Architectural Exploration of Blind CFO Estimation in OFDM Systems for Prototyping on a Reconfigurable Platform

This paper presents two architectures for prototyping an advanced carrier frequency offset (CFO) estimation technique for OFDM systems on field programmable gate array (FPGA). The parallel stream architecture (PSA) exploits the FPGA parallelism while the multiplexed stream architecture (MSA) employs multiplexing for more efficient hardware implementation. The dual-mode of operation for the proposed architectures has been proposed to achieve optimum performance depending on channel conditions. The proposed architectures with different implementation alternatives have been simulated and verified for FPGA implementation using the Xilinx’s DSP design flow. The estimation accuracy and the resource utilization for the proposed architectures have been evaluated. The prototyping results showed that MSA allows for more resource efficient implementation, where a single FFT core can be shared between parallel streams compared with PSA

Blind Estimation of Carrier Frequency Offset for OFDM Systems using Maximum Likelihood Technique

A Multicarrier Communication system such as an Orthogonal Frequency Division Multiplexing OFDM has been shown to be an impressive approach to combat multipath fading in wireless communications. OFDM is a modulation scheme that allows digital data to be efficiently and reliably transmitted over a radio channel, even in multipath environments. OFDM transmits data by using a large number of narrow bandwidth carriers. These carriers are regularly spaced in frequency, forming a block of spectrum. The frequency spacing and time synchronization of the carriers is chosen in such a way that the carriers are orthogonal, meaning that they do not cause interference to each other. In spite of the success and effectiveness of the OFDM systems, it suffers from a well-known drawback of high sensitivity to Carrier Frequency Offset (CFO). The presence of the CFO in the received carrier will lose orthogonality among the carriers and causes a reduction of desired signal amplitude in the output decision variable and introduces Inter Carrier Interference (ICI). It then brings up an increase of Bit Error Rate (BER). This makes the problem of estimating the CFO an attractive and necessary research problem. In this thesis Blind Modified ML CFO estimation technique based on data symbol repetition is discussed to estimate the offset parameter