A low-complexity multiple signal representation scheme in downlink OFDM-CDMA

2009 ◽  
Vol 52 (12) ◽  
pp. 2433-2444 ◽  
Author(s):  
LiLin Dan ◽  
Yue Xiao ◽  
Peng Cheng ◽  
Gang Wu ◽  
ShaoQian Li
Keyword(s):  
Low Complexity ◽  
Signal Representation ◽  
Multiple Signal ◽  
Representation Scheme

scholarly journals Low-complexity multiple-signal joint decoding for overlapped x domain multiplexing signalling

2018 ◽  
Vol 12 (11) ◽  
pp. 1273-1282 ◽  
Author(s):  
Peng Lin ◽  
Yafeng Wang ◽  
Daoben Li
Keyword(s):  
Low Complexity ◽  
Joint Decoding ◽  
Multiple Signal

scholarly journals On the PAR Reduction of OFDM Signals Using Multiple Signal Representation

2004 ◽  
Vol 8 (7) ◽  
pp. 425-427 ◽  
Author(s):  
A.D.S. Jayalath ◽  
C.R.N. Athaudage
Keyword(s):  
Signal Representation ◽  
Multiple Signal ◽  
Ofdm Signals

Multiple signal representation simulation of photonic devices, systems, and networks

2000 ◽  
Vol 6 (2) ◽  
pp. 282-296 ◽  
Author(s):  
A. Lowery ◽  
O. Lenzmann ◽  
I. Koltchanov ◽  
R. Moosburger ◽  
R. Freund ◽  
...  
Keyword(s):  
Photonic Devices ◽  
Signal Representation ◽  
Multiple Signal

scholarly journals Signal compression and reconstruction using multiple bases representation

1988 ◽  
Author(s):  
◽  
Félix G. Safar
Keyword(s):  
Projection Operator ◽  
Side Information ◽  
Signal Reconstruction ◽  
A Priori ◽  
Basis Sets ◽  
Signal Representation ◽  
Reconstruction Methods ◽  
Data Rates ◽  
Noise Tolerant ◽  
Representation Scheme

The problem of efficient signal communication at low data rates involves, in general, the encoding of the source for maximum data compression at the transmitter end, and the reconstruction using the received information and all the available a priori or side information at the receiver end. In this thesis, we propose an adaptive signal representation scheme, based on the use of multiple orthogonal basis sets, that exhibits very good potential in both the source encoding and the signal reconstruction problems. This representation leads naturally to the splitting of the signal mto additive components, each of which has a simpler description than the original process. In addition, it exhibits a structure similar to that of codebook based coding. As a result, a very compact signal representation can be achieved. A splitting procedure called recursive residual projection is proposed, and its performance evaluated for the separation of imagelike signals into basis-defined "edge" and "texture" components. The coding of these components leads to lower rates than those for transform coding methods. In reconstruction, the representation can be considered as a well-behaved constraint. This allowed for the development of the corresponding unique projection operator, with application to general iterative reconstruction methods. In particular, we also proposed a noise tolerant version of the operator, a so-called soft projection operator, capable of achieving convergence under noisy measurement conditions. Computer simulations in the representation, coding, and reconstruction applications corroborate the usefulness of this proposed representation.

scholarly journals PAPR Reduction of a Universal Filtered Multicarrier Using a Selective Mapping Scheme

2019 ◽  
Vol 54 (5) ◽  
Author(s):  
Farooq Sijal Shawqi ◽  
Ahmed Talaat Hammoodia ◽  
Lukman Audah ◽  
Ammar Ahmed Falih
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Communication Systems ◽  
Average Power ◽  
Mapping Method ◽  
Signal Representation ◽  
Multiple Signal ◽  
Representation Technique ◽  
Selective Mapping ◽  
Papr Performance

The new generation of wireless communication systems involves several different technologies. The universal filtered multicarrier (UFMC) is one of these technologies. UFMC supports various numerology designs; however, the high peak to average power ratio (PAPR) is a major limitation faced by designers. Therefore, diverse approaches have been introduced, such as amplitude clipping, tone reservation, and active constellation extension, to mitigate the PAPR problem. These algorithms produce significant degradation in terms of bit error rate or power consumption. Another proposed solution is multiple signal representation schemes, which have promised to conserve bit error rate performance without power waste. Selected mapping is a multiple signal representation technique that reduces the PAPR without bit error degradation. This paper focuses on integrating the selected mapping method with the UFMC. Simulation results show that the integrated algorithm presents better PAPR performance: the PAPR was reduced by 2.1 dB and 1 dB for UFMC and CP-OFDM, respectively, without bit error rate degradation.

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