Radar Orthogonal Frequency Division Multiplexing Waveforms Agility Processing with Compressive Sensing

2013 ◽  
Vol 416-417 ◽  
pp. 1181-1186
Author(s):  
Feng Xie ◽  
Feng Liu ◽  
Xiao Hui Ye
Keyword(s):  
Compressive Sensing ◽  
Orthogonal Frequency Division Multiplexing ◽  
Matched Filter ◽  
New Method ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Measurement Matrix ◽  
Range Profile ◽  
Ofdm Signals

CS is a very new method that is being evaluated for many applications, in which signals are sparse in some basis/dictionary, e.g. the radar range profile. In this article, we have formulated the range processing with CS and introduced fair comparisons between matched filter and CS with chirps and OFDM signals. Two relevant features have been inspected: waveform bandwidth and measurement matrix.

Some OFDM waveforms for a fully polarimetric weather radar

2012 ◽  
Vol 4 (2) ◽  
pp. 163-169 ◽  
Author(s):  
Piet van Genderen ◽  
Oleg A. Krasnov ◽  
Zongbo Wang ◽  
Recep Firat Tigrek
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Weather Radar ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Cloud Parameters ◽  
Polarimetric Weather Radar ◽  
Ofdm Signals ◽  
Simultaneous Transmission

Retrieval of cloud parameters in weather radar benefits from polarimetric measurements. Most polarimetric radars measure the full backscatter matrix (BSM) using a few alternating polarized sounding signals. Using specially encoded orthogonal frequency division multiplexing (OFDM) signals however, the BSM can be measured in a single simultaneous transmission of two orthogonally polarized signals. Based on a set of parameters for weather radar, the properties of such a signal are explored and its merit as a useful capability is shown.

scholarly journals Pilot Design for Sparse Channel Estimation in Orthogonal Frequency Division Multiplexing Systems

2018 ◽  
Vol 2 ◽  
pp. 60-68 ◽  
Author(s):  
P. Vimala ◽  
G. Yamuna
Keyword(s):  
Channel Estimation ◽  
Compressive Sensing ◽  
Fading Channel ◽  
Orthogonal Frequency Division Multiplexing ◽  
Wide Band ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Ofdm Systems ◽  
Sparse Channel Estimation ◽  
Sparse Channel

Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band wireless communication systems. Coherent OFDM systems achieve its advantages over a multipath fading channel, if channel impulse response is estimated precisely at the receiver. Pilot-aided channel estimation in wide band OFDM systems adopts the recently explored compressive sensing technique to decrease the transmission overhead of pilot subcarriers, since it exploits the inherent sparsity of the wireless fading channel. The accuracy of compressive sensing techniques in sparse channel estimation is based on the location of pilots among OFDM subcarriers. A sufficient condition for the optimal pilot selection from Sylow subgroups is derived. A Sylow subgroup does not exist for most practical OFDM systems. Therefore, a deterministic pilot search algorithm is described to select pilot locations based on minimizing coherence, along with minimum variance. Simulation results reveal the effectiveness of the proposed algorithm in terms of bit error rate, compared to the existing solutions.

Evaluating and Reducing the Envelope Fluctuations of OFDM Signals Based on Distortion Prediction

Frequenz ◽  
2017 ◽  
Vol 71 (1-2) ◽  
pp. 73-81
Author(s):  
Xiangyin Zhang ◽  
Xiaodong Zhu ◽  
Youxi Tang
Keyword(s):  
System Performance ◽  
Orthogonal Frequency Division Multiplexing ◽  
Nonlinear Distortion ◽  
Average Power ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Frequency Division ◽  
Selective Mapping ◽  
Mapping Scheme ◽  
Ofdm Signals

Abstract Orthogonal frequency division multiplexing (OFDM) signals with large envelope fluctuations are prone to be affected by power amplifier (PA), resulting in degradation of system performance. Peak-to-average power ratio (PAPR) and cubic metric (CM) are commonly used as the reduction criteria of envelope fluctuations of OFDM signals. However, our analysis shows that minimizing the PAPR or CM does not necessarily mean the optimization of system performance, since both metrics are inadequate to quantify the distortion in nonlinear OFDM transmission. In this paper, we fully discuss the effects of PA nonlinearity on OFDM signals and propose a new metric called distortion component metric (DCM), which is closely related to the nonlinear distortion caused by the PA. We compare the system performance when several metrics are respectively used as the reduction criterion for the selective mapping scheme. It is shown that in the presence of memoryless or memory PA, the usage of DCM can provide better inband and out-of-band performance than PAPR and CM.

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