Papr analysis and channel estimation techniques for 3GPP LTE system

Abstract

High data rates and secured data communication has become an unavoidable need of every mobile users. 3G technology provided greater data speed and secured networks compared to its predecessor 2G or 2.5G. The highest bit rates in commercially deployed wireless systems are achieved by means of Orthogonal Frequency Division Multiplexing (OFDM) [1]. The next advance in cellular systems, under investigation by Third Generation Partnership Project (3GPP), also anticipates the adoption of OFDMA to achieve high data rates. But a modified form of OFDMA i.e. SCFDMA (Single Carrier FDMA) having similar throughput performance and essentially the same complexity has been implemented as it has an edge over OFDMA having lower PAPR (peak to average power ratio) [2]. SCFDMA is currently a strong candidate for the uplink multiple access in the Long Term Evolution of cellular systems under consideration by the 3GPP. In our project we have worked on PAPR analysis of OFDMA, SCFDMA and various other SCFDMA (with different subcarrier mapping). Though SCFDMA had larger ISI it has lower PAPR which help in avoiding the need of an efficient linear power amplifier. We have analyzed various modulation techniques and implemented various kinds of pulse shaping filters and compared the PAPR for IFDMA, DFDMA and LFDMA (kinds of SCFDMA). Like other communication systems, in SCFDMA we encounter many trade-offs between design parameters (such as roll-off factor) and performance.

The project report also constitutes the channel estimation techniques implemented in OFDM systems. Due to multipath fading the channel impulse response fluctuates for different subcarriers in different time slots. But with channel estimation OFDM systems can use coherent detection instead of differential. For MIMO system like OFDM channel information is vital for diversity combining and interference suppression [3]. So we need to estimate the channel as accurately as possible. As we have taken a slow Rayleigh fading channel in our study we used block type pilot arrangement channel estimation which uses LS (least square), MMSE (minimum mean square error) estimator. Due to higher complexity of the MMSE estimator, modified MMSE is implemented where tradeoff is made with performance. Here we have compared various channel estimation techniques used in OFDM systems. There are various other adaptive estimation techniques like LMS and RLS for estimating blind channels and comb type pilot arrangement estimation techniques for fast fading channels.