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In this paper a highly selective ultra-wide band (UWB) bandpass filter is designed using interdigital parallel coupled lines (IDPCL) and multiple resonance resonator (MRR). Interdigital capacitor (IDC) is used to achieve strong coupling between short circuit stubs. Mixed coupling produced by IDC and coupled short circuit stubs introduce a finite tr...
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... proposed UWB bandpass filter is shown in Fig.1. Filter consists of two high impedance parallel coupled lines attached to a low impedance coupled lines in the center. ...
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... 3 shows the location of transmission zero. It depends on the resonating structure consist chip capacitor parallel with short circuit stub as shown in Fig. 2. 978-1-4673-2141-9/13/$31.00 ©2013 IEEE The quadratic equation in the denominator of F (θ), as separately written in equation (4), effects the number of transmission poles in the passband. (4) gives non-zero real roots, total of six transmission poles can be achieved. Now in order to get parameter values, design procedure given in [8] is adopted. Bandwidth of 5.5 GHz is ...
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... validate the proposed design, full wave EM simulation is done using RT duriod 5880 with (ε r = 2.2, tan δ = 0.0009 and height h = 787µm) on microstrip line. IDPCL's are used with MRR to realize UWB bandpass filter. In order to meet the tight coupling requirement, the middle line width of IDPCL transmission line is made different than the side lines. 50 Ohm transmission lines are used at input/output. Full wave simulation is done using ADS momentum [10]. The calculated physical dimensions shown in Fig. 1
Fig. 6 shows simulated and measured results of designed filter. Passband of 4.8 GHz, with six transmission poles, at 20 dB return loss has been achieved. Measured results are well correlated with simulation. However, there are some mismatch in ripple levels. These variations are due to the effect of fingers lines of IDC and also from the IDPCL tight coupling requirements. By introducing ground aperture under the IDC the even-mode impedance can be maximized thus increasing coupling gaps. This will restrict the ripple level under 20 dB. Moreover, the substrate losses, nonlinear loss factor for wide bandwidths and fabrication losses may also contributes towards the high return loss in some parts. Further investigating the performance of frequency response shows increase in fractional bandwidth to 70.1%. Furthermore, by adding IDPCL at input output port, the return loss performance improves compare to single stage MRR. Here the bandwidth is set with respect to standard UWB filter specification. From the the response, it can be seen that the frequency is now centered around 6.85 GHz of frequency. The sub-figure shows the close-up of transmission coefficient S 12 . The effect of low Q-factor for microstrip line can be observed, where the measured response degrade over the passband. Moreover, with this structure high bandwidth can be achieved at the cost of low loss performance. ...
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... proposed UWB bandpass filter is shown in Fig.1. The filter consists of two high impedance IDPCL attached to a low impedance short circuit stubs. Short circuits are realized by via holes with diameter d. IDC is used to couple the low impedance short circuit stubs. For achieving tight coupling, ten finger lines are used to design IDC. Here, MRR consists of IDC and short circuit stubs. In this configuration MRR structure produces four transmission poles while two more poles are introduced by IDPCLs. Here, to minimize the discontinuity loss tapered transmission line is used to attach IDC with short circuit ...
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Citations
... To solve this problem, Z. Tian and Giannakis [14] applied Compressive spectrum sensing (CSS) theory to CR systems for acquiring wideband signals at sub-Nyquist sampling rates. Capitalizing on the sparseness of the signal spectrum in open-access networks, compressed sensing techniques were developed for the coarse sensing task of unutilized spectrum i.e. spectrum holes' (SHs) identification. ...
In the last few years Compressed Sampling (CS) has been well used in the area of signal processing and image compression. Recently, CS has been earning a great interest in the area of wireless communication networks. CS exploits the sparsity of the signal processed for digital acquisition to reduce the number of measurement, which leads to reductions in the size, power consumption, processing time and processing cost. This article presents application of CS for the spectrum sensing and channel estimation in Cognitive Radio (CR) networks. Basic approach of CS is introduced first, and then scheme for spectrum sensing and channel estimation for CR is discussed. First, fast and efficient compressed spectrum sensing (CSS) scheme is proposed to detect wideband spectrum, where samples are taken at sub-Nyquist rate and signal acquisition is terminated automatically once the samples are sufficient for the best spectral recovery and then, after the spectrum sensing, in the second phase notion of multipath sparsity is formalized and a novel approach based on Orthogonal Matching Pursuit (OMP) is discussed to estimate sparse multipath channels for CR networks. The effectiveness of the proposed scheme is demonstrated through comparisons with the existing conventional spectrum sensing and channel estimation methods.
... To implement wideband spectrum sensing, CR systems need some fundamental segments, i.e., wideband antenna, wideband radio frequency front-end, and high speed Analogto-Digital Converter (ADC). [14] and [15] developed the wideband antenna and the wideband filter efficiently but the development of ADC converter is moderately behind as the ADC currently have limited sampling rates, of the order of 1 GHz, which is not sufficient for wideband spectrum. To solve this problem, Tian and Giannakis [16] applied CS theory to CR systems for acquiring wideband signals at sub-Nyquist sampling rates. ...
This paper presents a Compressive Spectrum Sensing (CSS) technique for wideband Cognitive Radio (CR) system to shorten spectrum sensing interval. Fast and efficient CSS is used to detect wideband spectrum, where samples are taken at sub-Nyquist rate and signal acquisition is terminated automatically once the samples are sufficient for the best spectral recovery. To improve sensing performance we propose a new approach for sparsifying basis in context of CSS, based on Empirical Wavelet Transform (EWT) which is adaptive to the processed signal spectrum. Simulation results show that the proposed fast and efficient EWT CSS scheme outperforms the conventional Discrete Fourier Transform (DFT) and Discrete Cosine Transform (DCT) based schemes in terms of sensing time, detection probability, system throughput and robustness to noise
