘŎŘÝ ˛Ŏʭģ ŔÝ äáÚŰŗ ęùĕĚý ěù ˫ĕʭŀĄğù ʭý ŗù. ʯ[ʹ-ʷ]Ăğù
-ʼnʭŒâŞğ ŏŘŞğťŗĖŎ ĵŘő ĦŞĔĤă Ŕý ŌùĖŃù ĖģʭýäŎ ĂĤŕ ŔþăĚŎ äĤēĚ×
äğęĚý ĂĐă ʼnʭőʭÝ āťʭńŎ ŐŰù Ŕ˙ŕ ęĕ äŊŗ.[ʺ]ĕŘ˙ő QAM ˫ĕùŘőʭē ãʭŕ
ęĕ ŔÝ Ėģ Ŕ÷ùęù ä˙ĄŰęŘâŊù [ʻ] ęĕ ęʭý ŐŞŊŗù ãùĚý ʯĕŘý ˫ĚŞĠŎ Üă ʼnʭőʭÝ ÜŰ
ěù äĤőùĕ ŐĄģùĕ ŏŗĖý ŗ ęŘÝ āęŘħ Ŕý ŌęʭŖ× ŔþăĚŎ ŏʭ˙Ŏ ěù ˫ĕʭŀĄğù ʭý ŏí
ěù ˫ĕʭŀĄğù ʭý ŏí ěù ĞÏ ŗ Ėģ ˫ĕě ŐŞ˙Ĕă ʼnʭőʭÝ ˫ĜŞŊʭŎĚő üŰùĚī ʼnʭőʭÝ
-ʼ]ęĕ ŏí ěù ĞÏ .ĖŰĕĚá ĦĔĤŎ ŏŘŞğťŗĖŎ ĵŘő ŌęʭŖ× ŔþăĚŎ ĂŒŊŘŎŘÝ
ęʭÝĕŘē ĦŞĔĤă ěù ˛ħʭď ĊŰʭĄő ōĤģ ŔþăĚŎ ĂŒŊŘŎŘÝ ěù ˫ĕʭŀĄğù ʭý [ʴʴ
ŗ čŦħù ʭý ŔŊʭńŎ ŐŰù ęĕ .Ėģ ˫ĕùĕ ʭńăęù ˫ĚŞĠŎĖŒ× ʼnʭőʭÝ ęĕ ŏŘŞğťŗĖŎ
Ěăťʭý ĂŃĕ ʭý ʼnʭőʭÝ ˫ĜŞŊʭŎĚő üŰùĚī ʯ[ʻ] ęĕ ˫Ėģ Ŕ÷ùęù ōĄŰęŘâŊù ʭńăęù
ĵŘő ʯęʭŖ× ŔþăĚŎ ĂŒŊŘŎŘÝ ěù ˫ĕʭŀĄğù ʭý ŏí ěù ĞÏ ŗ Ėģ ĖŕùŘē ˫ĕě ŐŞ˙Ĕă
ĚâőʭŞý ĕŘē ʯãěʭğŔŞþģ ěù ˛ħʭď ĊŰʭĄő .ĕĕĚáäŎ ĦĔĤŎ ŏŘŞğťŗĖŎ
ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù ĮğŘă ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă Ėħ ęĕ ĕŘþŖý
.ĖŒģʭýäŎ
ŔþăĚŎ ĂŒŊŘŎŘÝ ěù ˫ĕʭŀĄğù ʭý ŔŊʭńŎ ŐŰù ęĕ .ĖģʭýäŎ G g2 ĞőʭŰęùŗ
àŒŰĖŞĿ ʼnʭőʭÝ ÜŰ ěù äĄĿʭŰęĕ ʼnʭŒâŞğ ŏŘŞğťŗĖŎ ĵŘő (C42 )ęʭŖ×
.ĕŘĤŞŎ ĦĔĤŎ ʯ ˫ĚŞĠŎĖŒ×
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Cum[( x(n)) q ( x(n)) n q ]
Cx,n ,q
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ěù ĉùĚĔĄğù ˛ýʭŃ ŗ ŐÞ˙Ŏ ãʭŕãĖŒýŔĄğĕ Ōʭ˙ă ĚâőʭŞý „z ŏí ęĕ ŔÝ
˛ńĄĠŎ ŗ äŖă ĚŞĻ ʭŕãĖŒýŔĄğĕ ŐŰù ʯ Ăğù „ {1,..., n} ŔķŘ˙ČŎ
ĚâőʭŞý Z .ĕŘģäŎ „ŔķŘ˙ČŎ ʭý ĚýùĚý ʭŕŏí ĵŘ˙ČŎ ŗ ˫ĕŘý ĚâŰĖÞŰ ěù
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ĉŗĕĜŎ ãʭĬķù ĕùĖĸă ĚâőʭŰʭ˙ő qz ŗ ŔķŘ˙ČŎĚŰě Ěŕ ãʭĬķù ĕùĖĸă ʭý
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ŔÞŰęŘį Ŕý .ĖŒģʭýäŎ ŔķŘ˙ČŎĚŰě Ěŕ ˫Ėģ
n
z
Ōù n ŔþăĚŎ ŏʭ˙Ŏ ĚâőʭŞý mx , nz ,qz ŔŊĕʭĸŎ ŐŰù ęĕ .Ăğù ¦ qz q
ŐŞ˙Ĕă (ʶ) ʼnŘŎĚĿ ěù ˫ĕʭŀĄğù ʭý ùę ŏí ŏùŘĄŞŎ ŔÝ .Ăğù q ĊŰŗĜă ęùĖńŎ ʭý
:ĕě
mx , n z , q z
E[( x(n)) qz ( x( n)) nz qz ]
(ʵ)
M
M 1 ¦ ( x(n)) qz ( x( n)) nz qz
˫ĚŞĠŎĖŒ× ʼnʭőʭÝ ÜŰ ěù äĄĿʭŰęĕ ʼnʭŒâŞğ ʼnĖŎ Ōŗĕ Ă˙ĠŃ ęĕ ŔŎùĕù ęĕ
ŌŘğ Ă˙ĠŃ ęĕ .Ăğù ˫ĖŰĕĚá ŏʭŞý ŏí ěù ĂŒŊŘŎŘÝ äáÚŰŗ ĉùĚĔĄğù ěĚį ŗ
˫Ėģ ˫ĜŰʭŎĚő üŰùĚī ŐŞ˙Ĕă ãùĚý łŞŃĕ äģŗę [ʻ] ōĄŰęŘâŊù čŦħù ʭý
ęùĚŃ äğęĚý ĕęŘŎ ãěʭğŔŞþģ ĊŰʭĄő ŌęʭŖ× Ă˙ĠŃ ęĕ ŗ ʯĕŘģäŎ Ŕ÷ùęù ʼnʭőʭÝ
.ĂĿĚá ĖŕùŘē
m 1
˛Ý ĕùĖĸă ʭý ĚýùĚý M ŗ äīʭŰę ĖŞŎù Ěâŋ˙ķ ãʭŒĸŎ Ŕý E ŏí ęĕ ŔÝ
.Ăğù Ōù i ŏŘŞğťŗĖŎ ěù äŊʭğęù ãʭŕʼnŘþ˙ğ
ęùĖńŎ ŗ ˫ĕŘ˙ő ĉùĚĔĄğù ùę C42 ʼnŘŎĚĿ (ʶ) ŗ (ʵ) ʼnŘŎĚĿ ěù ˫ĕʭŀĄğù ʭý
:ōŞŰʭ˙őäŎ ŔþğʭĐŎ ĚŰě āęŘħ Ŕý ùę ŏí ˫Ėģ ˫ĜŞŊʭŎĚő
C 42, x
C42, x
C21, x
äáÚŰŗ ĉùĚĔĄğù ŗ ʼnʭŒâŞğ āʭŞħŘĨē -ʵ
(ʶ)
ŔŊĕʭĸŎ āęŘħ Ŕý ŏùŘăäŎ ùę äĄĿʭŰęĕ ʼnʭŒâŞğ ˫ĚŞĠŎĖŒ× ʼnʭőʭÝ ÜŰ ęĕ
:ĕŘ˙ő ʼnĖŎ (ʴ)
˫ĜŞŊʭŎĚő ĚŰĕʭńŎ .ĖŕĕäŎ ŏʭĤő ùę ʼnʭŒâŞğ ãÙĚőù ęùĖńŎ C21 ŏí ęĕ ŔÝ
ęĕ 64QAM ŗ16QAM ŗ 4QAM ãʭŕ ŏŘŞğťŗĖŎ ãùĚý ʷ ĂŒŊŘŎŘÝ ˫Ėģ
.Ăğù ˫Ėģ ˫ĕùĕ ŏʭĤő ÜŰ ʼnŗĖċ
l 1
y (n)
¦ h( k ) x ( n k ) g ( n)
k 0
ʺ
۷۵۱
Additive White Gaussian Noise
(ʴ)
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
h (k )
ʻŗʷ ŔþăĚŎ ãʭŕĂŒŊŘŎŘÝ ˫Ėģ ˫ĜŞŊʭŎĚő ĚŰĕʭńŎ
h( k )
h(0)
h(0)h( L 1)h( L 1)h(k ) E ( x4 ) Residual
(ʻ)
Constellation
C 42
(h(0)h( L 1))2 E ( x 4 ) Residual
Ŕý ŔċŘă ʭý ĉĚĔŎ ŗ āęŘħ ęĕ ĕŘċŘŎ (Residual)ƚ ˫Ėőʭ˙ŞŃʭý ĚŰĕʭńŎ ŔÝ
ʼnʭ˙Ąďù ŗ ˫ĕŘý ĚâŰĖÞŰ ěù ˛ńĄĠŎ äĄĿʭŰęĕ ʼnʭŒâŞğ ãʭŕʼnŘþ˙ğ ŔÝ ŔÞŒŰù
ÜŰ ęĕ ĶŃùŗ ęĕ.ĖŒģʭýäŎ Ěŀħ ʭý ĚýùĚý ʯ(i.i.d˅) Ėőęùĕ äőʭĠÞŰ ĵŘŃŗ
:ĖģʭýäŎ ęùĚŃĚý ĚŰě ĮŰùĚģ i.i.d ʼnʭŒâŞğ
:ʴ ʼnŗĖċ
4QAM
16QAM
64QAM
-ʴ
-ʳºʹʻ
-ʳºʹʵ
ãʭŕäáÚŰŗ ŗ (ʴ) ŔŊĕʭĸŎ Ŕý ŔċŘă ʭý ˫ĚŞĠŎ ĖŒ× àŒŰĖŞĿ ʼnʭőʭÝ ęĕ
ãʭŕʼnŘþ˙ğ ŐŞý ˫Ėģ ˫ĜŞŊʭŎĚő ĂŒŊŘŎŘÝ Ŕİýùę ŏùŘăäŎ [ʴʷ-ʴʵ]ĂŒŊŘ˙Ý
:ĕŘ˙ő ŏʭŞý (ʸ) ŔŊĕʭĸŎ āęŘħ Ŕý ùę äĄĿʭŰęĕ ãʭŕʼnŘþ˙ğ ŗ äŊʭğęù
E{x(n) x(n W 1 ) x( n W 2 ) x(n W 3 )}
­ E ( x 4 ), W 1 W 2 W 3
®
otherwise
¯0,
0
(ʼ)
C 42, x
1
E (C 2 21, y G g2 )
L 1
äŒŞ˙Ĕă ęùĖńŎ ěù āʭþğʭĐŎ ęĕ ŔÞŒŰù Ŕý ŔċŘă ʭý äĸŃùŗ ĮŰùĚģ ęĕ äŊŗ
ʭńŞŃĕ (ʻ) ʼnŘŎĚĿ ęĕ ˫Ėőʭ˙ŞŃʭý ĚŰĕʭńŎ ʯĕŘģäŎ ˫ĕʭŀĄğù ãęʭŎí ãʭŕŏʭ˙Ŏ
ʼnʭŒâŞğ ŗ ʼnʭőʭÝ üŰùĚī ęùĖńŎ ˛ŞŊĕ Ŕý ãĕęùŘŎęĕ ŗ ĖőŘģä˙ő Ěŀħ ʭý ĚýùĚý
ĕʭČŰù Ćķʭý ĕŘē ĚŎù ŐŰù ŔÝ ĖőŘģäŎ äŖċŘă ˛ýʭŃ ęùĖńŎ ãùęùĕ äŊʭğęù
.ĕĕĚâŞŎ [ʻ] ōĄŰęŘâŊù ŔŋŞğŗ Ŕý ʼnʭőʭÝ üŰùĚī ŐŞ˙Ĕă ęĕ ˛ēùĖă
ęùĖńŎ ŏĖģ ßęĜý üċŘŎ ŔÝ äŋŰťĕ ěù äÞŰ (ʻ)ŗ(ʹ) ʼnŘŎĚĿ Ŕý ŔċŘă ʭý
L-1 ĚŞĠŎ üŰĚī ŏĕŘý Ü×ŘÝ ʯĕŘģäŎ äŋħù Ŕŋ˙ċ Ŕý ĂþĠő ˫Ėőʭ˙ŞŃʭý
äáÚŰŗ ŐŞŒ× ãùęùĕ ʼnʭőʭÝ ŔÝ äĄŊʭď ęĕ .Ăğù ʼnʭőʭÝ üŰùĚī ĚŰʭğ Ŕý ĂþĠő
ĂŃĕ ŗ ĕŘģäŎ ˛ÞĤŎ ęʭ×ĕ [ʻ] ōĄŰęŘâŊù ˫ŘŞģ Ŕý ʼnʭőʭÝ ŐŞ˙Ĕă Ėģʭý
.ĖýʭŰäŎ ĢŕʭÝ äğŘĠĐŎ āęŘħ Ŕý ŐŞ˙Ĕă
ĞőʭŰęùŗ ŗ äğŘá üŰùĚī ʭý ˫ĚŞĠŎ ęʭŖ× ʼnʭőʭÝ ŗĕ ĵŘīŘŎ ŐŰù äğęĚý ãùĚý
(L-1) ŌęʭŖ× ĚŞĠŎ üŰĚī ˫ěùĖőù ʼnŗù ʼnʭőʭÝ ęĕ .Ėģ ŔĄĿĚá ĚĴő ęĕ ʳºʳʸ
ěù Ōŗĕ ʼnʭőʭÝ ęĕ äŊŗ ʯĂğù ãĚĄÞ×ŘÝ ęùĖńŎ ãùęùĕ ʭŕĚŞĠŎ ĚŰʭğ Ŕý ĂþĠő
ĂþĠő ęùĖńŎ ʯ ʼnʭőʭÝ ŗĕ ŔĠŰʭńŎ ãùĚý .Ăğù ęùĕęŘēĚý äþğʭŒŎ ęùĖńŎ
E
h (k )
ʻ
h( k )
h(0)
4
m4y (0, U , U , k )
,k
m4y (0, U , U , 0)
0,..., L 1
m4y (0, L 1, L 1, k )
,
m4y (0, L 1, L 1, 0)
k
˫ŘŞģ Ŕý ùę [ʻ] ōĄŰęŘâŊù ʯ˫Ėőʭ˙ŞŃʭý ęùĖńŎ Ěćù ĢŕʭÝ ŗ ˛ÞĤŎ ŐŰù ˛ď ãùĚý
:ōŞŰʭ˙őäŎ čŦħù ĚŰě
h( k )
h(0)
2
ěù ˫ĕʭŀĄğù ʭý ŏí ęĕ ŔÝ ĖŰĕĚá Ŕ÷ùęù ä˙ĄŰęŘâŊù ęʭý ŐŞŊŗù ãùĚý [ʻ] ęĕ
ʼnʭőʭÝ àŒŰĖŞĿ üŰùĚī ʯʼnʭőʭÝ ěù ĂķŦįù ŐĄģùĕ ŏŗĖý ŗ ŏʭáęʭŎí äáÚŰŗ
ŔþăĚŎ ŏʭ˙Ŏ ěù ˫ĕʭŀĄğù ʭý [ʻ] ōĄŰęŘâŊù ęĕ .ĖģäŎ ˫ĕě ŐŞ˙Ĕă ˫ĚŞĠŎĖŒ×
ŔþğʭĐŎĚŰě āęŘħ Ŕý ʼnʭőʭÝ ˫Ėģ ˫ĜŞŊʭŎĚő üŰùĚī ʯäĄĿʭŰęĕ ʼnʭŒâŞğ ŌęʭŖ×
:ĖőŘģäŎ
(ʴʳ)
(ʹ)
0,..., L 1
ŏí ęĕ ŔÝ
ŗ Ėģ ŔþğʭĐŎ ŘŊęʭÝ ŔĄőŘŎ ġŦă ʴʳʳʳ ŗ ʶʳdB ĜŰŘő Ŕý ʼnʭŒâŞğ ĂþĠő ęĕ
ęĕ ŔÝ ĕŘģäŎ ˫ĖŕʭĤŎ ʯ Ăğù ˫Ėģ ˫ĕùĕ ŏʭĤő Ōŗĕ ʼnŗĖċ ęĕ ŏí ĊŰʭĄő ŗ
ŗ Ăğù ãĚĄáęĜý ęùĖńŎ ãùęùĕ |R/M| ʯ Ōŗĕ ʼnʭőʭÝ Ŕý ĂþĠő ʼnŗù ʼnʭőʭÝ
.ĕŘý ĖŕùŘē ŔċŘă ˛ýʭŃ ˫Ėőʭ˙ŞŃʭý ęùĖńŎ
h (k )
k 0
­ L 1
2½
®¦ h( k ) ¾
¯k 0
¿
m (0, 4, 4, 0) h(0)h(l 1) E ( x )
m4y (0, 4, 4, 0)
2
y
4
M
4
ʼnʭőʭÝ ŐŞ˙Ĕă ãùĚý ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù-ʶ
y
4
ʼnʭőʭÝ ŗĕ Ěŕ ãùĚý ( R
¦ h( k )
(ʷ)
,
2
ĂŒŊŘŎŘÝ ęùĖńŎ ŏĕęŗí ĂğĖý ãùĚý ʯ(ʸ) ʼnŘŎĚĿ Ŕý ŔċŘă ʭý üŞăĚă ŐŰù Ŕý
-äŎ ʼnʭőʭÝ üŰùĚī ěù ŔĄĿĚá Ěý ŔÝ E ęùĖńŎ ĂĠŰʭýäŎ äŊʭğęù ãʭŖŊŘþ˙ğ
.ĕŘ˙ő ŔþğʭĐŎ ùę Ėģʭý
m (0, 4, 4, 0) Ŕŋ˙ċ ˛Ý Ŕý (Residual) ˫Ėőʭ˙ŞŃʭý
)
C42, y
.
m4y (0,W , U , T )
E ( y (n) y (n W ) y (n U ) y (n T )) ,
(ʺ)
ęĕ ʼnʭőʭÝ üŰùĚī ãʭċ Ŕý ˫ĕěŐŞ˙Ĕă ˫ĜŞŊʭŎĚő üŰùĚī ŏĕùĕ ęùĚŃ ʭý
.ĕŘ˙ő ŔþğʭĐŎ äþŰĚńă ęŘį Ŕý ùę E ęùĖńŎ ŏùŘăäŎ ʯ(ʸ) ŔŊĕʭĸŎ
ʯŏí ěù ʼnʭőʭÝ ˫ĜŞŊʭŎĚő üŰùĚī ĉùĚĔĄğù ˫ŘĐő ŗ (ʹ) ʼnŘŎĚĿ äğęĚý ãùĚý
: ōŞŕĕäŎ ĮĠý ĚŰě āęŘħ Ŕý ùę ŔŊĕʭĸŎ ŐŰù ĉĚĔŎ ŗ āęŘħ
Independent and identically distribution
۷۵۲
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
-äŎ (˫Ėģ ĉęĕ (ʴ) ʼnŗĖċ ęĕ ŔÝ)äĸŃùŗ ęùĖńŎ Ŕý ãĚĄŒŞŰʭÏ ĜŰŘő Ŕý ʼnʭŒâŞğ
.ĖŒŰùĚá
2
4QAM proposed algorithm
4QAM algorithm [8]
16QAM proposed algorithm
16QAM algorithm [8]
1.8
ęʭŞĄēù ùę ^0,..., L 1` ĚŰĕʭńŎ ěù äÞŰ ĖőùŘăäŎ U ŏí ęĕ ŔÝ
(ʻ) ŔŊĕʭĸŎ ĉĚĔŎ ŗ āęŘħ ęĕ ĕŘċŘŎ ˫Ėőʭ˙ŞŃʭý ęùĖńŎ ŔÞŒŰù ãùĚý .ĖŰʭ˙ő
-ŔőŘá Ŕý U ʯĂŊʭď L-1 ŏʭŞŎ ěù ʯĕĕĚá ō˙ŞŒŞŎ äŋħù Ŕŋ˙ċ ʭý ŔĠŰʭńŎ ęĕ
)äĄĿʭŰęĕ ʼnʭŒâŞğ ŌęʭŖ× ŔþăĚŎ ŏʭ˙Ŏ ĖőùŘĄý ŔÝ ĕĕĚáäŎ ûʭĔĄőù äŰù
.ĖŰʭ˙ő ō˙ŰĜÝʭŎ ùę ( m4y ( U , U , U , U )
Residual ęùĖńŎ ęĕ ʼnʭőʭÝ Ěćù äğęĚý
1.6
|R/M|
ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù
1.4
:ʵ ʼnŗĖċ
|R/M|
[ʻ] ōĄŰęŘâŊù
ʼnʭőʭÝ üŰùĚī
ʼnʭőʭÝ
C42
h(0) = ʴ
1.2
ʳºʳʴʻʹ
ʳºʺʻʼʼ
1
H1
h(0) = ʴ
ʳºʳʳʺʹ
-5
-4
-3
-2
-1
0
1
SNRdB
2
3
4
5
h(1) = ʳºʳʶʺ + ʳºʴʸ i
h(2) = ʳºʳʴʴ - ʳºʳʵʴi
H2
h(3) = ʳºʴʷʸ + ʳºʴʳʸi
( E ( E ) E ) E ãʭİē ĶýĚŎ ŐŞâőʭŞŎ ˫ĜŞŊʭŎĚő ęùĖńŎ ʯʼnʭőʭÝ ŐŞ˙Ĕă
E
(L=4) ˫ĚŞĠŎ ęʭŖ× ʼnʭőʭÝ ÜŰ ãùĚý āŗʭŀĄŎ ãʭŕĜŰŘő Ŕý ʼnʭŒâŞğ ĂþĠő ęĕ
ōĄŰęŘâŊù ęĕ ĕŘģäŎ ˫ĖŕʭĤŎ ŔÝ ŔőŘâőʭ˙ŕ .Ăğù ˫Ėģ ˫ĕùĕ ŏʭĤő
ęĕ ŗ ˫ĕŘý Ü×ŘÝ ęʭŞĠý [ʻ] ōĄŰęŘâŊù ʭý ŔĠŰʭńŎ ęĕ ęùĖńŎ ŐŰù ãĕʭŖŒĤŞÏ
.Ăğù ęùĕęŘēĚý ãĚăťʭý ãęùĖŰʭÏ ěù āŗʭŀĄŎ ãʭŕĜŰŘő Ŕý ʼnʭŒâŞğ ĂþĠő
0.16
Proposed algorithm
algorithm [8]
m4y (0, U , U , 0) h(0)h( U ) E ( x 4 )
2
R
ęĕ ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù ĂŃĕ ŏùĜŞŎ ŏĕùĕ ŏʭĤő ãùĚý Ōŗĕ ˛Þģ ęĕ .
0.14
ʳºʳʶʹʴ
6
[ʻ]ōĄŰęŘâŊù ŗ ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù ĮğŘă C 42 ˫ĕě ŐŞ˙Ĕă ęùĖńŎ :ʴ ˛Þģ
L=ʷŗ N=ʵʳʳʳ ãùĚý SNR Ŕý ĂþĠő
M
( propsed )
m4y (0, U , U , 0)
ęùĖńŎ
.Ăğù ˫ĖŰĕĚá Ŕ÷ùęù ŗĕ ʼnŗĖċ ęĕ ŗ ˫Ėģ ŔþğʭĐŎ ŗĕ ŗ ÜŰ ãʭŕʼnʭőʭÝ ãùĚý
Ŕý ĂþĠő ʼnʭőʭÝ ŗĕ Ěŕ ęĕ ˫Ėőʭ˙ŞŃʭý ęùĖńŎ ĕŘģäŎ ˫ĖŕʭĤŎ ŔÝ ŔőŘâőʭ˙ŕ
.Ăğù ŔĄĿʭŰ ĢŕʭÝ [ʻ] ōĄŰęŘâŊù
˛ýʭŃ Ėď ʭă Ăģùĕ ĕŘċŗ [ʻ] ōĄŰęŘâŊù ęĕ ŔÝ äŎʭŖýù üŞăĚă ŐŰù Ŕý
ŔŊĕʭĸŎ ĉĚĔŎ ŗ āęŘħ ęĕ ˫Ėőʭ˙ŞŃʭý ĚŰĕʭńŎŗ ĖýʭŰäŎ ĢŕʭÝ äŰùŔĴďŦŎ
˛ýʭŃ ˫ěùĖőù Ŕý ʼnʭőʭÝ üŰùĚī ŐŞ˙Ĕă ĂŃĕ ŗ ĖŰùĚáäŎ Ěŀħ Ă˙ğ Ŕý (ʼ)
ãěʭğŔŞþģ ĊŰʭĄő ęĕ ŏùŘăäŎ ùę ĵŘīŘŎ ŐŰù .ĖýʭŰäŎ ĢŰùĜĿù äŰùŔĴďŦŎ
.ĕŘ˙ő ˫ĖŕʭĤŎ
ãěʭğŔŞþģ – ʷ
˫ĕ ʼnŘį ŗ ęʭŖ× ʼnŘį ʭý äŋŰùę àŒŰĖŞĿ ʼnʭőʭÝ ʼnĖŎ ŗĕ ěù ʭŕãěʭğŔŞþģ ęĕ
ōĄŰęŘâŊù Ŕý ŔċŘă ʭý . (h(0),..., h( L 1)) Ăğù ˫Ėģ ˫ĕʭŀĄğù
ĚýùĚý ùę ŏí ęùĖńŎ ĂŊŘŖğ ãùĚý ʯ h (0) ęùĖńŎ Ŕý ŏí ěʭŞő ŌĖķ ŗ ãĕʭŖŒĤŞÏ
ĮĄĔŎ äğŘá äĿĕʭĨă ãʭŕĚŞŞļĄŎ ʭý ĚýùĚý ùę üŰùĚī ŔŞńý ŗ ˫ĕùĕ ęùĚŃ ÜŰ ʭý
ãùęùĕ ÜŰ Ěŕ ŔÞŰęŘį Ŕý ōŞŰʭ˙őäŎ ĩĚĿ Ěŀħ ŐŞâőʭŞŎ ʭý ˛ńĄĠŎ
0.12
0.1
0.08
0.06
0.04
ʵʳʳʳ ãùĚý ùę āʭŞŋ˙ķ.ĖŒĄĠŕ Ěŀħ ŐŞâőʭŞŎ ŗ G h2 0.05 ĞőʭŰęùŗ
˫ęʭ˙ģ ˛Þģ ęĕ .ōŞŕĕäŎ ŌʭČőù N ʼnŘį ʭý ãʭŕ˫ĕùĕ ŗ ŘŊęʭÝ ŔĄőŘŎ ġŦă
0.02
1
2
SNR Ŕý ĂþĠő
h(2) = ʳºʳʼʺ - ʳºʵʴ i
h(3) = ʳºʳʵʷ + ʳºʳʴʺi
0.8
0
0
h(1) = ʳºʳʻʼ + ʳºʵʵ i
3
E (E ) E ʯ
E
4
5
6
SNR (dB)
7
8
9
10
E ŐŞ˙Ĕă ãʭİē ˫ĜŞŊʭŎĚő ęùĖńŎ :ʵ ˛Þģ
L=4 ŗ N= ʵʳʳʳ
ãùĚý
ŏŘŞğťŗĖŎ ãùĚý C 42 ĚŰĕʭńŎ ʯ(L=4) ˫ĚŞĠŎ ęʭŖ× ʼnʭőʭÝ ÜŰ ãùĚý ʯÜŰ
˫ĕùĕ ĢŰʭ˙ő āŗʭŀĄŎ ãʭŕĜŰŘő Ŕý ʼnʭŒâŞğ Ŕý ĂþĠő 16QAM , 4QAM
˫ĕě ŐŞ˙Ĕă ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù ŗ [ʻ]ōĄŰęŘâŊù ĮğŘă ĚŰĕʭńŎ ŐŰù.Ėőù ˫Ėģ
ōĄŰęŘâŊù ĮğŘă ŔÝ C 42 ĚŰĕʭńŎ ĕŘģäŎ ˫ĖŕʭĤŎ ŔÝ ŔőŘâőʭ˙ŕʯĖőù˫Ėģ
ĂþĠő ęĕ ŗ ĖŒĄĠŕ ęùĕęŘēĚý ãĚăťʭý ãęùĖŰʭÏ ěù Ėőù˫Ėģ ˫ĕě ŐŞ˙Ĕă ĖŰĖċ
۷۵۳
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
ĢŰùĜĿù ʭý ʼnʭőʭÝ ŐŞ˙Ĕă ĂŃĕ .ĖőŘģäŎ ˫ĕě ŐŞ˙Ĕă ťʭý ęʭŞĠý ĂŃĕ ʭý ʼnʭőʭÝ
ĮğŘă ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă Ėħ ęĕ .ĖýʭŰä˙ő ĢŕʭÝ ʼnʭőʭÝ ʼnŘį
äŋŎʭÝ āʭķŦįù ŔÝ Ăğù äİŰùĚģ ęĕ ĂŞńĿŘŎ Ėħ ęĕ ʭý ĚýùĚý ōĄŰęŘâŊù ŐŰù
-äŎ Ėģʭý ĚĄĤŞý ʭŕŏŘŞğťŗĖŎ ĕùĖĸă ŔÞŞăęŘħ ęĕ .Ėģʭý ĕŘċŘŎ ʼnʭőʭÝ ěù
ʹŗʷ ŔþăĚŎ ãʭŕ ĂŒŊŘŎŘÝ ˛Ŏʭģ ŔÝʯ ʭŕäáÚŰŗ ěù ãęùĕĚý ěù ˫ĕʭŀĄğù ʭý ŏùŘă
.ĕŘ˙ő ˛ħʭď äýŘē ĊŰʭĄő ĖŒģʭý ʻŗ
90
80
àŒŰĖŞĿ ʼnʭőʭÝ ęĕ ŏŘŞğťŗĖŎ ęʭÝĕŘē ĦŞĔĤă ōĄŰęŘâŊù äğęĚý ãùĚý
} ãʭŕŏŘŞğťŗĖŎ ŔķŘ˙ČŎ ěù [ʻ] ōĄŰęŘâŊù ʭý ŏí ŔĠŰʭńŎ ŗ ˫ĚŞĠŎ ĖŒ×
ʼnʭőʭÝ ʼnĖŎ ŗĕ ãùĚý ãěʭğŔŞþģ .ōŰĕŘ˙ő ˫ĕʭŀĄğù {4QAM,16QAM,64QAM
ŏʭĠÞŰ ʭŕŏŘŞğťŗĖŎ Ŕ˙ŕ ʼnʭğęù ʼnʭ˙Ąďù .ĂĿĚá āęŘħ ˫ĚŞĠŎ ˫ĕ ŗ ęʭŖ×
ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă ʼnʭ˙Ąďù ŌŘğ ˛Þģ ęĕ.Ăğù ˫Ėģ ĩĚĿ
ęʭŖ× ʼnŘį ʭý àŒŰĖŞĿ ʼnʭőʭÝ ÜŰ ãùĚý āŗʭŀĄŎ ãʭŕĜŰŘő Ŕý ʼnʭŒâŞğ Ŕý ĂþĠő
ĦŞĔĤă Ėħ ęĕ ĕŘģäŎ ˫ĖŕʭĤŎ ŔÝ ŔőŘâőʭ˙ŕ . Ăğù ˫Ėģ ˫ĕùĕ ŏʭĤő
Ŕý [ʻ]ōĄŰęŘâŊù Ŕý ĂþĠő ãĕʭŖŒĤŞÏ ōĄŰęŘâŊù ĮğŘă ŏŘŞğťŗĖŎ ĎŞĐħ
āʭķŦįù ŔÝ Ăğù äőʭŎě ʭý ĚýùĚý ŏí ŏùĜŞŎ ŗ ŔĄĿʭŰ ĢŰùĜĿù äğŘĠĐŎ ęŘį
ōĄŰęŘâŊù ãťʭý ĂŃĕ ĚâőʭŞý ĕŘē ŐŰù ŗ Ėģʭý Ăğĕ ęĕ ʼnʭőʭÝ ěù äŋŎʭÝ
.Ăğù ʼnʭőʭÝ ŐŞ˙Ĕă ęĕ ãĕʭŖŒĤŞÏ
70
Pc
100
60
90
50
80
40
30
-10
70
Pc
algoithm[8]
propsed algoithm
with perfect info
60
-5
0
5
10
SNR(dB)
15
20
25
30
50
-ŏŘŞğťŗĖŎ ŔķŘ˙ČŎ ŐŞý ěù ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă ʼnʭ˙Ąďù :ʷ ˛Þģ
L=ʴʳŗ N=ʵʳʳʳ ãùĚý SNR Ŕý ĂþĠő {4QAM,16QAM,64QAM} ãʭŕ
40
30
-10
ĶċùĚŎ
propsed algoithm
algorithm[8]
with perfect info
-5
0
5
10
SNRdB
15
20
25
30
-ŏŘŞğťŗĖŎ ŔķŘ˙ČŎ ŐŞý ěù ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă ʼnʭ˙Ąďù :ʶ ˛Þģ
[1] Panagiotou, P., A. Anastasopoulos, and A. Polydoros.
Likelihood ratio tests for modulation classification. in
MILCOM 2000. 21st Century Military Communications
Conference Proceedings. 2000.
[2] Swami, A. and B.M. Sadler, Hierarchical digital
modulation
classification
using
cumulants.
Communications, IEEE Transactions on, 2000. 48(3): p.
416-429.
[3] Spooner, C.M. On the utility of sixth-order cyclic
cumulants for RF signal classification. in Signals, Systems
and Computers, 2001. Conference Record of the ThirtyFifth Asilomar Conference on. 2001.
[4] Dobre, O.A., et al., Survey of automatic modulation
classification techniques: classical approaches and new
trends. Communications, IET, 2007. 1(2): p. 137-156.
[5]Dobre, O.A., et al. Selection combining for modulation
recognition
in
fading
channels.
in
Military
L= ʷŗ N=ʵʳʳʳ ãùĚý SNR Ŕý ĂþĠő {4QAM,16QAM,64QAM} ãʭŕ
ãʭŕʼnʭŒâŞğ ęĕ ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă Ėħęĕ ŌęʭŖ× ˛Þģ ęĕ
˫ĕùĕ ŏʭĤő (L=ʴʳ) ˫ĕ ʼnŘį ʭý àŒŰĖŞĿ ʼnʭőʭÝ ÜŰ ãùĚý MQAM ˫ĕùŘőʭē
ʼnʭőʭÝ ʼnŘį Ŕ× Ěŕ ĕŘģäŎ ˫ĖŕʭĤŎ ŌŘğ ˛Þģ ʭý ŔĠŰʭńŎ ęĕ .Ăğù ˫Ėģ
ĕùĖĸă ãùĚý ŗ ĖýʭŰäŎ ĢŕʭÝ ĜŞő ĎŞĐħ ĦŞĔĤă ʼnʭ˙Ąďù ĖýʭŰ ĢŰùĜĿù
Ŕý ŔċŘă ʭý.ĖģʭýäŎ ãĚĄĤŞý ãʭŕ ʼnŘþ˙ğ ĕùĖĸă Ŕý ěʭŞő ĚĄĤŞý ãʭŕĚŞĠŎ
ōĄŰęŘâŊù ĮğŘă ŏŘŞğťŗĖŎ ĎŞĐħ ĦŞĔĤă Ėħęĕ ęʭŖ× ˛Þģ
ěù ˛ŎʭÝ äăʭķŦįù ŔÝ Ăğù äőʭŎě ęĕ ĂŞńĿŘŎ ʼnʭ˙Ąďù ʭý ĚýùĚý ãĕʭŖŒĤŞÏ
ʼnʭőʭÝ ŐŞ˙Ĕă ęĕ ōĄŰęŘâŊù ĂŃĕ ŔÝ ĖŕĖŞŎ ŏʭĤő ŐŰùŗ Ėģʭý ęʭŞĄēù ęĕ ʼnʭőʭÝ
.ĖýʭŰä˙ő ĢŕʭÝ ʼnʭőʭÝ ʼnŘį ĢŰùĜĿù ʭý
ãĚŞáŔČŞĄő - ʸ
ęĕ ŏŘŞğťŗĖŎ ĦŞĔĤă ãùĚý ĖŰĖċ ä˙ĄŰęŘâŊù ŔŊʭńŎ ŐŰù ęĕ
Ŕ÷ùęù ˫ĚŞĠŎĖŒ× àŒŰĖŞĿ ʼnʭőʭÝ ęĕ ŗ MQAM ˫ĕùŘőʭē ãʭŕʼnʭŒâŞğ
˫ĜŞŊʭŎĚő üŰùĚī [ʻ] ęĕ ˫Ėģ Ŕ÷ùęù ġŗę čŦħù ʭý ōĄŰęŘâŊù ŐŰù ęĕ.ĖŰĕĚá
۷۵۴
۱۳۹۴ ‫ اردﯾﺒﻬﺸﺖ‬۲۴ ‫ ﺗﺎ‬۲۰ ،‫ داﻧﺸﮕﺎه ﺻﻨﻌﺘﯽ ﺷﺮﯾﻒ‬،‫ﺑﯿﺴﺖ و ﺳﻮﻣﯿﻦ ﮐﻨﻔﺮاﻧﺲ ﻣﻬﻨﺪﺳﯽ ﺑﺮق اﯾﺮان‬
Communications Conference, 2005. MILCOM 2005.
IEEE. 2005.
[6] Dobre, O.A., Y. Bar-Ness, and S. Wei. Higher-order
cyclic cumulants for high order modulation classification.
in Military Communications Conference, 2003. MILCOM
'03. 2003 IEEE. 2003.
[7] Dobre, O.A., Y. Bar-Ness, and S. Wei. Robust QAM
modulation classification algorithm using cyclic
cumulants. in Wireless Communications and Networking
Conference, 2004. WCNC. 2004 IEEE. 2004.
[8] Hsiao-Chun, W ,.M. Saquib, and Y. Zhifeng, Novel
Automatic Modulation Classification Using Cumulant
Features for Communications via Multipath Channels.
Wireless Communications, IEEE Transactions on, 2008.
7(8): p. 3098-3105.
[9] Orlic, V. and M.L. Dukic. Algorithm for automatic
modulation classification in multipath channel based on
sixth-order cumulants. in Telecommunication in Modern
Satellite, Cable, and Broadcasting Services, 2009.
TELSIKS '09. 9th International Conference on. 2009.
[10] Orlic, V.D. and M.L. Dukic ,Automatic modulation
classification algorithm using higher-order cumulants
under real-world channel conditions. Communications
Letters, IEEE, 2009. 13(12): p. 917-919.
[11] Orlic, V.D. and M.L. Dukic. Automatic modulation
classification: Sixth-order cumulant features as a solution
for real-world challenges. in Telecommunications Forum
(TELFOR), 2012 20th. 2012.
[12] Dandawate, A.V. and G.B. Giannakis, Asymptotic
theory of mixed time averages and kth-order cyclicmoment and cumulant statistics. Information Theory,
IEEE Transactions on, 1995. 41(1): p. 216-232.
[13] Gardner, W.A. and C.M. Spooner, The cumulant
theory of cyclostationary time-series. I. Foundation.
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3387-3408.
[14] Spooner, C.M. and W.A. Gardner, The cumulant
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.
۷۵۵

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