Title: Prezentace aplikace PowerPoint
1Sub-Optimum MSF-MUD for CDMA Systems
Dušan Kocur, Jana Cížová, Stanislav
Marchevský Department of Electronics and
Multimedia Communications Faculty of Electrical
Engineering and Informatics Technical University
of Košice, Park Komenského 13, 041 20
Košice Slovak Republic E-mail Dusan.Kocur_at_tuke.sk
, Jana.Cizova_at_tuke.sk, Stanislav.Marchevsky_at_tuke.s
k
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32. MSF-MUD receiver
- MSF-MUD is the promising member of the nonlinear
singlestage multi-user receivers' (NSSMUD)
family, - NSS-MUDs approximate the nonlinear boundary of
the decision regions better than the linear
receivers, - the output of the NSS-MUD is taken as the sign of
the nonlinear transformation of the output of a
bank of the matched filters (BMF), - the nonlinear transformation is done by
multi-channel conventional microstatistic filter
(M-CMF).
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53. M-CMF
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63.1 Threshold decomposer
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74. M-CMF and MSF-MUD
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85. The M-CMF design procedure
- minimum meansquare error criterion
- where
- threshold value vector,
-
- desired signals.
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95. The M-CMF design procedure basic principle
Step 1 threshold values estimation (SC-M, GA-M,
CDF-M). Step 2 optimum coefficients estimation
, ...crosscorrelatio
n vector of the desired signals and the
signals at the output of the TDi,
... crosscorrelation function of the signals at
the output of the TDi , Step 3
evaluation of the cost function of MSF-MUD
(minimum BER).
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106. TD level estimation
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116. TD level estimation (cont.)
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126.1 Scanning method (SC-M)
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136.2 Genetic algorithm based method (GA-M)
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146.3 Method of cumulative distribution function
(CDF-M)
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157. Computer experiments
- synchronous DSCDMA base-band transmission system
in the AWGN channel, - first 3 experiments are deal with MSF-MUD design
procedure, - next 9 experiments are deal with MSF-MUD
properties.
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167. Computer experiments (cont.)
Number of users 2
Number of Transmitted bits 1 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Number of threshold levels 4
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177. Computer experiments (cont.)
Number of users 30
Number of transmitted bits 10, 100, 200, 300, 500, 1 000, 2 000, 5 000, 7 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Number of threshold levels 4
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187. Computer experiments (cont.)
Number of users 20
Length of training sequence 300
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Number of threshold levels 4
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197. Computer experiments (cont.)
Number of users 2
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 11
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207. Computer experiments (cont.)
Number of users 10
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 11
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217. Computer experiments (cont.)
Number of users 20
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 11
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227. Computer experiments (cont.)
Number of users 30
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 11
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237. Computer experiments (cont.)
Number of users 1, 2, 5, 7, 10, 20, 30
Number of transmitted bits 10 000, 7 000
Spreading codes Gold
Number of chips for 1 period 31
Eb/No 5 dB
Environment AWGN
Near-far effect 11
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247. Computer experiments (cont.)
Number of users 2
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 0.11
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257. Computer experiments (cont.)
Number of users 5
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 0.11
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267. Computer experiments (cont.)
Number of users 2
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Eb/No 5 dB
Environment AWGN
Near-far effect 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 11
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277. Computer experiments (cont.)
Number of users 5
Number of transmitted bits 10 000
Spreading codes Gold
Number of chips for 1 period 31
Environment AWGN
Near-far effect 11
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288. CONCLUSIONS
- the design procedure of M-CMF and MSF-MUD was
described. - Properties
- comparable or lower complexity than other
non-linear MUD, - easily rearranged in adaptive or blind
modifications, - attractive and promissing for CDMA and advanced
transmission systems like MC-CDMA.
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29THANK YOU FOR YOUR ATTENTION
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