Orthogonal frequency-division multiplexing radar signal design with optimised ambiguity function and low peak-to-average power ratio

2009 ◽  
Vol 3 (2) ◽  
pp. 122 ◽  
Author(s):  
M.A. Sebt ◽  
A. Sheikhi ◽  
M.M. Nayebi
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Ambiguity Function ◽  
Radar Signal ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Signal Design ◽  
Frequency Division

scholarly journals Advantages of Spectrally Efficient Frequency Division Multiplexing Over Orthogonal Frequency Division Multiplexing

2020 ◽  
Vol 9 (8) ◽  
pp. 238-244
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Frequency Division ◽  
Sphere Decoder ◽  
Symbol Rate ◽  
Transmission Length ◽  
Spectrally Efficient ◽  
The Impact

An analysis on Spectrally Efficient Frequency Division Multiplexing (SEFDM) is contrast with Orthogonal Frequency Division Multiplexing (OFDM) considering the impact on Peak to Average Power Ratio (PAPR) and nonlinearities within fibre. With respect to OFDM the sub-carriers in SEFDM signals are compressed adjacent to each other at a rate of frequency lesser than the symbol rate. At the receiver end we have utilized the Sphere Decoder which is used to recover the data to remunerate the Interference created by the compressed signals (ICI) faced in the system. This research shows the advantages by using SEFDM and evaluates its achievement. PAPR. when compared with OFDM, while effects of non-linear fibres are considered. The use of various formats of modulation going from 4-QAM to 32-QAM, shows that the SEFDM signals have a noteworthy increment in the transmission length with respect to ordinary signals.

scholarly journals AN EFFICIENT METHOD FOR PAPR REDUCTION IN OFDM SYSTEMS WITH REDUCED COMPLEXITY

2013 ◽  
pp. 96-100
Author(s):  
PRITANJALI KUMARI ◽  
US TRIAR
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
High Peak ◽  
Papr Reduction ◽  
Power Calculation ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Frequency Division ◽  
Ofdm Systems ◽  
Reduced Complexity

Orthogonal Frequency Division Multiplexing (OFDM), widely used in digital wireless communication, has a major drawback of high Peak to Average Power Ratio (PAPR). A reduced complexity partial transmit sequence (PTS) scheme has been proposed to solve high peak to average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) system. In the proposed PTS scheme, a function is generated by summing the power of time domain samples at time ‘n’ in each sub blocks, known as “Hn”.Only those samples, having Hn greater than or equal to a preset threshold value (αT) are used for peak power calculation during the process of selecting a candidate signal with the lowest PAPR for transmission. As compared to conventional PTS scheme, the proposed scheme achieves almost the same PAPR reduction performance with much lower computational complexity.

scholarly journals A CCM-Based OFDM System with Low PAPR for Sparse Source

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Qinbiao Yang ◽  
Zulin Wang ◽  
Qin Huang
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Coded Modulation ◽  
High Peak ◽  
Frequency Division Multiplexing ◽  
Power Ratio ◽  
Frequency Division ◽  
Ofdm System ◽  
Simulation Results ◽  
Clipping And Filtering

Orthogonal frequency division multiplexing (OFDM) usually suffers high peak-to-average power ratio (PAPR). As shown in this paper, PAPR becomes even severe for sparse source due to many identical nonzero frequency OFDM symbols. Thus, this paper introduces compressive coded modulation (CCM) in order to restrain PAPR by reducing identical nonzero frequency symbols for sparse source. As a result, the proposed CCM-based OFDM system, together with iterative clipping and filtering, can efficiently restrain the high PAPR for sparse source. Simulation results show that it outperforms about 4 dB over the traditional OFDM system when source sparsity is 0.1.

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