Estimation, Training, and Effect of Timing Offsets in Distributed Cooperative Networks

Abstract

Abstract-Successful collaboration in cooperative networks requires accurate estimation of multiple timing offsets. When combined with signal processing algorithms, the estimated timing offsets can be applied to mitigate the resulting inter-symbol interference (ISI). This paper seeks to address timing synchronization in distributed multi-relay amplify-and-forward (AF) and decode-andforward (DF) relaying networks, where timing offset estimation using a training sequence is analyzed. First, training sequence design guidelines are presented that are shown to result in improved estimation performance. Next, two iterative estimators are derived that can determine multiple timing offsets at the destination. The proposed estimators have a considerably lower computational complexity while numerical results demonstrate that they are accurate and reach or approach the Cramer-Rao lower bound (CRLB).

Optimal Training Sequences for Joint Timing Synchronization and Channel Estimation in Distributed Communication Networks

“…It is also known that in distributed multiuser and multi-relay cooperative networks, the receiver needs to detect and decode the signals from multiple nodes that are affected by multiple channels, multiple timing offsets (MTOs), and multiple carrier frequency offsets (MCFOs) [3], Ali [4]. However, the main focus in the literature has been on the design of TSs for channel estimation [5]- [18], or MCFO and channel estimation [19]- [23], while relatively little attention has been paid to the topic of TS design for joint MTO and multiple channel estimation [24].…”

“…However, the resulting TSs are only optimal for the estimation method under consideration and may not have broader applications. In [5], [23], and [24], new TSs that minimize the Cramér-Rao lower bound (CRB), which is the lower bound on the variance of the estimation error of any unbiased estimator, are derived. However, since the CRBs in [5], [23], and [24] are functions of specific channel realizations, the resulting TSs cannot be guaranteed to be optimal for all instances of random channels.…”

Transceiver Design for Distributed STBC Based AF Cooperative Networks in the Presence of Timing and Frequency Offsets

“…Quasi-static and frequency flat fading channels are considered, i.e., the channel gains do not change over the length of a frame but change from frame to frame according to a complex Gaussian distribution, CN (0, σ 2 ). The use of such channels is motivated by prior research in this field [10], [14], [33], [37]- [41]. Moreover, the assumption of frequency flat channels can be broadened to frequency selective channels by employing OFDM.…”

“…Following the approach in [7], [33], [37], [41] and for ease of reproducing the CRLBs and MSE curves in T . Note that in the next subsection, we employ random Rayleigh fading channels for analyzing the end-to-end BER performance of the overall system.…”

A Synchronous Cooperative Communication for Emergency Alert Broadcast Based on Cellular Systems

“…이 경우 릴레이들과 최종 수신원 사이의 서로 다른 시간 옵셋이 불 가피하며 이는 심볼간 간섭을 증대시키고 SNR(Signal-toNoise power Ratio) 손실을 초래하여 수신단의 성능을 현저 히 저하 시킨다 [5] . 이를 위하여 동기식 협력통신 방식이 필 요하며 이에 대한 많은 연구가 진행되는 상황이다 [6,7] . 특히 복잡도가 감소된 효율적인 동기 방식을 위한 프리엠블 (preamble) 구조와 데이터 복구 기법이 제안되었다 [8] .…”