PowerPoint-Pr

1
Effect of Carrier Frequency Offset on Channel
Capacity in Multi User OFDM-FDMA Systems
Martin Stemick and Hermann Rohling Hamburg
University of Technology Institute of
Telecommunications
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Motivation
In frequency-selective radio channels, OFDM-FDMA
provides

• high data rates
• high degree of adaptivity

Adaptive subcarrier allocation exploits Multi
User Diversity
3
Cell Model
BS
MT
WSSUS Channel
Downlink Situation
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Multi User Diversity and Blocksize
QPSK, R1/2, 16 users
0
10
-1
10
-2
BER
10
-3
10
7 dB
-4
10
-6
-4
-2
0
2
4
6
8
SNR (dB)
blocksize 8
subcarrierwise
? Smaller blocksize yields higher diversity gain
5
Pure Multi User Diversity
Subcarrierwise selection, QPSK, R1/2
4 users
8 users
16 users
Increasing number of users
? Adaptive subcarrier allocation yields a high
diversity gain
6
Cell Model in the Uplink
BS
Bandwidth at BS
MT
subcarriers
Uplink Situation

• Signals of mobile terminals superimpose at base
  station
• Every MT shows individual Carrier Frequency
  Offset (CFO)
• Non-ideal synchronization leads to Intercarrier
  Interference (ICI)

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Analytical Model for Intercarrier Interference
Received Signal at BS
Since transmit symbols can be modeled as
random variables
? Stochastic modeling of
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Analytical Model for Intercarrier Interference
Stochastic assumptions

• Modulation symbols are statistically independent
  random variables

• Transmit power is normalized

? Therefore, we can apply the central limit
theorem
(ICI noise power)
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Analytical Model for Intercarrier Interference
This leads to the following description of ICI
influence
(ICI noise power)
(Rx power loss)
(Overall SNR)
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Example for Intercarrier Interference
df0
Receive-Amplitude
0
1
2
3
4
5
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Evaluation of CFO on Allocation Schemes
Considering various subcarrier allocation schemes
in multi user systems

• Blockwise allocation (various blocksizes)

subcarriers

• Interleaved allocation

subcarriers
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Evaluation of ICI Noise
Blockwise allocation 2 users, 2 blocks,
blocksize 128
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Evaluation of ICI Noise
Blockwise / Interleaved allocation 2 users, 16
blocks, blocksize 16
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Evaluation of ICI Noise

• Blockwise allocation produces self-interference

• Interleaved allocation reduces self-interference
  but
• increases external interference

The distribution of ICI noise in the system
depends very much on the subcarrier allocation
scheme
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Effect of CFO on Capacity
After evaluation of noise power for individual
users, a measure for the performance of a multi
user system is needed
Using Shannon Capacity to quantify the effect of
CFO on the system performance
Shannon Capacity of user l
bits / OFDM-Sym.
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System Model
BS

• AWGN Channel
• WSSUS Channel

MT
Uplink Situation

• System assumptions
• 256 carriers, 16 users
• various allocation schemes
• random subcarrier assignment

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Simulation Results (AWGN Channel)
First Scenario

• All users in the cell are perfectly
  synchronized, except one

• Capacity of badly synchronized user is observed
  for various allocation schemes

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Simulation Results (AWGN Channel)
Second Scenario

• All users in the cell show consistent CFO of
  , except one

• Capacity of perfectly synchronized user is
  observed for various allocation schemes

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Comparison WSSUS AWGN
Second Scenario in AWGN and WSSUS Environment
Bits per OFDM-Symbol.
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Summary Conclusions

• Adaptive allocation yields high performance
  gains in the downlink

• In the uplink, interference due to non-ideal
  synchronization
• must be considered

• Choice of allocation scheme influences
  interference distribution and system
  performance

• This can be especially of interest in adaptive
  allocation schemes, where interference is the
  main noise contribution

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Thank you for your attention
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Results (wrong!!!)
one good user, all other unsynched, perf of good
user.
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Multi User Diversity and Blocksize
QPSK, R1/2, 16 users
blocksize 8
subcarrierwise
? Smaller blocksize yields higher diversity gain
24
Pure Multi User Diversity
Subcarrierwise selection, QPSK, R1/2
4 users
8 users
16 users
Increasing number of users
? Adaptive subcarrier allocation yields a high
diversity gain