Orthogonal frequency division multiplexing (OFDM) is a technique that will prevail in the next-generation wireless Communication. Channel estimation is one of the key challenges in OFDM, since high-resolution channel estimation can significantly improve the equalization at the receiver and consequently enhance the Communication performances. In this paper, we propose a system with an asymmetric digital-to-analog converter/analog-to-digital converter (DAC/ADC) pair and formulate OFDM channel estimation as a compressive sensing problem. By skillfully designing pilots and taking advantages of the sparsity of the channel impulse response, the proposed system realizes high-resolution channel estimation at a low cost. The pilot design, the use of a high-speed DAC and a regular-speed ADC, and the estimation algorithm tailored for channel estimation distinguish the proposed approach from the existing estimation approaches. We theoretically show that in the proposed system, a $N$-resolution channel can be faithfully obtained with an ADC speed at $M=O(S^{2}log(N/S))$, where $N$ is also the DAC speed and $S$ is the channel impulse response sparsity. Since $S$ is small and increasing the DAC speed to $N>M$ is relatively cheap, we obtain a high-resolution channel at a low cost. We also present a novel estimator that is both faster and more accurate than the typical $ell_{1}$ minimization. In the numerical experiments, we simulated various numbers of multipaths and different SNRs and let the transmitter DAC run at 16 times-
the speed of the receiver ADC for estimating channels at the 16$times$ resolution. While there is no similar approaches (for asymmetric DAC/ADC pairs) to compare with, we derive the Cramér–Rao lower bound.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Compressive Color Pattern Detection Using Partial Orthogonal Circulant Sensing Matrix ABSTRACT: To get acceptable signal reconstruction quality with compressive sensing, it's important to create a sensing matrix
PROJECT TITLE :Structure-Aware Bayesian Compressive Sensing for Frequency-Hopping Spectrum Estimation With Missing Observations - 2018ABSTRACT:During this Project, we tend to address the matter of spectrum estimation of multiple
PROJECT TITLE :Efficient Compressive Channel Estimation for Millimeter-Wave Large-Scale Antenna Systems - 2018ABSTRACT:Giant-scale antenna systems are thought of as a viable technology to catch up on huge path loss in millimeter-wave
PROJECT TITLE :Frequency-Domain Compressive Channel Estimation for Frequency-Selective Hybrid Millimeter Wave MIMO Systems - 2018ABSTRACT:Channel estimation is helpful in millimeter wave (mm-wave) MIMO communication systems. Channel
PROJECT TITLE :Compressive Channel Estimation and Multi-User Detection in C-RAN With Low-Complexity Methods - 2018ABSTRACT:This Project considers the channel estimation (CE) and multi-user detection (MUD) problems in cloud radio

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry