PARAMETRIC MODEL OF THE BICONICAL ANTENNA CLASS

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FCC Spectral Mask

The FCC has assigned the effective isotropic radiated power (EIRP) allowed for each frequency band, mentioned in Table 1.1, in order to avoid interference with existing communication systems. This regulation limits various regions of the spectrum to have different power spectral densities (PSD). The EIRP (equivalent isotropically radiated power or Effective isotropic radiated power) is the amount of power radiated by a transmitter, relative to theoretical isotropic antenna or radiator. EIRP refers to the highest signal strength measured in any direction and at any frequency by the UWB device or system. EIRP is used to estimate the service area of the transmitter, and to coordinate various transmitters on the same frequency, so that their coverage areas do not overlap. Fig. 1.2 illustrates the FCC radiation limits for the indoor and outdoor UWB communication systems. The level of 41.3 dBm/MHz in the frequency band of 3.1–10.6 GHz is set to limit interference to existing communication systems and to protect the existing radio services. This level (–41.3 dBm/MHz), is 75 nW/MHz, which is in fact identical to the unintentional radiation level of television sets or monitors [2]. For the indoor and outdoor UWB communications, the FCC radiation limits in the frequency range of [3.1–10.6] GHz are alike. While for the [1.61–3.1] GHz frequency range the outdoor radiation limit is 10 dB lower than the indoor Conventional Radio Signals UWB Radio Signals Power Spectral Density (PSD) Frequency mask. It should be noted that FCC rules confine the outdoor UWB communications.

Challenges and Requirements of UWB Antenna design

One of the challenges for the implementation of UWB systems is the development of a suitable or optimal antenna. The UWB system characteristics are heavily dependent on the design of the radiating element. The requirements imposed on UWB antennas, such as the phase linearity and the spectral efficiency, are more demanding than narrow band and broad band antennas. In designing UWB antenna, both the frequency and time-domain responses should be taken into account. In the following, the fundamental requirements for the UWB antennas are discussed briefly. In chapter 3 the parameters for characterizing a UWB antenna will be discussed.

Input Impedance bandwidth

The impedance bandwidth is measured in terms of reflection coefficient or voltage standing wave ratio (VSWR). Usually, the return loss should be less than 0.312 (or −10 dB reflection coefficient) for an antenna to be considered properly matched. An antenna with an impedance bandwidth narrower than the operating bandwidth behaves like a band pass filter and, as a result, modifies the transmitted/received signal. In other words, it reshapes the radiated or received pulses in the time domain. Small UWB antennas have a small radiation resistance and a large reactance. Consequently, it is difficult to achieve a suitable impedance matching. Therefore, the threshold of 10 dB can be seen as a too strict criterion when enforced over the whole operating bandwidth. Instead a more relaxed 6 dB threshold can also be considered, especially when it is neared over a small bandwidth as compared to the total BW of interest.

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Table of contents :

1. INTRODUCTION
1.1. UWB TECHNOLOGY
1.2. CHALLENGES AND REQUIREMENTS OF UWB ANTENNA DESIGN
1.3. CONTEXT OF THE WORK
1.4. STATE OF THE ART
1.5. OBJECTIVES
1.6. METHODOLOGY
1.7. ORGANIZATION OF THE THESIS
2. ANTENNA DESIGNS
2.1. INTRODUCTION
2.2. GENERIC GEOMETRY
2.3. PARAMETERIZATION
2.4. MONOPOLE DESIGNS
2.5. DIPOLE DESIGNS
2.6. MULTIBAND DESIGN
2.7. 3D BICONE DESIGN
2.8. CONCLUSION
3. OPTIMIZATION
3.1. INTRODUCTION
3.2. ANTENNA TRANSFER FUNCTION (ATF)
3.3. SYNTHETIC PERFORMANCE INDICATORS
3.4. OPTIMIZATION
3.5. THE OPTIMAL DESIGNS
3.6. BICONICAL DESIGN
3.7. MULTIBAND DESIGN
3.8. CONCLUSION
4. STATISTICAL ANALYSIS
4.1. INTRODUCTION
4.2. PROCEDURE
4.3. POPULATION STATISTICS
4.4. MODELING OF RADIO EM PARAMETERS – RESULTS
4.5. STATISTICS OF ADDITION KEY PERFORMANCE PARAMETERS
4.6. MULTI-OBJECTIVITY
4.7. CONCLUSION
5. PARAMETRIC MODELING
5.1. INTRODUCTION
5.2. THE PROCEDURE:
5.3. SINGULARITY EXPANSION METHOD (SEM)
5.4. SPHERICAL MODE EXPANSION METHOD (SMEM)
5.5. ULTRA COMPRESSED PARAMETRIC MODELING
5.6. CONCLUSION
6. ULTRA COMPRESSED STATISTICAL MODELING
6.1. INTRODUCTION
6.2. THE PROCEDURE
6.3. PARAMETRIC MODEL OF THE BICONICAL ANTENNA CLASS
6.4. CONCLUSION
7. SUMMARY AND CONCLUSIONS
8. REFERENCES
APPENDICES
A GOODNESS OF FIT TESTS
A.1 CHI-SQUARED TEST
A.2 KOLMOGOROV-SMIRNOV TEST
A.3 ANDERSON-DARLING TEST
A.4 AKAIKE INFORMATION CRITERION (AIC)
B STATISTICAL DISTRIBUTIONS
B.1 NORMAL DISTRIBUTION
B.2 WEIBULL DISTRIBUTION
B.3 BETA DISTRIBUTION
B.4 STUDENT‘S T DISTRIBUTION
B.5 GENERALIZED EXTREME VALUE (GEV) DISTRIBUTION
C SUPPORTED PROGRAMS
C.1 MATLAB TO CST CONTROL
C.2 CST DATA EXPORT
C.3 OPTIMIZATION COST FUNCTIONS