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Joint signal detection and classification of mobile WiMAX and LTE OFDM signals for cognitive radio

Joint signal detection and classification of mobile WiMAX and LTE OFDM signals for cognitive radio,10.1109/ACSSC.2010.5757489,A. Al-Habashna,O. A. Dob

Joint signal detection and classification of mobile WiMAX and LTE OFDM signals for cognitive radio   (Citations: 3)
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Spectrum awareness is one of the most challenging tasks in cognitive radio (CR). To adequately adapt to the changing radio environment, it is necessary for the CR to be able to perform joint detection and classification of low signal-to-noise ratio (SNR) signals without requiring much a priori information on the signal parameters. In this paper, we propose a joint detection and classification algorithm for the mobile Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution (LTE) signals. The algorithm has the advantage that it requires relaxed information on the signal parameters. Simulation results are presented, which show the efficiency of the proposed algorithm under diverse scenarios.
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    • ...Most of the algorithms proposed for the OFDM signal detection rely on the cyclic prefix (CP)-induced cyclostationarity, viz., the existence of statistically significant peaks in the cyclic autocorrelation function (CAF) due to the CP [3]-[7]...
    • ...Although the parameters related to the CP-induced cyclostationarity are known for standard signals (note that diverse transmission modes can have different parameters) [7], cognitive users sharing the spectrum might employ the OFDM modulation with similar subcarrier frequency separation...

    Ala'a Al-Habashnaet al. Cyclostationarity-Based Detection of LTE OFDM Signals for Cognitive Ra...

    • ...Abstract- This paper provides a brief overview of selected achievements by our group concerning cyclostationarity -based signal detection, classification, and blind parameter estimation [1 ]-[9]...
    • ...The secon d-order/ one-conjugate CCs and the set ofCFs for OFDM signals are respectively given as [2], [9] cr(/3; t)2,1 =,A 2cs,2,Ir-le-j2m;�TEK(t)A(t) + cw( /3; t)2,1' (16)...
    • ...Moreover, standard signals can be identified Here we consider the example of mobile WiMAX OFDM signals (symbol-, CP-, and preamble-induced cyclostationarity); for the LTE OFDM signals the reader is referred to [8] and [9]; -Furthermore, higher-order cyclostationarity can be employed to identify the modulation type of SCLD and CP-SCLD signals, i.e., M-ASK, M-PSK, or M­ QAM...
    • ...If the candidate CF is found to be a CF, the decision that an SCLD or an CP-SCLD signal is present is made . Furthermore, for the recognition of the mobile WiMAX OFDM signal in the frequency bands specified by the standard [19]-[21], the estimated delay related to the CP-induced cyclostationarity [12], is compared against those corresponding to the standard [9], and the existence of the preamble-induced second-order cyclostationarity ...
    • ...Note that the first- and second-order cyclostationarity based signal detection and classification algorithms have the advantage of avoiding the need for the recovety of the carr ier, waveform, and symbol timing, or the estimation of noise and signal power [1]-[2], [5]-[9]...
    • ...I Note that in practice we use discrete-time signals obtained by sampling the corresponding continuous-time signals at rate f.. Hence, the CCS and CPs have to be correspondingly considered [1]-[9]...
    • ...The detection and classification perfonnance for the CP-SCLD signals, and the perfonnance of the estimators for N and f are respectively plotted versus SNR in Fig. 4 and 5. Additional results are given in [1]-[9]...

    O. A. Dobreet al. Application of cyclostationarity to joint signal detection, classifica...

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