Advisor : Tzi-Dar Chiueh Student : Jui-Ping Lien Progress Report of OFDM-based Agile Baseband Transceiver for Spectrum Pooling Wireless Systems Advisor : Tzi-Dar Chiueh Student : Jui-Ping Lien Date : Nov 29th , 2004

Outline Overview of Spectrum Pooling System Transmit Power Spectrum Feature Specification Transmit Power Spectrum Two approaches of reducing signal sidelobe Simulation Result SISO perfect channel estimation in AWGN Conclusion Future Work Reference

Overview of Spectrum Pooling System

Flexible Spectrum Coexist with LU in the same frequency band without interfering LU. Use idle bands which LU does not use. Band Allocation: totally 15 combinations LU RU LU LU LU RU RU LU sub-band No. #1 #2 #3 #4 LU/RU: licensed/rental user

Adaptive Transmission Pros Enhance the capacity Cons Increase the complexity Assume transmitter knows CSI (channel state information) Adaptive transmission using water-filling techniques [3] Power allocation Bit loading (adaptive modulation) SBLA ( Simple Blockwise Loading Algorithm ) [1]

MIMO Scheme 2x2 MIMO: enhance higher data rate VBLAST SVD-based (Singular Value Decomposition) Pros: support adaptive modulation Cons: Assume transmitter knows CSI Channel matrix Transmit signal Received signal [2] [3]

System specifications FFT size 256 Bandwidth 100MHz (use 80MHz actually) Sampling rate 80MHz (4 times faster than 802.11a) Sub-carrier spacing 312.5KHz (=80 MHz/256) FFT period 3.2us (=1/312.5 KHz) Guard interval duration 0.8us OFDM symbol duration 4.0us (=3.2+0.8 us) Sub-carrier in use variable Modulation type BPSK, QPSK, 16QAM, 64QAM Operating frequency Upper UNII bands

Transmit Power Spectrum Analysis

Transmitter Block Diagram CSI

Transmit Spectrum Mask 802.11a spec has transmit spectrum mask Two approaches to reduce sidelobes of transmitted waveform Time domain windowing Frequency domain filtering RU #1234 RU #13

Time domain windowing Raised cosine windowing Larger roll-off factor improves the spectrum, at the cost of decreased delay spread tolerance.

Frequency domain filtering (1/2) Filter Requirement Interpolator filer Band-limited filter: reduce out-of-band spectrum Reconfigurable filter Complex filter: for asymmetric spectrum case

Frequency domain filtering (2/2) Item Elliptic Filter (IIR) Filter Coefficient Case 1 N=6 Wp=19/80 Ws = 23/80 Rp=0.1 dB Rs=40 dB RU#23 2 RU#1, RU#2, RU#12 3 RU#3, RU#4, RU#34 4 N=7 Wp=29/80 Ws = 33/80 Rp=0.1dB RU#13, RU#123 5 complex conjugate of item4 RU#24. RU#234 6 Wp=39/80 Ws = 43/80 Rp=0.1, Rs=40 RU#14, RU#124, RU#134, RU#1234

Simulation Transmit Spectrum -- 1 sub-band (1/3) β=0, 1/160, 1/40 β=0, 1/160, 1/40

Simulation Transmit Spectrum -- 2 sub-bands (2/3)

Simulation Transmit Spectrum -- 3 or 4 sub-bands (3/3)

Simulation of Perfect Channel Estimation in AWGN

Receiver Architecture Inner receiver

SISO Perfect Channel Estimation in AWGN Channel Simulation Environment More available sub-band → higher data rate → higher BER @ same SNR per OFDM symbol RU#1 RU#1234

Simulation Result (1/2) 16 QAM of 15 cases 4 modulation types of RU#1234

Simulation Result (2/2)

Conclusion Features of SP system has been introduced. Since transmit power spectrum should achieve the mask requirement, we use both techniques time domain raised cosine windowing (overlap 1 pt ) frequency domain filtering SISO perfect channel estimation in AWGN has been simulated.

Future Work Extend SISO to MIMO scheme Build up timing recovery block of receiver Support adaptive modulation System modification according to final specification

Reference [1] Rainer Gr¨unheid, Edgar Bolinth, and Hermann Rohling, “A Blockwise Loading Algorithm for the Adaptive Modulation Technique in OFDM Systems,” in IEEE VTC-2001, Atlantic City, USA, October 2001. [2] http://www.tgnsync.org/techdocs/tgnsync-proposal-technical-specification.pdf [3] Juha Heikala, John Terry, “OFDM Wireless LANs: A Theoretical and Practical Guide” 2002