A little feedback can simplify sensor network cooperation

Abstract

Abstract-Shannon's discovery of digital communication has shaped the architecture of virtually all communication systems in use today. The digital communication paradigm is built around the notion of bits and uses careful coding to deliver bits reliably end-to-end. It has been shown that this architectural principle can lead to a very significant performance penalty in wireless sensor networks. For a limited class of network scenarios, it was shown that optimal architectures are analog in nature, simple and scalable. In this paper, we show that more generally, simple analog architectures crucially depend on feedback to the sensors. Interesting questions then concern the amount of feedback needed and the resulting trade-off with performance. This paper provides rules-of-thumb for the selection of the number of feedback bits.

Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters

“…4, we present convergence trajectories of CCP (namely, Algorithm 1) and penalty CCP (namely, Algorithm 2) as functions of interation index for 10 different initial points. For comparison, we plot the worst objective function value of collaboration problem (7) when w = 0, namely, LMMSE is determined only by the prior information, which leads to the worst estimation error tr(Σ θ ) = K = 3. As we can see, much of the benefit of using CCP or penalty CCP is gained during the first few iterations.…”

“…In this section, we simplify problem (7) by exploiting the sparsity structure of the topology matrix and concatenating the nonzero entries of a collaboration matrix into a collaboration vector. There exist two benefits to using matrix vectorization: a) the topology constraint in (7) can be eliminated without loss of performance, which renders a less complex problem; b) the structure of nonconvexities is more easily revealed via such a reformulation. In problem (7), the only optimization variables are the nonzero entries of collaboration matrices.…”

“…Compared to problem (7), the topology constraint in terms of A is eliminated without loss of performance in (P1) since the sparsity structure of the topology matrix has been taken into account while constructing the collaboration vector. In the special case of single-snapshot estimation (namely, K = 1), the objective function of (P1) simplifies to a single quadratic ratio.…”

“…In [6], a likelihoodbased multiple access communication strategy was proposed for estimation, and was proved to be asymptotically efficient as the number of sensors increases. In [7], feedback signals were studied to combat uncertainty in the observation model for distributed estimation with coherent MAC. In [8], distributed detection problem was studied in the setting of identical Gaussian multiple access channels (without fading).…”

Surveying Multidisciplinary Aspects in Real-Time Distributed Coding for Wireless Sensor Networks

“…Though the majority of WSNs adopt digital transmission [ 31 ] (commonly used standards are IEEE 802.15.4/ZigBee [ 32 ], IEEE 802.15.1/Bluetooth [ 33 ], ISA100/WirelessHart [ 34 ]), a number of solutions based on analog modulation are emerging ([ 35 – 41 ], among others). Although the communication problem presented here is formulated for analog transmission, the impact on WSN applications may be relevant, because fully digital and fully analog architectures may be intrinsically inefficient for a WSN [ 42 ]. In multi-hop WSNs with relaying, analog and digital solutions have been compared in [ 43 ].…”