A new kind of adaptive frequency shift filter

Zhang, J.; Wong, K.M.; Jin, Qu; Wu, Qiang

doi:10.1109/icassp.1995.480323

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…u km [n] is the vector containing the input to the mth FRESH branch of the kth user. Considering x k [n] as the reference signal for the kth user, the weight vector w k may be determined so that the mean square error defined by the following equation is minimized [9].…”

Section: B the Spectrum Sensing Modelmentioning

confidence: 99%

“…This process of lineary combining frequency shifted versions of a signal is known as FRESH or Frequency shift filtering [5] and has been utilized in enhancing and detecting primary signals in the presence of noise [8]. The optimal weights, in the Minimum Mean Square Error (MMSE) sense, for the FRESH filter may be obtained by solving the Wiener-Hopf equations or may be found adaptively [9]. It is shown in [10] that the detection performance of primary signals exhibiting cyclostationarity or spectral coherence may be improved further by the use of Space Time FRESH (FREquency SHift) filters.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative spectrum sensing for cognitive radios using jointly adaptive FRESH filters

Ribhu

Ghosh

Mehra

2015

2015 Twenty First National Conference on Communications (NCC)

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In this paper, the problem of cooperative spectrum sensing of cyclostationary signals for cognitive radios is considered. It has been shown that the MMSE optimal filters for cyclostationary signals involve one or more frequency shift branches and are called FRESH (FREquency SHift) filters. Adaptive FRESH filters have been used in the past to enhance cyclostationary signals so as to ease their detection in AWGN channels. It has been observed that space time FRESH filtering leads to gains of up to 10 dB over a standard energy detector in a single user case. In this paper, it is proposed to extend this approach to a cooperative setting under fading channels resulting in gains of up to 3 dB over the standard energy detectors. Following this, the problem of joint adaptation of weights at different sensors is considered. It is seen via simulation that joint adaptation leads to additional gains of nearly 2 dB for a flat fading channel and 1 dB for a dispersive channel, in comparison to local adaptation schemes.

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Section: B the Spectrum Sensing Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Cooperative spectrum sensing for cognitive radios using jointly adaptive FRESH filters

Ribhu

Ghosh

Mehra

2015

2015 Twenty First National Conference on Communications (NCC)

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“…where r k [n] = r[n]e −j2πα k n and r c k [n] = r * [n]e −j2πα k n . From (3) we observe that the system performs linear time invariant (LTI) filtering of frequency shifted versions of r[n], therefore, the FRESH filter can be modeled as an LTI filter-bank applied to the frequency shifted versions of the input signal [20], [21]. The optimal FRESH filter in the sense of minimal TA-MSE between the output signal and the desired signal is developed in [19].…”

Section: E Frequency Shift Filteringmentioning

confidence: 99%

“…Fig. 12 compares between the values of the scaling obtained from the simulation and from the analytical expression (21) for Rx 4 with the KATA2 model parameters. The measured average scaling is obtained by averaging the scaling of the recovered signal at the output of h 2 [n], that is, evaluating y[n] d [n] .…”

Section: ) Evaluating Ta-mse Performance and Verifying Robustness Ofmentioning

confidence: 99%

Frequency-Shift Filtering for OFDM Signal Recovery in Narrowband Power Line Communications

Shlezinger

Dabora

2014

IEEE Trans. Commun.

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Power line communications (PLC) has been drawing considerable interest in recent years due to the growing interest in smart grid implementation. Specifically, network control and grid applications are allocated the frequency band of 0−500 kHz, commonly referred to as the narrowband PLC channel. This frequency band is characterized by strong periodic noise which results in low signal to noise ratio (SNR).In this work we propose a receiver which uses frequency shift filtering to exploit the cyclostationary properties of both the narrowband power line noise, as well as the information signal, digitally modulated using orthogonal frequency division multiplexing. An adaptive implementation for the proposed receiver is presented as well. The proposed receiver is compared to existing receivers via analysis and simulation.The results show that the receiver proposed in this work obtains a substantial performance gain over previously proposed receivers, without requiring any coordination with the transmitter.

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“…As a result, this system's capacity can increase several-times [1][2][3][4][5][6][7]. Studies on large narrowband interference suppression can be seen in other literatures [8][9][10][11][12][13][14][15], which apply the cyclostationary property of signals in wireless communi-cation systems with narrowband interference. Researches and investigations in related literatures show the fact that most modulated signals encountered in communication systems exhibit desirable spectral correlation and present obvious cyclostationary characteristic.…”

Section: Introductionmentioning

confidence: 99%

Separating cyclostationary signals from spectrally overlapping interference

Liu

Guo

et al. 2006

Front. Electr. Electron. Eng. China

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This paper studies an algorithm about separating spectrally overlapping signals using the cyclostationary properties of signals. On the basis of direct sequence spread system (DSSS), frequency shift filter is added into the receiver of the communication system. Although the structure of frequency shift filter is more complicated than the time-domain filter, it uses both time correlations and frequency spectrum correlations so it can achieve better performances on separating the overlapping signals. After the analysis of cyclostationary characteristic and frequency spectrum correlation, the structure of the frequency shift filter can be gained. Then, a self-adaptive algorithm is utilized for the purpose of achieving optimum multidimensional tap weights of frequency shift components. The simulation results indicate that this method can efficiently separate overlapping signals, and its error rate is lower than the time-domain filter or DSSS system by two orders of magnitude on the condition that high-power interference is added into the system.

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A new kind of adaptive frequency shift filter

Cited by 11 publications

References 5 publications

Cooperative spectrum sensing for cognitive radios using jointly adaptive FRESH filters

Cooperative spectrum sensing for cognitive radios using jointly adaptive FRESH filters

Frequency-Shift Filtering for OFDM Signal Recovery in Narrowband Power Line Communications

Separating cyclostationary signals from spectrally overlapping interference

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