CiteULike: dcastro's Krishnamurthy

Adaptive OFDM synchronization algorithms based on discrete stochastic approximation

V Krishnamurthy — 2008-02-25T19:19:01-00:00

Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], Vol. 53, No. 4. (2005), pp. 1561-1574.

This paper presents discrete stochastic approximation algorithms (DSA) for time synchronization in orthogonal frequency division multiplexing (OFDM) systems. It is shown that the discrete stochastic approximation algorithms can be effectively used to achieve a significant reduction in computational complexity compared to brute force maximum-likelihood (ML) methods for OFDM synchronization. The most important property of the proposed algorithms is their recursive self-learning capability-most of the computational effort is spent at the global or a local optimizer of the objective function. The convergence of the algorithms is analyzed. An adaptive version of the discrete stochastic approximation algorithm is also presented for tracking time-varying time delays and frequency offsets in time-selective fading channels. Detailed numerical examples illustrate the performance gains of these DSA-based synchronization algorithms.

Power Management for Throughput Enhancement in Wireless Ad-Hoc Networks

Tamer Elbatt — 2006-08-24T23:47:15-00:00

(2000), pp. 1506-1513.

In this paper we introduce the notion of power management within the context of wireless ad-hoc networks. More specifically, we investigate the effects of using different transmit powers on the average power consumption and end-to-end network throughput in a wireless ad-hoc environment. This power management approach would help in reducing the system power consumption and hence prolonging the battery life of mobile nodes. Furthermore, it improves the end-to-end network throughput as compared to ...

On indoor position location with wireless LANs

P Prasithsangaree — 2007-04-19T08:42:56-00:00

Personal, Indoor and Mobile Radio Communications, 2002. The 13th IEEE International Symposium on, Vol. 2 (2002), pp. 720-724 vol.2.

Location aware services are becoming attractive with the deployment of next generation wireless networks and broadband multimedia wireless networks especially in indoor and campus areas. To provide location aware services, obtaining the position of a user accurately is important. While it is possible to deploy additional infrastructure for this purpose, using existing communications infrastructure is preferred for cost reasons. Because of technical restrictions, location fingerprinting schemes are the most promising. In this paper we present a systematic study of the performance tradeoff and deployment issues. In this paper we present some experimental results towards such a systematic study and discuss some issues related to the indoor positioning problem.

A low complexity timing and frequency synchronization algorithm for OFDM systems

CRN Athaudage — 2007-11-11T15:35:11-00:00

Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE, Vol. 1 (2002), pp. 244-248 vol.1.

The paper presents a low complexity discrete stochastic approximation algorithm for time and frequency synchronization in OFDM systems. The proposed technique can track the conditions of a slowly time varying channel where synchronization parameters, namely the symbol timing and frequency offset, vary slowly with time. The most important property of the proposed algorithm is its self-learning capability - it spends most of the computational effort at the global minimizer of the objective function. In particular, we show that the algorithm achieves an /spl epsiv/=(1-/spl rho/)/(1+/spl rho/) reduction in computational cost (in terms of complex multiplications to be performed), where /spl rho/=N/sub cp//N is the ratio between cyclic prefix length (N/sub cp/) and number of subcarriers (N) of the OFDM system (e.g. N=512 and N/sub cp/=64 gives /spl epsiv/=78%). Numerical examples illustrate the synchronization accuracy of the proposed technique in terms of symbol timing and frequency offset estimation errors.