Albrecht Wolf

Improved source correlation estimation in wireless sensor networks

Emerging wireless sensor networks (WSNs) aim to overcome current needs for additional backbone infrastructure in mobile networks. Confronted with enormous requirements in terms of spectrum and energy efficiency, WSNs have been shown to benefit from distributed source coding (DSC) by means of multi-route redundancy. However, DSC in WSNs yields low performance regarding the correlation estimation of messages sent across different routes. Thus, we introduce a new dynamic threshold for the employed DSC technique, which minimizes the mean-square error (MSE) of such estimations. Moreover, we enhance the DSC algorithm using an over-determined linear equation-system such that the standard deviation is considerably smaller. The thereby proposed correlation estimation improves both signifying regions of the bit-error rate (BER) curve. The waterfall region is shifted by up to 10.5 dB and the error floor region is lowered by 70%. Additionally, we derive a BER boundary for the error floor which serves as a general performance indicator of the employed DSC technique.

Asymptotically Optimal Power Allocation for WSNs With Mutually Correlated Sensing Data

It is well known that distributed source coding can improve the reliability and energy efficiency of wireless sensor networks by exploiting the correlation among sensing data. In this letter, we strengthen the benefits of such an approach by proposing a simple, general, efficient power allocation scheme for an arbitrary amount of sensors. The proposed power allocation is asymptotically optimal at high signal-to-noise ratio.

An Efficient Power Allocation Scheme for Multirelay Systems With Lossy Intra-Links

The so-called chief executive officer problem suggests that the source message can be recovered at the destination by merging a set of corrupted replicas forwarded by multiple relays, as long as these replicas are sufficiently correlated with the original message. In this paper, we build on Slepian-Wolf’s correlated source coding theorem to design a simple, yet efficient power allocation scheme for a multirelay system, in which the direct link is unavailable to convey information. In such a system, the replicas forwarded by the relays are allowed to contain intra-link errors due to previous unreliable hops, and the destination is supposed to retrieve the source message by jointly decoding all received replicas. Importantly, the proposed power allocation is asymptotically optimal at high signal-to-noise ratio.

Outage based power allocation for a lossy forwarding two-relaying system

The extension of Decode-and-Forward (DF) relaying by lossy forwarding has the potential to ensure a reliable multi-hop message transport in wireless mesh networks. Unlike in conventional DF relaying, with lossy forwarding a relay forwards a message regardless whether errors have been detected after decoding. At the destination, a proper joint decoding technique exploits the high correlation of messages received via different network paths. According to the Slepian-Wolf correlated source coding theorem a performance improvement compared with the conventional DF relaying can be expected. The performance can be optimized by a power allocation scheme that distributes the total transmit power budget between source and relay nodes. This paper analyzes the outage probability (OP) based on the Slepian-Wolf source correlation theorem for a system with two relays and designs a power allocation scheme to minimize the OP. The proposed scheme reduces the OP by up to 1.5 orders of magnitude compared to the reference case of equal power allocation. We also compare the performance gain of a system with two relays against the case with a single relay for the same total transmit power budget. Results show a reduction of the OP of at least one and up to two orders of magnitude.