7.1 Conclusion
In this thesis, we first discussed the synchronization problems of the IEEE 802.16e OFDM TDD UL system, modified to fixed-point version, and implemented them on TI’s C6416 digital signal processor. Second, we also discussed the synchronization problems of the OFDMA TDD DL system, which has different issues from OFDM.
In the OFDM system, we designed a new algorithm to estimate symbol timing by taking advantage of the time-domain structure of the preamble. This algorithm had a well per-formance (more than 80% correction rate) even in the 60 km/h multipath Rayleigh fading channel. A CP correlation in [21] was used to synchronize fractional CFO of each symbol, and we averaged each estimated values for more accurate results. After averaging, more than 99% of synchronized results can reach the requirement of the specification. The inte-ger CFO and symbol sampling frequency offset synchronization could be ignored. Next, we modified the whole system to fixed-point version, and used some optimization techniques to accelerate each block as fast as we can on TI’s DSP. The fixed-point modification degraded the performance of original methods in a range we can accept, and after optimization, every block could achieve real-time rate.
In the OFDMA system, SFO, integer CFO, and preamble index identification were three problems needed to be considered. Since an SS does not know the exact subcarrier values of the preamble, we just viewed a preamble symbol as a regular symbol and estimated timing and fractional CFO by CP correlation in [21]. Like in the OFDM system, we estimated symbol timing offset only by the preamble, but estimated fractional CFO by averaging the estimated values of each symbol for more accuracy. After averaging, more than 99%
of results can reach the requirement of the specification if the mobile speed wa less than 240 km/h. We developed a method to estimate symbol timing offset more accurately by observing consecutive symbols, this can help to improve the performance of preamble index identification. The integer CFO estimation and preamble index identification were done together. First we estimated the possible integer CFO, then we used this estimated value and its corresponding carrier-set to find which index it really was. If the SNR was reasonable, both error rates of these two synchronization methods were less than 1% even the mobile speed was high. If we took imperfect symbol timing estimation into consideration, the error rate of either the integer CFO estimation ot the preamble index identification was about 1%
when using the fine timing estimation.
7.2 Future Work
There are several possible extensions for our research:
• Take the effect caused by sampling frequency offset into consideration. This is for a more practical simulation.
• Consider to deal with SFO synchronization in addition, especially in the high mobile speed environment, this can help the performance of BER.
• Run fixed-point simulation for the OFDMA system. We must change it to fixed-point
version so that we can run the system in the hardware.
• Try to use the quasi-periodic time-domain structure of the preamble to estimation symbol timing offset.
• Analyze the effects of different length of guard interval. The guard interval length may effect the performance of fractional CFO and symbol timing.
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