Paper accepted in IEEE SPL 2017

Our paper:

D. Ciuonzo, P. Salvo Rossi and P. Willett,  “Generalized Rao Test for Decentralized Detection of an Uncooperative Target”

 

has been accepted for publication in IEEE Signal Processing Letters

The present work develops a generalized Rao test for decentralized detection of an uncooperative target through Sensor Networks and proposes a threshold-optimization criterion.

Paper accepted in IEEE CL (mar. 2015)

Our manuscript:

P. Salvo Rossi, D. Ciuonzo and T. Ekman, HMM-Based Decision Fusion in Wireless Sensor Networks with Noncoherent Multiple Access

has been accepted for publication in IEEE Communications Letters. The present manuscript provides a novel approach for decision fusion over multiple-access channel, when the binary source is generally modelled as a Markov Chain.

Paper accepted in IEEE TSP (Nov. 2014)

Our journal paper

D. Ciuonzo, P. Salvo Rossi and S. Dey, “Massive MIMO Channel-Aware Decision Fusion”,

has been accepted for publication in IEEE Transactions on Signal Processing.

The paper develops a thorough study on design and performance analysis of sub-optimal fusion rules when the fusion center is equipped with a large-array (namely a “massive” virtual MIMO setup).

Paper accepted in IEEE Sensors Journal (Oct. 2014)

Our journal paper

P. Salvo Rossi, D. Ciuonzo, T. Ekman and H. Dong, “Energy Detection for MIMO Decision Fusion in Underwater Sensor Networks”, IEEE Sensors Journal.

has been accepted for publication in IEEE Sensors Journal.

The paper proposes and studies energy detection test as a sub-optimal (but feasible) fusion rule for MIMO decision fusion in underwater wireless sensor networks.

Paper published in IEEE SPL 2014 (Feb. Issue)

Our journal paper

Mimetypes-pdf-icony   [J-11] || D. Ciuonzo and P. Salvo Rossi, “Decision Fusion with Unknown Sensor Detection Probability“, IEEE Signal Processing Letters, vol. 21, no. 2, pp. 1070-9908, February 2014.

appears in the current issue (Feb. 2014) of IEEE Signal Processing Letters.

The paper provides a detailed study on fusion rules which exploit the sole knowledge of the sensor false-alarm probabilities. Existing rules in the literature are theoretically compared and a locally-optimum detection (LOD) based fusion rule is derived, showing performance close to the (clairvoyant) Likelihood-ratio test.

Supplementary material is also given on IEEExplore, containing proofs and derivations.

Paper accepted in IEEE SPL (Dec 2013)

Our journal paper

– D. Ciuonzo and P. Salvo Rossi, “Decision Fusion with Unknown Sensor Detection Probability

has been accepted for publication in IEEE Signal Processing Letters.

The paper provides a detailed study on fusion rules which exploit the sole knowledge of the sensor false-alarm probabilities. Existing rules in the literature are theoretically compared and a locally-optimum detection (LOD) based fusion rule is derived, showing performance close to the (clairvoyant) Likelihood-ratio test.

Paper published IEEE TWC 2013

Our journal paper

[J-7] || D. Ciuonzo, G. Romano and P. Salvo Rossi, “Performance Analysis and Design of Maximum Ratio Combining in Channel-Aware MIMO Decision Fusion“, IEEE Transactions on Wireless Communications, vol. 12, no. 9, pp. 4716 – 4728, September 2013

appears in the current issue (Sep. 2013) of IEEE Transactions on Wireless Communications. The manuscript provides a detailed theoretical study of the inexpensive maximum-ratio combining (MRC) fusion rule in channel-aware MIMO decision fusion scenario.