Research on RACH Signal Detection Algorithm in TD-LTE System

2013 ◽  
Vol 380-384 ◽  
pp. 3912-3916 ◽  
Author(s):  
Wei Ping Shi ◽  
Zhuo Ran Wu ◽  
Xiao Wen Li
Keyword(s):  
Signal Detection ◽  
Random Access ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Time Frequency ◽  
Correlation Algorithm ◽  
Access Channel ◽  
Implementation Approach ◽  
Low Complexity Implementation ◽  
Signal Time

In TD-LTE system, RACH (Random Access Channel) process is an important process for gaining time-frequency resource of uplink. Through the research on RACH signal detection, a low-complexity implementation approach is proposed in this paper. After research and analysis of RACH signal time domain detection algorithm and RACH signal circulate correlation algorithm based on Fast Fourier Transform (FFT), According to the Zadoff-Chu (ZC) sequence character, RACH signal circulate correlation on detection algorithm based on frequency domain ZC is proposed in this paper .Combined with different algorithm, the algorithm is proposed in this paper can rapid and effective realize RACH signal detection.

scholarly journals Low-Complexity Soft-Output Signal Detection Based on Improved Kaczmarz Iteration Algorithm for Uplink Massive MIMO System

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1564
Author(s):  
Hebiao Wu ◽  
Bin Shen ◽  
Shufeng Zhao ◽  
Peng Gong
Keyword(s):  
Signal Detection ◽  
Output Signal ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Base Station ◽  
Matrix Inversion ◽  
Iteration Algorithm

For multi-user uplink massive multiple input multiple output (MIMO) systems, minimum mean square error (MMSE) criterion-based linear signal detection algorithm achieves nearly optimal performance, on condition that the number of antennas at the base station is asymptotically large. However, it involves prohibitively high complexity in matrix inversion when the number of users is getting large. A low-complexity soft-output signal detection algorithm based on improved Kaczmarz method is proposed in this paper, which circumvents the matrix inversion operation and thus reduces the complexity by an order of magnitude. Meanwhile, an optimal relaxation parameter is introduced to further accelerate the convergence speed of the proposed algorithm and two approximate methods of calculating the log-likelihood ratios (LLRs) for channel decoding are obtained as well. Analysis and simulations verify that the proposed algorithm outperforms various typical low-complexity signal detection algorithms. The proposed algorithm converges rapidly and achieves its performance quite close to that of the MMSE algorithm with only a small number of iterations.

An Improved MIMO-OFDM Detection Algorithm Based on OSIC

2014 ◽  
Vol 696 ◽  
pp. 201-206
Author(s):  
Da Jiang Yang ◽  
Zi Fa Zhong
Keyword(s):  
Signal Detection ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Optimal Detection ◽  
Ofdm Signal ◽  
Mimo Ofdm ◽  
Ml Detection ◽  
Improved Algorithm

This paper proposes a MIMO-OFDM signal detection algorithm with joint ML and MMSE-OSIC based on researches of ML algorithm and MMSE-OSIC algorithm. This kind of algorithm is an improved algorithm of MMSE-OSIC. Comparing to the traditional MMSE-OSIC algorithm, this algorithm uses ML detection on the relatively weaker signal layer. According to the experiment, it was found close to the optimal detection performance, much less complicated than the ML algorithm, which is a near-optimal and low-complexity MIMO-OFDM detection algorithm.

Design and Realization of a Full Digitalization GMSK Modem on FPGA

2014 ◽  
Vol 543-547 ◽  
pp. 562-567
Author(s):  
Ren Cai Zhao ◽  
Zhen Hu ◽  
Xiao Li ◽  
Yu Cheng Wu
Keyword(s):  
Signal Detection ◽  
Communication Channel ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Channel Gain ◽  
Sliding Windows ◽  
Timing Acquisition ◽  
Symbol Timing ◽  
Fast Acquisition ◽  
Simulation Results

To implement GMSK modem with the characteristics of good spectrum, low complexity and fast acquisition, a full digitizationGMSKmodem scheme was proposed. Based on LUT method, the generation of GMSK signals has better spectrum characteristicand easy to realize. In receive terminal, a non-coherent digitized GMSKreceiver with fast signal detection and symbol timing acquisitionalgorithm was presented. Double sliding windows was used to conquer the influence of communication channel gain on the detection algorithm and realized within 6 symbols with accuracy. Additionally, in order to reduce the complexity of the receiver, the received signals are demodulated sample by sample in advance and then decided with the estimated symbol timing. The symbol timing acquisition algorithm proposed is realized based on a preamble sequence rapidly within only 8 symbols. Simulation results and integrated FPGA realizationprove its feasibility and superiority.

Frequency hopping signal detection based on wavelet decomposition and Hilbert–Huang transform

2017 ◽  
Vol 31 (19-21) ◽  
pp. 1740078 ◽  
Author(s):  
Yang Zheng ◽  
Xihao Chen ◽  
Rui Zhu
Keyword(s):  
Signal Detection ◽  
Frequency Analysis ◽  
Wavelet Decomposition ◽  
Frequency Hopping ◽  
Detection Algorithm ◽  
Frequency Resolution ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Low Probability ◽  
Simulation Results

Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert–Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert–Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

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