Computational Complexity of Iterative Channel Estimation and Decoding Algorithms for GSM Receivers

2005 ◽  
pp. 129-138
Author(s):  
Hailong Cui ◽  
Predrag B. Rapajic
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Decoding Algorithms

An Improved Signal Detection Technique for OFDM System

2013 ◽  
Vol 347-350 ◽  
pp. 3527-3531
Author(s):  
Xiao Hong Wang ◽  
Feng Ming Li
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Signal Detection ◽  
Detection Probability ◽  
Roc Curves ◽  
Detection Technique ◽  
Ofdm System ◽  
Low Snr ◽  
Awgn Channel ◽  
Simulation Results

In this paper a signal detection technique based on pilots which are transmitted for channel estimation in OFDM system is proposed in AWGN channel. We analyse the algorithm based on pilots and derive an improved signal detection technique. The performance is compared in terms of detection probability and ROC curves are given. The simulation results show that the improved detection technique whose computational complexity is not high can increase the precision of the detection probability at low SNR.

scholarly journals Novel Low Complexity BP Decoding Algorithms for Polar Codes: Simplifying on Non-Linear Operations

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 93
Author(s):  
Yuhuan Wang ◽  
Jianguo Li ◽  
Neng Ye ◽  
Xiangyuan Bu
Keyword(s):  
Computational Complexity ◽  
Hardware Implementation ◽  
Low Complexity ◽  
Bp Algorithm ◽  
Polar Codes ◽  
Decoding Algorithm ◽  
Hyperbolic Tangent ◽  
Decoding Algorithms ◽  
Tangent Function ◽  
Non Linear

The parallel nature of the belief propagation (BP) decoding algorithm for polar codes opens up a real possibility of high throughput and low decoding latency during hardware implementation. To address the problem that the BP decoding algorithm introduces high-complexity non-linear operations in the iterative messages update process, this paper proposes to simplify these operations and develops two novel low complexity BP decoding algorithms, namely, exponential BP (Exp-BP) decoding algorithm and quantization function BP (QF-BP) decoding algorithm. The proposed algorithms simplify the compound hyperbolic tangent function by using probability distribution fitting techniques. Specifically, the Exp-BP algorithm simplifies two types of non-linear operations into single non-linear operation using the piece-wise exponential model function, which can approximate the hyperbolic tangent function in the updating formula. The QF-BP algorithm eliminates non-linear operations using the non-uniform quantization in the updating formula, which is effective in reducing computational complexity. According to the simulation results, the proposed algorithms can reduce the computational complexity up to 50% in each iteration with a loss of less than 0.1 dB compared with the BP decoding algorithm, which can facilitate the hardware implementation.

scholarly journals SYMBOL LEVEL DECODING FOR DUO-BINARY TURBO CODES

2017 ◽  
Vol 18 (1) ◽  
pp. 111-131 ◽  
Author(s):  
Yogesh Beeharry ◽  
Tulsi Pawan Fowdur ◽  
Krishnaraj M. S. Soyjaudah
Keyword(s):  
Computational Complexity ◽  
Turbo Codes ◽  
Complexity Analysis ◽  
Error Floor ◽  
Decoding Complexity ◽  
Decoding Algorithms ◽  
Level Information ◽  
Simulation Results

This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.

scholarly journals A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 218 ◽  
Author(s):  
Kifayatullah Bangash ◽  
Imran Khan ◽  
Jaime Lloret ◽  
Antonio Leon
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Least Square ◽  
Mimo Channel ◽  
Finite Sample ◽  
The Impact

Traditional Minimum Mean Square Error (MMSE) detection is widely used in wireless communications, however, it introduces matrix inversion and has a higher computational complexity. For massive Multiple-input Multiple-output (MIMO) systems, this detection complexity is very high due to its huge channel matrix dimension. Therefore, low-complexity detection technology has become a hot topic in the industry. Aiming at the problem of high computational complexity of the massive MIMO channel estimation, this paper presents a low-complexity algorithm for efficient channel estimation. The proposed algorithm is based on joint Singular Value Decomposition (SVD) and Iterative Least Square with Projection (SVD-ILSP) which overcomes the drawback of finite sample data assumption of the covariance matrix in the existing SVD-based semi-blind channel estimation scheme. Simulation results show that the proposed scheme can effectively reduce the deviation, improve the channel estimation accuracy, mitigate the impact of pilot contamination and obtain accurate CSI with low overhead and computational complexity.

scholarly journals Iterative Receiver with Low Complexity for Downlink Multicarrier Communications over Rapidly Time-Varying Channels

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Nihat Kabaoglu ◽  
Eylem Erdogan ◽  
Erdogan Aydin
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Communication Systems ◽  
Orthogonal Basis ◽  
Basis Functions ◽  
Time Varying ◽  
Low Computational Complexity ◽  
Downlink System ◽  
Time Varying Channel ◽  
Time Varying Channels

This study proposes an iterative, joint channel estimation, equalization, and data detection method in the presence of high mobility for a multicarrier downlink system that communicates over rapidly time-varying channels. The proposed method uses a basis expansion method (BEM) which has low computational complexity and helps to reduce the number of coefficients needed to represent a time-varying channel and therefore is extremely easy to implement practically. Unlike the current literature, which is almost entirely focused on the uplink communication systems due to their computational costs, this method prioritizes the goal of being feasible in a downlink system with a reasonable performance. The proposed suboptimal algorithm is based on the space-alternating generalized expectation-maximization (SAGE) algorithm and the time-varying channel is represented by orthogonal basis functions obtained by means of discrete Walsh-Hadamard transform (DWHT). The resulting receiver iterates between maximum a posteriori (MAP) based channel estimation in the subspace spanned by the orthogonal basis functions and successive interference cancellation. Numerical examples show that the proposed algorithm has a satisfactory symbol error rate with low computational complexity and also has a reasonable peak-to-average power ratio (PAPR) reduction effect.

Research on the Application of DPSK Technology in OFDM Doppler Receiver

2012 ◽  
Vol 468-471 ◽  
pp. 2206-2210
Author(s):  
Yao Fu ◽  
Xue Yan Chen ◽  
Yu Feng Ma ◽  
Hong Yuan Wang
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Phase Modulation ◽  
Original Data ◽  
Differential Phase ◽  
Doppler Diversity ◽  
Performance Gains ◽  
Diversity Receiver

A Doppler diversity receiver for OFDM is proposed by Kim B C[1], which requires channel estimation at the receiver, so its structure is complicated, what’s more, the receiver needs a large amount of calculation. Different from it, we use the differential phase modulation technology in the OFDM Doppler receiver, so the receiver can recover the original data without channel estimation, and the implement is simple, the computational complexity is low. However, experiment results show that the BER of the new receiver is higher than the conventional, and it can not get performance gains by diversity either.

scholarly journals Grouping-Based Channel Estimation and Tracking for Millimeter Wave Massive MIMO Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Rui Yin ◽  
Xin Zhou ◽  
Wei Qi ◽  
Celimuge Wu ◽  
Yunlong Cai
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Millimeter Wave ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Closed Form Solution ◽  
Network Capacity ◽  
Base Station ◽  
Estimation Accuracy

Although the millimeter wave (mmWave) massive multiple-input and multiple-output (MIMO) system can potentially boost the network capacity for future communications, the pilot overhead of the system in practice will greatly increase, which causes a significant decrease in system performance. In this paper, we propose a novel grouping-based channel estimation and tracking approach to reduce the pilot overhead and computational complexity while improving the estimation accuracy. Specifically, we design a low-complexity iterative channel estimation and tracking algorithm by fully exploiting the sparsity of mmWave massive MIMO channels, where the signal eigenvectors are estimated and tracked based on the received signals at the base station (BS). With the recovered signal eigenvectors, the celebrated multiple-signal classification (MUSIC) algorithm can be employed to estimate the direction of arrival (DoA) angles and the path amplitude for the user terminals (UTs). To improve the estimation accuracy and accelerate the tracking speed, we develop a closed-form solution for updating the step-size in the proposed iterative algorithm. Furthermore, a grouping method is proposed to reduce the number of sharing pilots in the scenario of multiple UTs to shorten the pilot overhead. The computational complexity of the proposed algorithm is analyzed. Simulation results are provided to verify the effectiveness of the proposed schemes in terms of the estimation accuracy, tracking speed, and overhead reduction.

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