Research On Synchronization And CFO, Channel Estimation In OFDM

It's said that in the near future, the number of wide band network users in China will be the most in the world surpassing that in America. And the most used technology by Chinese wide band network subscribers is DSL which stands for Digital Subscriber Loop. Why DSL can be called a wide band technology is because it exploits OFDM which represents Orthogonal Frequency Division Multiplexing. OFDM can largely improve the throughput of the communication system which employs it. The underlying principle is that OFDM can make information transmitted in different sub-channels and the frequency of transmitted signals in different sub-channels just overlap. So we can transmit much more information just through the same bandwidth as the frequencies that don't overlap.The advantage of OFDM described above gives OFDM widely usage through the future 4th Generation mobile communication network to the conceptual Ultra Wide-Band communication architecture. We can say that the future wideband wireless digital communication will heavily rely on the OFDM as the multiplexing base. Actually OFDM is one of the Multi-Carrier communication systems, so as to the traditional communications like CDMA and TDMA, we can also modify them to be MC-CDMA and MC-TDMA, much alike OFDM system.Different carriers in OFDM are orthogonal. So how to keep the orthogonality is the prominent issue of OFDM. The interference which collapse the orthogonality is called ICI, InterChannel Interference. It is caused by CFO (Carrier Frequency Offsets) between the transmitter oscillator and the receiver counterpart. OFDM must estimatethe CFO and compensate it.As a common issue in every wireless communication system, channel estimation is also very important in OFDM. Because of GI/CP ( Guard Interval/Cyclic Prefix), the OFDM channel can be mathematically modeled as a Toeplitz matrix.Before estimating and compensating the CFO, we must first equalize the received signal to remove the effect of the channel. Luckily, since OFDM channel's Toeplitz property, the effect of OFDM channel, with OFDM signals in GI/CP structure and under IDFT/DFT modulation/demodulation, will become a multiplication of a diagonal channel matrix. Then just in a simple way we can get the channel estimation. In detail, by multiplying the received training sequence (or preamble) with the inverse of training sequence (or preamble), we can remove the effect of the transmitted signal information so as to separate the information of the channel.After we get the channel estimation and the received signals are equalized, we can estimate the CFO and compensate it. The traditional CFO estimation utilizes the correlativity between the training sequences or preambles to separate the CFO. But in this paper, we introduce another CFO estimation method which is a subspace algorithm. In detail, the existence of the virtual channels (which means the number of IDFT/DFT channels is larger than that of OFDM samples) gives birth to the orthogonal subspace of the channel matrix. Exploiting the orthogonality, we can create special cost functions and solve the optimization problem minimizing/maximizing the cost functions.But unfortunately the optimization problem minimizing/maximizing the cost function is a nonlinear least squared problem. The paper reforms the parameters in the cost function so that the nonlinear problem becomes a linear least squared problem. The reformation largely simplifies computation.Another emphasis of this paper is MIMO-OFDM. MIMO is another prosperous technology. Because as same as OFDM it hugely improve the capacity of the channel, what's different with OFDM is that it utilizes the multi-path signals introduced by the multi-input and multi-output channel. So MIMO is a kind of space multiplexing butOFDM, frequency multiplexing.The characteristics of MIMO decide that MIMO-OFDM is for wireless communication systems. And the complexity of the wireless channel determines channel estimation is the most important theme in MIMO-OFDM. This paper introduces several channel estimation methods including blind channel estimation algorithms. And the future research of the author in this field will focus on it too.