B3G and MIMO MC-CDMA

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B3G and MIMO MC-CDMA

Speaker : Pei-Yun Tsai

Advisor : Tzi-Dar Chiueh

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Outline

• Beyond 3G

– Evolution – Main Features – Possible Techniques

• MIMO MC-CDMA

– From SISO to MIMO – Synchronization – Channel estimation – MIMO decoding

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Beyond 3G

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Evolution of Mobile Systems

[1]

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Main Features of B3G

• Frequency efficiency up to 10 b/s/Hz [2]

• Flexible radio resource management [2]

– Enlarge the coverage

– Improve system efficiency

• Supporting IPv6 multimedia services with [2]

– Low transmission power (10dB lower than 3G)

– Eb/N0 less than 3dB at bit error rate of 10-6 for 100 Mb/s.

• Supporting vehicular speed of 250 km/hr [2]

• Entirely packet-switch services [3]

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Possible Techniques –

Radio Transmission

• Modulation [2] – OFDM

– Robustness against frequency-selective fading channels in wide b andwidth

– Efficient spectrum utilization

– Flexibility in subcarrier allocation – Adaptability in subcarrier modulation

• In 3GPP [4],

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Possible Techniques –

Radio Transmission

• Multiple access scheme [5] – CDMA

– Greater coverage with fewer cell sites – Better frequency reuse

– Higher capacity

• In IMT-2000 family, four out

of five systems use CDMA

techniques.

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Possible Techniques –

Radio Transmission

• Advanced detection techniques [6]

– Multiuser detection (MUD) techniques

• MAI • Near-far effect – Linear receiver • MMSE – Interference canceller (Widely considered) • Parallel IC (PIC) • Successive IC (SIC) • Selective PIC (SPIC)

– Turbo MUD – Adaptive detector Received Signal Combining Informative Bit Decision > Threshold Reliable Signal Cancellation Combining Informative Bit Decision

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Possible Techniques –

Radio Transmission

• MIMO techniques [8]

– Providing spatial diversity

• STBC

– Achieve better QoS for average data rate

• STTC

– High complexity

– Increase frequency efficiency

• BLAST

– The number of receive antennas is greater than or equal to the number of independent transmit signals.

– Poor detection performance over spatially correlated channel.

– Exploit knowledge of channel to provide capacity gain

• SVD

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Possible Techniques –

Radio Transmission

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Possible Techniques –

Link Layer

• Adaptive modulation and coding techniques (AMC) [6]

– Adapt transmission parameters to take advantage of channel conditions.

– Increase spectral efficiency.

– Also power level, spreading factors, signal bandwidth, and etc. can be adjusted.

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Possible Techniques –

Resource Management

• Radio resource management (RRM)

– Admission control (AC)

• Reject new connection if causing unacceptable degradation

– Power control

• Minimize power consumption

– Scheduling

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MIMO MC-CDMA

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Consideration

• MIMO techniques

– STBC

– V-BLAST

• MIMO decoding

– Noise

– Multiple access interference (MAI)

– Inter antenna interference (IAI)

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MIMO MC-CDMA Receiver

• Synchronization blocks are shared.

• JWLS estimation, channel estimation, and combining

strategies are different from SISO version.

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Hardware Requirement

• Derotator x 2 • FFT x 2 • Channel estimation x 4 • Equalizer (FEQ) x 4 (More complicated) • Despreading x 4

• SRAM for channel Respons e x 4

• EQ data delay buffers x 4 • Channel estimates delay buf

fers x4

• Additional data buffers (N) x 2

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JWLS Estimation (1/2)

• Estimation for residual CFO and TFO

– Alternative pilot data are transmitted by antenna 1.

– Simple solution: using pilot data separated by 2 symbols

Antenna 0 Antenna 1 Training symbol 0 Training symbol 1 Data symbol 0 Data symbol 1 AWGN ICI H A H A Z_k_,_i  _k ₀₀_,_k  _k ₁₀_,_k   AWGN ICI e H A H A Z N k N j k k k k i k T       ) ( 2 2 , 10 , 00 2 , ( )    ... ) | | | (| | | ( ) 2 2 2 2 2 * _ _  _  k N N j T e H H A Z Z    Data symbol 2

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JWLS Estimation (2/2)

• Performance can be improved in the MIMO receiver due

to increase of SINR.

... ) | | | (| | | ( ) 2 2 2 , 10 2 , 00 2 * , 2 ,      k N N j k k k i k i k T e H H A Z Z   

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Channel Estimation

• Same performance as in the SISO cases at the same

transmitted power.

– LS channel estimation

– Frequency-domain channel interpolation

0 , 10 1 00 0 0 ,i k k k k k i k A H A H v Z    1 , 11 1 01 0 1 ,i _k _k k k k i k A H A H v Z    0 0 1 , 0 , 00 0 0 1 , 0 , 00 ˆ k i k i k i k i k k v v H Z Z H        k k k k k k Z_A H _Av Hˆ    0 1 , 10 1 00 0 0 1 ,i  k k  k k  k i k A H A H v Z 1 1 , 11 1 01 0 1 1 ,i  _k _k  k k  k i k A H A H v Z MIMO SISO k k k k A H v Z  

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Review of SUD in SISO MC-CDMA

• Single user detection [9]

– MRC : maximize SNR

– EGC : no optimization

– ORC : reduce MAI

– MMSEC (per subcarrier): reduce MAI and noise

– TORC : combine EGC and ORC

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MIMO Processing

- STBC (1/2)

• Consider SUD

– Apply TORC to reduce MAI, inter-antenna interference (IAI), and noise 0 , , 10 , , 00 , 0 , k i u u k k u l L u u k k u l i k c H d c H d v Z 







_  1 1 , * , 10 , * , 00 , 0 1 ,   



 



 k i u u k k u l u u k k u l L i k c H d c H d v Z

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MIMO Processing

- STBC (2/2)

• Apply MRC.

• Consider orthogonality restoring to reduce MAI.

• Avoid noise enhancement like TORC.

term noise d c H H Z H Z H W u u k u l k k i k k i k k i k0,  ( 00)* 0,  10( 0, 1)*  (| 00 |2 | 01 |2)



, ,  term noise d c c W c H H d u u k u l k k i k k _k _k k l    



₀₀ ₂ ₀₁ ₂ ₀_, 0_,



₀_,



_, _, , 0 ) | | | (| 1 ˆ G_k              threshold H H H H threshold H H H H G k k k k k k k 2 01 2 00 2 01 2 00 2 01 2 00 2 01 2 00 | | | | ) | | | (| 1 | | | | | | | | 1

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Conclusion and Future Work

• The current status of B3G is introduced.

– Possible features and techniques are discussed.

• Our MIMO MC-CDMA is examined.

– Consider the hardware requirement, the synchronization block the channel estimation block and MIMO decoding.

• Future work

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Reference

[1] B. Li and et al., ’’Recent advances on TD-SCDMA in China,’’ IEEE Communications Magazine, vol. 1, pp. 30-37, Jan. 2005.

[2] P. Zhang and e. al., ’’A vision from the future: beyond 3G TDD,’’ IEEE Communications Magazine, vol. 1, pp. 38-44. Jan. 2005.

[3] http://users.ece.gatech.edu/~jxie/4G/

[4] 3GPP, Technical Specification Group Radio Access Network, Feasibility study for orthogoanl frequency di vision multiplexing (OFDM) for UTRAN Enhancement, TR 25.892, V6.0.0 (2004-06).

[5] A. Jamalipour and et al., ’’ A tutorial on multiple access technologies for beyond 3G mobile networks,’’ IEEE Communications Magazine, vol. 2, pp.110-117, Feb. 2005.

[6] R. Fantacci and et al., ’’Perspectives for present and future CDMA-based communications systems,’’ IEE E Communications Magazine, vol. 2, pp. 95-100, Feb. 2005.

[7] K. Zheng and et al.,’’TD-CDM-OFDM: evolution of TD-SCDMA toward 4G,’’IEEE Communications Magazine , vol. 1, pp. 40-52, Jan. 2005.

[8] H. Yang,’’A road to future broadband wireless access: MIMO-OFDM-based air interface,’’IEEE Communic ations Magazine, vol. 1, pp. 53-60, Jan. 2005.

[9] R. Le Gouable and M. Helard,’’Performance of single and multi-user detection techniques for a MC-CDM A system over channel model used for HIPERLAN2,’’ IEEE International Symposium on2000 IEEE Sixth Sp read Spectrum Techniques and Applications, Parsippany,New Jersey, Sep. 2000, pp. 718-722.