scholarly journals Carrier Diversity Incorporation to Low-Complexity Near-ML Detection for Multicarrier Systems over V2V Radio Channel

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6067
Author(s):  
Jose Alberto Del Puerto-Flores ◽  
Fernando Peña-Campos ◽  
Ramón Parra-Michel ◽  
Carolina Del-Valle-Soto
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Radio Channel ◽  
Computational Cost ◽  
Low Complexity ◽  
Data Detection ◽  
Frequency Diversity ◽  
Ofdm Systems ◽  
Iterative Receivers ◽  
Multicarrier Systems ◽  
Non Linear

Inter-carrier interference (ICI) in vehicle to vehicle (V2V) orthogonal frequency division multiplexing (OFDM) systems is a common problem that makes the process of detecting data a demanding task. Mitigation of the ICI in V2V systems has been addressed with linear and non-linear iterative receivers in the past; however, the former requires a high number of iterations to achieve good performance, while the latter does not exploit the channel’s frequency diversity. In this paper, a transmission and reception scheme for low complexity data detection in doubly selective highly time varying channels is proposed. The technique couples the discrete Fourier transform spreading with non-linear detection in order to collect the available channel frequency diversity and successfully achieving performance close to the optimal maximum likelihood (ML) detector. When compared with the iterative LMMSE detection, the proposed system achieves a higher performance in terms of bit error rate (BER), reducing the computational cost by a third-part when using 48 subcarriers, while in an OFDM system with 512 subcarriers, the computational cost is reduced by two orders of magnitude.

scholarly journals OFDM PAPR Reduction via Time-Domain Scattered Sampling and Hybrid Batch Training of Synchronous Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1708
Author(s):  
Ahmad Gendia ◽  
Osamu Muta
Keyword(s):  
Neural Network ◽  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Computational Cost ◽  
Low Complexity ◽  
Critical Issue ◽  
Papr Reduction ◽  
Ofdm Systems ◽  
Comparable Performance ◽  
Increasing Demand

Peak-to-average power ratio (PAPR) reduction in multiplexed signals in orthogonal frequency division multiplexing (OFDM) systems has been a long-standing critical issue. Clipping and filtering (CF) techniques offer good performance in terms of PAPR reduction at the expense of a relatively high computational cost that is inherent in the repeated application of fast Fourier transform (FFT) operations. The ever-increasing demand for low-latency operation calls for the development of low-complexity novel solutions to the PAPR problem. To address this issue while providing an enhanced PAPR reduction performance, we propose a synchronous neural network (NN)-based solution to achieve PAPR reduction performance exceeding the limits of conventional CF schemes with lower computational complexity. The proposed scheme trains a neural network module using hybrid collections of samples from multiple OFDM symbols to arrive at a signal mapping with desirable characteristics. The benchmark NN-based approach provides a comparable performance to conventional CF. However, it can underfit or overfit due to its asynchronous nature which leads to increased out-of-band (OoB) radiations, and deteriorating bit error rate (BER) performance for high-order modulations. Simulations’ results demonstrate the effectiveness of the proposed scheme in terms of the achieved cubic metric (CM), BER, and OoB emissions.

scholarly journals A low complexity partial transmit sequence approach based on hybrid segmentation scheme

2020 ◽  
Vol 9 (6) ◽  
pp. 2371-2379
Author(s):  
Ali Hussein Fadel ◽  
Hasanain H. Razzaq ◽  
Salama A. Mostafa
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Low Complexity ◽  
Frequency Division ◽  
Ofdm Systems ◽  
Wave Shape ◽  
Data Sequence ◽  
Practical Applications ◽  
Phase Rotation ◽  
Hybrid Segmentation

The partial transmit sequences (PTS) is regarded as a promising scheme for inhibiting ‎the high peak-to-average power ratio (PAPR) problem in the orthogonal frequency division ‎multiplexing (OFDM) systems. The PTS scheme relies on partitioning the ‎data sequence into subsets and weighting these subsets by a group of the phase rotation ‎factors. Although the PTS can efficiently reduce the high PAPR value, a great ‎computational complexity (CC) level restricts the utilization of the PTS scheme in practical ‎applications. In PTS, there are three common types of segmentation schemes; ‎interleaving (IL-PTS), pseudo-random (PR-PTS), and adjacent (Ad-PTS) schemes. This ‎paper presents a new algorithm named hybrid pseudo-random and interleaving cosine wave shape ‎‎(H-PRC-PTS) by combining the PR-PTS scheme and the symmetrical ‎interleaving cosine wave shape (S-IL-C-PTS) scheme which was proposed in our previous ‎work. The results indicate that the suggested algorithms can ‎diminish the PAPR value like the PR-PTS scheme, whereas the CC level is reduced significantly.

scholarly journals An Efficient Adaptive Technique with Low Complexity for Reducing PAPR in OFDM-Based Cognitive Radio

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Hefdhallah Sakran ◽  
Omar Nasr ◽  
Mona Shokair
Keyword(s):  
Cognitive Radio ◽  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Low Complexity ◽  
Papr Reduction ◽  
Modulation Scheme ◽  
Ofdm Systems ◽  
Cpu Time ◽  
Reduction Techniques ◽  
Selective Mapping

Cognitive radio (CR) is considered nowadays as a strong candidate solution for the spectrum scarcity problem. On standards level, many cognitive radio standards have chosen Non-Contiguous Orthogonal Frequency Division Multiplexing (NC-OFDM) as their modulation scheme. Similar to OFDM, NC-OFDM suffers from the problem of having a high Peak to Average Power Ratio (PAPR). If not solved, either the transmitted signal will be distorted, which will cause interference to primary (licensed) users, or the effeciency of the power amplifier will be seriously degraded. The effect of the PAPR problem in NC-OFDM based cognitive radio networks is worse than normal OFDM systems. In this paper, we propose enhanced techniques to reduce the PAPR in NC-OFDM systems. We start by showing that combining two standard PAPR reduction techniques (interleaver-based and selective mapping) results in a lower PAPR than using them individually. Then, an “adaptive number of interleavers” will be proposed that achieves the same performance of conventional interleaver-based PAPR reduction while reducing the CPU time by 41.3%. Finally, adaptive joint interleaver with selective mapping is presented, and we show that it gives the same performance as conventional interleaver-based technique, with reduction in CPU time by a factor of 50.1%.

scholarly journals Ciphered BCH Codes for PAPR Reduction in the OFDM in Underwater Acoustic Channels

2022 ◽  
Vol 10 (1) ◽  
pp. 91
Author(s):  
Mohsin Murad ◽  
Imran A. Tasadduq ◽  
Pablo Otero
Keyword(s):  
Secure Communication ◽  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Low Complexity ◽  
Bch Codes ◽  
Papr Reduction ◽  
Ofdm Systems ◽  
Computational Power ◽  
Underwater Acoustic ◽  
Underwater Acoustic Channels

We propose an effective, low complexity and multifaceted scheme for peak-to-average power ratio (PAPR) reduction in the orthogonal frequency division multiplexing (OFDM) system for underwater acoustic (UWA) channels. In UWA OFDM systems, PAPR reduction is a challenging task due to low bandwidth availability along with computational and power limitations. The proposed scheme takes advantage of XOR ciphering and generates ciphered Bose–Chaudhuri–Hocquenghem (BCH) codes that have low PAPR. This scheme is based upon an algorithm that computes several keys offline, such that when the BCH codes are XOR-ciphered with these keys, it lowers the PAPR of BCH-encoded signals. The subsequent low PAPR modified BCH codes produced using the chosen keys are used in transmission. This technique is ideal for UWA systems as it does not require additional computational power at the transceiver during live transmission. The advantage of the proposed scheme is threefold. First, it reduces the PAPR; second, since it uses BCH codes, the bit error rate (BER) of the system improves; and third, a level of encryption is introduced via XOR ciphering, enabling secure communication. Simulations were performed in a realistic UWA channel, and the results demonstrated that the proposed scheme could indeed achieve all three objectives with minimum computational power.

scholarly journals Low Power Consumption Signal Detector Based on Adaptive DFSD in MIMO-OFDM Systems

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 599
Author(s):  
Seong-Joon Shim ◽  
Seung-Jin Choi ◽  
Hyoung-Kyu Song
Keyword(s):  
Power Consumption ◽  
Orthogonal Frequency Division Multiplexing ◽  
Signal To Noise Ratio ◽  
Low Complexity ◽  
Ofdm Systems ◽  
Error Performance ◽  
Detection Scheme ◽  
Signal Detector ◽  
Multiple Input ◽  
Mimo Ofdm

For a low complexity signal detector to reduce the power consumption for multiple input and multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems, the depth-first sphere decoding (DFSD) detection scheme was proposed. However, the DFSD detection scheme still has high complexity in the hardware implementation. The complexity is especially high when the signal-to-noise ratio (SNR) is low. Therefore, this paper proposes an adaptive DFSD detection scheme. The proposed detection scheme arrays nodes, sorting by ascending order of squared Euclidean distance (ED) at the top layer of tree structure. Then, the proposed detection scheme uses the different number of nodes according to thresholds based on channel condition. In the simulation results, the proposed detection scheme has similar error performance and low complexity compared with the conventional DFSD detection scheme. Therefore, the proposed detection scheme reduces the power consumption in the signal detector.

Low-complexity compensation of sampling offset with cross-correlation and early-late gate for OFDM receivers

2020 ◽  
Vol 20 (3) ◽  
pp. 827-837
Author(s):  
Lingfei Zhang ◽  
Jun Ma ◽  
Rongxin Liu ◽  
Zhonglun You ◽  
Tingting Xiang
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Cross Correlation ◽  
Local Area ◽  
Low Complexity ◽  
Large Error ◽  
Ofdm Systems ◽  
Hardware Resource ◽  
Offset Compensation ◽  
The Impact ◽  
Early Late

This paper proposes a method for compensation of sampling offset for orthogonal frequency division multiplexing (OFDM) used in wireless local area networks (WLAN). Sampling offset is a typical transmission interference used in OFDM systems that introduce large error when synchronized data is demodulated. In this regard, an appropriate offset compensation method with a simple structure can be adopted to mitigate the impacts of sampling offset by using cross-correlation and early-late gate compensation methods for OFDM receivers instead of conventional methods that use algorithms with analog and mixed mode loops implementations. When bit error rate (BER) is at 10-3, simulation with the method without sampling offset compensation showed a signal noise rate (SNR) curve of about 25 dB, while the SNR curve of the method with offset compensation as proposed in this paper is about 26 dB. The comparisons show that the proposed system sacrifices performance by 1 dB to realize the benefit of compensating sampling offset. This sacrifice of 1 dB in performance is within the system’s tolerance range. Furthermore, the method overcomes the impact of sampling offset without additional hardware resource in WLAN applications.

A Low Complexity Integer Frequency Offset Estimation Scheme Based on Coherence Phase Bandwidth for OFDM Systems

2013 ◽  
Vol 479-480 ◽  
pp. 878-882
Author(s):  
Youngseok Lee ◽  
Seong Ro Lee ◽  
Seungsoo Yoo ◽  
Jeongyoon Shim ◽  
Jaewoo Lee ◽  
...  
Keyword(s):  
Orthogonal Frequency Division Multiplexing ◽  
Low Complexity ◽  
Frequency Offset ◽  
Frequency Division ◽  
Ofdm Systems ◽  
Frequency Offset Estimation ◽  
Timing Offset ◽  
Estimation Scheme ◽  
Reduced Complexity ◽  
Integer Frequency Offset

In this paper, we propose a low complexity integer frequency offset estimation scheme based on coherence phase bandwidth for orthogonal frequency division multiplexing (OFDM) systems. The proposed scheme overcomes the effect of the timing offset via correlating the local and received OFDM training symbols in a coherence phase bandwidth block unit. Moreover, by utilizing a threshold to determine an interger frequency offset etimate, the proposed scheme need not calculate correlation values for all possible interger frequency offset candidates. From numerical results, it is demonstrated that the proposed scheme can estimate the integer freqeuncy offset with a reduced complexity while minataining the same level of the estimation performance.

scholarly journals Variable Is Better Than Invariable: Sparse VSS-NLMS Algorithms with Application to Adaptive MIMO Channel Estimation

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Guan Gui ◽  
Zhang-xin Chen ◽  
Li Xu ◽  
Qun Wan ◽  
Jiyan Huang ◽  
...  
Keyword(s):  
Channel Estimation ◽  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Computational Cost ◽  
Mimo Channel ◽  
Variable Step Size ◽  
Mean Square ◽  
Ofdm Systems ◽  
Step Size ◽  
Estimation Performance

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparseinvariable step-size normalized least mean square(ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stablesparse variable step-sizeNLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics.

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