Performance Improvement of Spatial Modulation in Multipath Fading Channel (Generalized Spatial Modulation)

1. ARVIN MOEINI – 504151332
TEL505E – MOBILE & PERSONAL
COMMUNICATION
ELECTRONIC AND COMMUNICATION DEPARTMENT
I STANBUL TECHNI CAL UNI VERSI TY

3. History
2001 First time “ Space modulation on wireless fading channels “ by A.Chau & S. Hang Yu
- introduce SSK special form of SM
2006 Common Method “Spatial modulation-a new low complexity spectral efficiency enhancing
technique,” by R. Mesleh, H. Haas
- every moment just 1 active antenna
-antenna numbers & symbol
2008 SM in OFDM “Spatial modulation,” by R. Mesleh, H. Haas , …
-Compare with Alamouti OFDM & V-BLAST OFDM
-Reduce 90% complexity in SM-OFDM
2010 Generalised SM “Generalised spatial modulation,” by A. Younis, N. Serafimovski, R.
Mesleh, and H. Haas
-Using Multi Active Antenna on every symbol slot

4. 2010 Trellis Code in SM “Trellis coded spatial modulation,” by R. Mesleh, M. D. Renzo...
2011 New Trellis Code “New trellis code design for SM,” by E. Basar, U. Aygolu,…
-Using multi antenna and TCM –> TCSM
-TCSM is better than TCM
2011 STBC-SM “Space-time block coded spatial modulation,” by E. Basar, U. Aygolu,…
- Using SM in Space-time Block Coding
- Coding gain and diversity together
2012 Multiple Active Ant. “Generalised spatial modulation system with multiple active
transmit antennas and low complexity detection scheme,” by J. Wang, S. Jia,…
-Higher Multiplexing gain than standard form

5. MIMO
• First idea was 1970
• todays standards IEEE 802.11n (WiFi)IEEE 802.16e
(WiMax) 3GPP 4G
• using multiple antenna was paid attention from 2000 in
universities and economic environments
• It cause multiplexing gain, diversity gain, antenna gain
and due to these data rate , error probability, signal to
noise ratio and interferences was improved.

6. Multiple Antenna Systems Gain
• Multiplexing gain
• Diversity gain
• Array gain

7. Multiplexing gain
Spatial multiplexing (often abbreviated
SM or SMX) is a transmission technique in
MIMO wireless communication to
transmit independent and separately
encoded data signals, so-called streams,
from each of the multiple transmit
antennas
Gains from incensement of data rate in
comparison with SISO named multiplexing
gain .

8. Communication Channel

9. Best example for communication channel  multiple person speak in a room
TDM  Speak by sort
FDM  speak by different voice frequency
CDM  Speak by different language
SDM  Speak in portioned sub rooms
Use same method for multi user access
TDMA FDMA CDMA SDMA
Spatial multiplexing is a powerful method for increase channel capacity at high SNR
R= Data rate at specific SNR
r= Multiplexing gain

10. Diversity gain
Repetitive Codes  Max Diversity
Diversity gain formula
r = Multiplexing gain
Pout= Outage probability
Data rate > channel Capacity

12. MRC
Xi = Transmitted Signal
yi = Received Signal from i’th antenna
ni = AWGN
αi = fading complex coefficients
Combination of 2 received signal at receiver

13. EGC
Same as MRC  Received signals χ K  for being same phase
SC
Detect signal that have highest E/No at receiver between received signals

14. If we cannot use receive diversity or we need more diversity gain

15. Because of these problems open loop without feedback is preferred  Space time coding
Comparing 2 methods

16. MIMO MODEL
Channel state information
Channel fading coefficient changes by the time
and its different along h11 h12 h21 .h22

17. SPACE TIME CODING
Mobile station  small  difficult to use multiple antenna  we choose
method with high diversity gain
First method with 2 antenna  ALAMOUTI

18. SPACE TIME TRELLIS CODE
Vahid Tarokh  1998  similar to convolutional codes or Trellis Coded
Modulation
transmit copies of trellis code by multiple antenna
difference with block code is that these codes are memorable
This method has more complexity compare with other methods

19. Spatial Modulation

20. Main idea of SM is to mapping 1 block data
bit into 2 unit data carrier

21. Antenna index
log2NT
Symbol
log2M
binary string data divided to log⌊ 2NT ⌋ + log2M Block
codes
SM TRANSMITTER
First sub-block code select
the antenna and active it then
second sub-block select
transmission symbol and
transmit them.
6 bit data  32QAM – 2 Antenna
 16QAM – 4 Antenna

22. SM CHANNEL
Best model for wireless channel is
Multipath Fading Channels, so we
simulate this channel in our simulations
The other point is that the wireless link
(elements of H matrix) should be
different with each other to have a clear
detection at receiver .

23. SM RECEIVER
For detecting Tx from Rx additive noise, receiver should know channel impulse
response completely for all links between transmitter and receiver. In general ( NR ×
NT ) impulse response should be estimated at receiver.
ML (maximum likelihood) detector  measure the distance between received
signals and detect the closest one.
• Measure the NR × NT × M
distances

26. Detection Method for
Transmitted Signals at Receiver

28. Generelised Spatial Modulation
This method was discussed recently in [5]
and in this system 1 symbol was sent by 2 or
more Antenna at the same time
In this method the number of antenna is not
limited but in general SM we have 2^N
antenna
Code Tran. symbol Active Ant. Num.

30. Performance Improvement
of SM
In this project we use Monte Carlo method for calculation of error
probability and these tests continue until errors number reach 100 .

31. QAM modulation simulation

32. SM simulation
Rayleigh Flat fading  1 active antenna  MAP Detector  its necessary to
know antenna index so we have
We have 2 errors in this systems  1- error related to transmitted symbol
2- error in antenna index estimator
both of them are separated from each other and they don’t have any effect to
each other Total error is the sum of these 2 errors

33. Comparing SM performance with 4 and 8 antenna

34. GSM simulation
Development kind of SM  multiple active
antenna  in our simulation 2 active Tx and 4
active Rx  Also all active antenna transmit 1
similar symbol  if we send with multiple antenna
we also use spatial diversity  decrease error
probability  in other hand we have more errors
because of more active transmit antenna

35. GSM performance

36. GSM error probability calculation
These 2 error are independent so we have

37. problems
No chance for using diversity for detection antenna number
This problem is due to that Detection of active antenna numbers is
used by channel fading coefficient
So we provide methods to improve the Antenna error probability

38. Improvement SM performance
On this project we focused on reducing the error probability of antenna detection because
the methods to reducing symbol error like increasing transmit antenna are not so efficient
This project methods for improving these system
•Using convolutional codes
•Parity check code

39. Convolutional coding
The best point of spatial modulation is spectral gain enhancement so we should
choose coding method that does not change spectral gain.
Trellis CodingCodingK bit K+1 bit

40. No change to spectral gain and
bandwidth but the problem is
that points are very close and
it’s difficult to detect
Error Probability ↑
Convolutional
Coding
GSM
Coding ch
an
ne
l GSM
decoding
Viterbi
algorithm

41. Convolutional Code (2, 1, 3)
Viterbi algorithm
First state of Viterbi algorithm
Repetitive state of Viterbi algorithm

42. We have good result but
complexity of system in
coding and decoding
section was increased so
we provide another
method for this system.

43. Parity check code
In GSM if there is an error in antenna detection
usually it occurs just in 1 antenna  so we find a way
to improve error channel detection probability 
because we don’t have any information about  it
acts just through channel information matrix  So we
cannot use diversity
simple method for detecting 1 bit error  parity
check code idea  adding 1 bit parity to symbol for
antenna info
Number of 1
odd
even
Add 1 (to be even)
Add 0
Receiver
Num of 1 even
No Error √
or 2,4 χ

44. Using more antenna at transmitter

45. Small modulations have better performance
So we can use these method for using small size modulation

46. We also can improve the system
performance by increasing the
number of receiver antenna , you
can see in the figure comparison
of 4-Rx and 5-Rx of GSM and
MIMO .

47. Conclusion
In this project we provide 3 methods to improve the performance of GSM using
convolutional coding and parity check code methods
•in the first method we added convolutional coding to the GSM structure and we
saw 2.5dB improvement in the performance of this method.
•In the second method we just have some changes in transmitted symbol and
we have 0.7 dB improvement with low complexity in our system.
•In the third one by increasing the number of antenna at transmitter we have
0.7dB gain and at receiver we saw 2dB at average SNRs and our complexity
increases by the antenna number.
According our necessity and facilities each of these methods can be useful and
improve our system performance

48. [1] R. Mesleh, H. Haas, C. W. Ahn, and S. Yun, “Spatial modulation-a new low complexity
spectral efficiency enhancing technique,” in Communications and Networking in China, 2006.
ChinaCom’06. First International Conference on, pp. 1–5, IEEE, 2006. ,
[2] Y. A. Chau and S.-H. Yu, “Space modulation on wireless fading channels,” in Vehicular
Technology Conference, 2001. VTC 2001 Fall. IEEE VTS 54th, vol. 3, pp. 1668–1671, IEEE, 2001.
[3] R. Y. Mesleh, H. Haas, S. Sinanovic, C. W. Ahn, and S. Yun, “Spatial modulation,”
Vehicular Technology, IEEE Transactions on, vol. 57, no. 4, pp. 2228–2241, 2008.
[4] J. Jeganathan, A. Ghrayeb, and L. Szczecinski, “Spatial modulation: optimal detection and
performance analysis,” Communications Letters, IEEE, vol. 12, no. 8, pp. 545–547, 2008. ,
[5 A. Younis, N. Serafimovski, R. Mesleh, and H. Haas, “Generalised spatial modulation,” in
Signals, Systems and Computers (ASILOMAR), 2010 Conference Record of the Forty Fourth
Asilomar Conference on, pp. 1498–1502, IEEE, 2010.
[6] R. Mesleh, M. D. Renzo, H. Haas, and P. M. Grant, “Trellis coded spatial modulation,”
Wireless Communications, IEEE Transactions on, vol. 9, no. 7, pp. 2349– 2361, 2010.
References

49. [7] E. Basar, U. Aygolu, E. Panayirci, and H. Poor, “New trellis code design for spatial modulation,” Wireless
Communications, IEEE Transactions on, vol. 10, no. 8, pp. 2670–2680, 2011.
[8] E. Basar, U. Aygolu, E. Panayirci, and H. V. Poor, “Space-time block coded spatial
modulation,” Communications, IEEE Transactions on, vol. 59, no. 3, pp. 823–832, 2011.
[9] E. Basar, U. Aygolu, E. Panayirci, and H. V. Poor, “Performance of spatial modulation in the presence of
channel estimation errors,” Communications Letters, IEEE, vol. 16, no. 2, pp. 176–179, 2012.
[10] J. Wang, S. Jia, and J. Song, “Generalised spatial modulation system with multiple
active transmit antennas and low complexity detection scheme,” Wireless Communications, IEEE Transactions
on, vol. 11, no. 4, pp. 1605–1615, 2012.
[11] M. D. Renzo and H. Haas, “Bit error probability of sm-mimo over generalized
fading channels,” Vehicular Technology, IEEE Transactions on, vol. 61, no. 3, pp. 1124–1144, 2012.
[12] L. G. Ordónez, D. P. Palomar, and J. R. Fonollosa, “On the diversity, multiplexing, and array gain tradeoff
in mimo channels,” in Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on, pp.
2183–2187, IEEE, 2010.
[13] D. Tse and P. Viswanath, Fundamentals of wireless communication. Cambridge university press, 2005.
[14] H. Rad, S. Gazor, and K. Shahtalebi, “Spatial-temporal-frequency decomposition for 3d mimo
microcellular environments,” in Electrical and Computer Engineering, 2004. Canadian Conference on, vol. 3, pp.
1229–1232, IEEE, 2004

50. [15] J. Mietzner, R. Schober, L. Lampe, W. H. Gerstacker, and P. A. Hoeher, “Multipleantenna techniques for
wireless communications-a comprehensive literature survey,” Communications Surveys & Tutorials, IEEE, vol. 11,
no. 2, pp. 87–105, 2009.
[16] J. Proakis and M. Salehi, Digital Communications. McGraw-Hill higher education, McGraw-Hill Education,
[17] J. Abouei, “Wireless communication,” tech. rep., 2011.
[18] A. Goldsmith, Wireless communications. Cambridge university press, 2005. ,
[19]T. Duman and A. Ghrayeb, Coding for MIMO Communication Systems. Wiley, 2008.
[20] V. Tarokh, N. Seshadri, and A. R. Calderbank, “Space-time codes for high data rate wireless
communication: Performance criterion and code construction,” Information Theory, IEEE Transactions
on, vol. 44, no. 2, pp. 744–765, 1998.
[21] M. D. Renzo, H. Haas, and P. M. Grant, “Spatial modulation for multiple-antenna wireless systems:
a survey,” Communications Magazine, IEEE, vol. 49, no. 12,pp. 182–191, 2011.
[22]S. Song, Y. Yang, Q. Xionq, K. Xie, B.-J. Jeong, and B. Jiao, “A channel hopping
technique i: Theoretical studies on band efficiency and capacity,” in Communications, Circuits and
Systems, 2004. ICCCAS 2004. 2004 International Conference
on, vol. 1, pp. 229–233, IEEE, 2004.