Improved adaptive impedance matching for RF front-end systems of wireless transceivers

In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a low-pass passive T-impedance matching LC-network inserted between an RF transceiver and its antenna. Results of the AQGA tuning method are presented for applications across 1.4 to 5 GHz (satellite services, LTE networks, radar systems, and WiFi bands). Compared to existing genetic algorithm-based tuning techniques the proposed algorithm converges much faster to provide a solution. At 1.4, 2.3, 3.4, 4.0, and 5.0 GHz bands the proposed AQGA is on average 75%, 49.2%, 64.9%, 54.7%, and 52.5% faster than conventional genetic algorithms, respectively. The results reveal the proposed AQGA is feasible for real-time application in RF-front-end systems

On the Trade-Off Between Quality Factor and Tuning Ratio in Tunable High-Frequency Capacitors

A benchmark of tunable and switchable devices at microwave frequencies is presented on the basis of physical limitations to show their potential for reconfigurable cellular applications. Performance limitations are outlined for each given technology focusing on the quality factor (Q) and tuning ratio (eta) as figures of merit. The state of the art in terms of these figures of merit of several tunable and switchable technologies is visualized and discussed. If the performance of these criteria is not met, the application will not be feasible. The quality factor can typically be traded off for tuning ratio. The benchmark of tunable capacitor technologies shows that transistor-switched capacitors, varactor diodes, and ferroelectric varactors perform well at 2 GHz for tuning ratios below 3, with an advantage for GaAs varactor diodes. Planar microelectromechanical capacitive switches have the potential to outperform all other technologies at tuning ratios higher than 8. Capacitors based on tunable dielectrics have the highest miniaturization potential, whereas semiconductor devices benefit from the existing manufacturing infrastructure

Optimum power transfer in RF front end systems using adaptive impedance matching technique

Matching the antenna's impedance to the RF-front-end of a wireless communications system is challenging as the impedance varies with its surround environment. Autonomously matching the antenna to the RF-front-end is therefore essential to optimize power transfer and thereby maintain the antenna's radiation efficiency. This paper presents a theoretical technique for automatically tuning an LC impedance matching network that compensates antenna mismatch presented to the RF-front-end. The proposed technique converges to a matching point without the need of complex mathematical modelling of the system comprising of non-linear control elements. Digital circuitry is used to implement the required matching circuit. Reliable convergence is achieved within the tuning range of the LC-network using control-loops that can independently control the LC impedance. An algorithm based on the proposed technique was used to verify its effectiveness with various antenna loads. Mismatch error of the technique is less than 0.2%. The technique enables speedy convergence (<5 s) and is highly accurate for autonomous adaptive antenna matching networks

Improved adaptive impedance matching for RF front‑end systems of wireless transceivers

In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a low-pass passive T-impedance matching LC-network inserted between an RF transceiver and its antenna. Results of the AQGA tuning method are presented for applications across 1.4 to 5 GHz (satellite services, LTE networks, radar systems, and WiFi bands). Compared to existing genetic algorithm-based tuning techniques the proposed algorithm converges much faster to provide a solution. At 1.4, 2.3, 3.4, 4.0, and 5.0 GHz bands the proposed AQGA is on average 75%, 49.2%, 64.9%, 54.7%, and 52.5% faster than conventional genetic algorithms, respectively. The results reveal the proposed AQGA is feasible for real-time application in RF-front-end systems

Improved Adaptive Impedance Matching for RF Front-End Systems of Wireless Transceivers

In this paper an automatic adaptive antenna impedance tuning algorithm is presented that is based on quantum inspired genetic optimization technique. The proposed automatic quantum genetic algorithm (AQGA) is used to find the optimum solution for a low-pass passive T-impedance matching LCnetwork inserted between an RF transceiver and its antenna. Results of the AQGA tuning method are presented for applications across 1.4 to 5 GHz (satellite services, LTE networks, radar systems, and WiFi bands). Compared to existing genetic algorithm-based tuning techniques the proposed algorithm converges much faster to provide a solution. At 1.4, 2.3, 3.4, 4.0, and 5.0 GHz bands the proposed AQGA is on average 75%, 49.2%, 64.9%, 54.7%, and 52.5% faster than conventional genetic algorithms, respectively. The results reveal the proposed AQGA is feasible for real-time application in RF-front-end systems

Optimum Power Transfer in RF Front End Systems Using Adaptive Impedance Matching Technique

Matching the antenna’s impedance to the RF-front-end of a wireless communications system is challenging as the impedance varies with its surround environment. Autonomously matching the antenna to the RF-front-end is therefore essential to optimize power transfer and thereby maintain the antenna’s radiation efficiency. This paper presents a theoretical technique for automatically tuning an LC impedance matching network that compensates antenna mismatch presented to the RF-front-end. The proposed technique converges to a matching point without the need of complex mathematical modelling of the system comprising of non-linear control elements. Digital circuitry is used to implement the required matching circuit. Reliable convergence is achieved within the tuning range of the LC-network using control-loops that can independently control the LC impedance. An algorithm based on the proposed technique was used to verify its effectiveness with various antenna loads. Mismatch error of the technique is less than 0.2%. The technique enables speedy convergence

Measured CMOS Switched High-Quality Capacitors in a Reconfigurable Matching Network

Switched capacitors are here investigated for use in reconfigurable matching networks, particularly for DVB-H frequencies. A 0.13 um CMOS circuit is evaluated through both simulations and measurements. Source grounded NMOS transistors are used to switch high quality metal capacitors located above metal layer 8. The quality factor and tuning range depend on frequency, switch voltage, capacitor size, and transistor width. There is a clear trade-off between quality factor and tuning range, and measurements show quality factors above 50, 100, and 150 at tuning ranges of 3.9, 2.4, and 1.6, respectively. A reconfigurable matching network with the switched capacitors has been realized using external inductors and the measured matching domain for the DVB-H frequency band is shown. The total loss of the network is 1.0 dB, a result of the high quality switched capacitors