As wireless communication becomes an ever-more important and pervasive part of our everyday life, system capacity and quality of service issues are becoming more critical. In order to increase the system capacity and improve the quality of service, it is necessary that we pay closer attention to bandwidth and power efficiency issues.

Orthogonal Frequency Division Multiplexing (OFDM) is a multicarrier modulation technique for high speed data transmission and is generally regarded as bandwidth efficient. However, OFDM signals suffer from high peak-to-average power ratios (PARs) which lead to power inefficiency in the RF portion of the transmitter. Moreover, in OFDM, the well-known pilot tone assisted modulation (PTAM) technique utilizes a number of dedicated training pilots to acquire the channel state information (CSI), resulting in somewhat reduced bandwidth efficiency.

In this talk, we will address the above mentioned bandwidth and power efficiency issues in OFDM. To avoid bandwidth efficiency loss due to dedicated training, we will first develop a superimposed training framework that can be used to track the frequency selective as well as the Doppler shift characteristics of a channel. Later on, we will propose a generalized superimposed training framework that allows improved channel estimates. To improve the power efficiency, we adopt the selected mapping (SLM) framework to reduce the PARs for OFDM. We first propose a dynamic SLM algorithm to greatly reduce the computational requirement of SLM without sacrificing its PAR reducing capability. We then propose a blind selected pilot tone modulation (BSPTM) scheme that avoids the side information issue in conventional SLM. Our proposed BSPTM is a novel joint channel estimation and PAR reduction algorithm, for which bandwidth efficiency – power efficiency - complexity - bit error rate tradeoffs are carefully considered.

Host: Joseph Cavallaro

Biography of Ning Chen:
Ning Chen received his dual B.S. degrees in Electronic Engineering and in Accounting from the Shanghai Jiao Tong University (SJTU), China in 1997. He was awarded the 1997 Outstanding Graduate of Shanghai Award by the Shanghai Educational Committee. From July 1997 to August 2000, he was an instructor in the School of Electronics and Information Technology at SJTU. He received his M.S. degree in Electrical and Computer Engineering from the New Mexico State University in December 2001. From January 2002 to May 2006, he was with the Georgia Institute of Technology, where he earned his Ph.D. degree in Electrical Engineering. He won the First Place Award in the lecture session of the Georgia Tech Annual Graduate Research Symposium in 2006. He is currently employed by Freescale Semiconductor in Austin, Texas.

Dr. Chen's general research interests are in the areas of signal processing and communications. Specific current interests include cross-layer design, predistortion linearization of nonlinear power amplifiers, peak-to-average power ratio reduction of communication signals, communication channel identification and equalization, and adaptive algorithm development on DSP. He is a technical committee member for GLOBECOM'06 and ICC'07. He is also an active reviewer for two IEEE journals, two European journals, and he has served as a reviewer for twelve international conferences.