RSS-based Localization in Wireless Sensor Networks using SOCP Relaxation

Marko Beko; Rui Miguel Henriques Dias Morgado Dinis; DEE Group Author

doi:10.1109/SPAWC.2013.6612150

RSS-based Localization in Wireless Sensor Networks using SOCP Relaxation

Marko Beko, Rui Miguel Henriques Dias Morgado Dinis, DEE Group Author

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Citations (Scopus)

Abstract

This paper addresses the problem of locating a single source from noisy received signal-strength (RSS) measurements in wireless sensor networks (WSNs). To overcome the non-convexity of the maximum likelihood (ML) optimization problem, we provide an efficient convex relaxation that is based on the second order cone programming (SOCP), for both cases of known and unknown source transmit power, and we use a simple iterative procedure to solve the problem when the transmit power and the path loss exponent (PLE) are simultaneously unknown. Simulation results demonstrate that the new approach outperforms the existing ones in terms of the estimation accuracy, while in terms of the complexity, it represents a good balance when compared to the existing approaches.

Original language	Unknown
Title of host publication	IEEE International Workshop on Signal Processing Advances in Wireless Communications
Pages	749-753
DOIs	https://doi.org/10.1109/SPAWC.2013.6612150
Publication status	Published - 1 Jan 2013
Event	SPAWC 2013: IEEE 14th Workshop on Signal Processing Advances in Wireless Communications - Duration: 1 Jan 2013 → …

Conference

Conference	SPAWC 2013: IEEE 14th Workshop on Signal Processing Advances in Wireless Communications
Period	1/01/13 → …

Access to Document

10.1109/SPAWC.2013.6612150

Cite this

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title = "RSS-based Localization in Wireless Sensor Networks using SOCP Relaxation",

abstract = "This paper addresses the problem of locating a single source from noisy received signal-strength (RSS) measurements in wireless sensor networks (WSNs). To overcome the non-convexity of the maximum likelihood (ML) optimization problem, we provide an efficient convex relaxation that is based on the second order cone programming (SOCP), for both cases of known and unknown source transmit power, and we use a simple iterative procedure to solve the problem when the transmit power and the path loss exponent (PLE) are simultaneously unknown. Simulation results demonstrate that the new approach outperforms the existing ones in terms of the estimation accuracy, while in terms of the complexity, it represents a good balance when compared to the existing approaches.",

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AU - Dinis, Rui Miguel Henriques Dias Morgado

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N2 - This paper addresses the problem of locating a single source from noisy received signal-strength (RSS) measurements in wireless sensor networks (WSNs). To overcome the non-convexity of the maximum likelihood (ML) optimization problem, we provide an efficient convex relaxation that is based on the second order cone programming (SOCP), for both cases of known and unknown source transmit power, and we use a simple iterative procedure to solve the problem when the transmit power and the path loss exponent (PLE) are simultaneously unknown. Simulation results demonstrate that the new approach outperforms the existing ones in terms of the estimation accuracy, while in terms of the complexity, it represents a good balance when compared to the existing approaches.

AB - This paper addresses the problem of locating a single source from noisy received signal-strength (RSS) measurements in wireless sensor networks (WSNs). To overcome the non-convexity of the maximum likelihood (ML) optimization problem, we provide an efficient convex relaxation that is based on the second order cone programming (SOCP), for both cases of known and unknown source transmit power, and we use a simple iterative procedure to solve the problem when the transmit power and the path loss exponent (PLE) are simultaneously unknown. Simulation results demonstrate that the new approach outperforms the existing ones in terms of the estimation accuracy, while in terms of the complexity, it represents a good balance when compared to the existing approaches.

U2 - 10.1109/SPAWC.2013.6612150

DO - 10.1109/SPAWC.2013.6612150

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EP - 753

BT - IEEE International Workshop on Signal Processing Advances in Wireless Communications

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