Pilot symbol driven monitoring of electrical degradation in RF transmitter systems using model anomaly diagnosis

Modern RF circuits suffer from increased electrical degradation induced by electrical stress and thermal effects due to the high speeds of operation and the effects of technology scaling. Detection of such degradation is important, particularly in wireless basestations which must operate round-the-clock with high dependability. In this paper, a new approach for detecting degradation in RF transmitter systems using pilot symbols is proposed and is superior to prior algorithms because degradation can be monitored on a frame-to-frame basis independent of the data being transmitted. The response of the RF transmitter to known pilot symbols is captured at the output of the RF power amplifier using an envelope detector and is fitted to a third order transmitter model using a model-parameter solving algorithm. It is shown that the computed model parameters deviate away from their nominal values, exhibiting model anomalies once nonidealities due to electrical degradation start affecting transmitter behavior. The amount of the degradation is proportional to the magnitude of this deviation as measured by a distance metric and is easily computed using simple algorithms running on the baseband processor. Preliminary results indicate the feasibility and low cost of the proposed approach.

[1]  Irith Pomeranz,et al.  Concurrent online testing of identical circuits using nonidentical input vectors , 2005, IEEE Transactions on Dependable and Secure Computing.

[2]  Reliability model for predicting long-term DC/RF performance in GaAs PHEMTs , 2005, IEEE Compound Semiconductor Integrated Circuit Symposium, 2005. CSIC '05..

[3]  Trevor Hastie,et al.  Multivariate adaptive regression splines. Discussions , 1991 .

[4]  Gordon W. Roberts,et al.  A built-in self-test strategy for wireless communication systems , 1995, Proceedings of 1995 IEEE International Test Conference (ITC).

[5]  L Moquillon,et al.  DC hot carrier stress effect on CMOS 65nm 60 GHz power amplifiers , 2010, 2010 IEEE Radio Frequency Integrated Circuits Symposium.

[6]  Abhijit Chatterjee,et al.  On-line error detection in wireless RF transmitters using real-time streaming data , 2006, 12th IEEE International On-Line Testing Symposium (IOLTS'06).

[7]  Abhijit Chatterjee,et al.  Low-cost parametric test and diagnosis of RF systems using multi-tone response envelope detection , 2007, IET Comput. Digit. Tech..

[8]  J. Friedman Multivariate adaptive regression splines , 1990 .

[9]  Timo Rahkonen,et al.  Distortion in RF power amplifiers , 2003 .

[10]  Chuanzhao Yu,et al.  Electrical and Temperature Stress Effects on Class-AB Power Amplifier Performances , 2007, IEEE Transactions on Electron Devices.

[11]  Sinem Coleri Ergen,et al.  Channel estimation techniques based on pilot arrangement in OFDM systems , 2002, IEEE Trans. Broadcast..

[12]  Abhijit Chatterjee,et al.  Automatic test stimulus generation for accurate diagnosis of RF systems using transient response signatures , 2011, 29th VLSI Test Symposium.

[13]  Abhijit Chatterjee,et al.  Environment-Adaptive Concurrent Companding and Bias Control for Efficient Power-Amplifier Operation , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[14]  H.-G.D. Stratigopoulos,et al.  An adaptive checker for the fully differential analog code , 2006, IEEE Journal of Solid-State Circuits.

[15]  Jien-Chung Lo Online Current Testing , 1998, IEEE Des. Test Comput..

[16]  Yushi Shen,et al.  Channel Estimation in OFDM Systems , 2006 .

[17]  G. Palmisano,et al.  Degradation Mechanisms in CMOS Power Amplifiers Subject to Radio-Frequency Stress and Comparison to the DC Case , 2007, 2007 IEEE International Reliability Physics Symposium Proceedings. 45th Annual.

[18]  Abhijit Chatterjee,et al.  Built-in performance monitoring of mixed-signal/RF front ends using real-time parameter estimation , 2010, 2010 IEEE 16th International On-Line Testing Symposium.