Spinal codes

Spinal codes are a new class of rateless codes that enable wireless networks to cope with time-varying channel conditions in a natural way, without requiring any explicit bit rate selection. The key idea in the code is the sequential application of a pseudo-random hash function to the message bits to produce a sequence of coded symbols for transmission. This encoding ensures that two input messages that differ in even one bit lead to very different coded sequences after the point at which they differ, providing good resilience to noise and bit errors. To decode spinal codes, this paper develops an approximate maximum-likelihood decoder, called the bubble decoder, which runs in time polynomial in the message size and achieves the Shannon capacity over both additive white Gaussian noise (AWGN) and binary symmetric channel (BSC) models. Experimental results obtained from a software implementation of a linear-time decoder show that spinal codes achieve higher throughput than fixed-rate LDPC codes, rateless Raptor codes, and the layered rateless coding approach of Strider, across a range of channel conditions and message sizes. An early hardware prototype that can decode at 10 Mbits/s in FPGA demonstrates that spinal codes are a practical construction.Massachusetts Institute of Technology (Irwin and Joan Jacobs Presidential Fellowship)Massachusetts Institute of Technology (Claude E. Shannon Assistantship)Intel Corporation (Intel Fellowship

Factor graph based detection approach for high-mobility OFDM systems with large FFT modes

In this article, a novel detector design is proposed for orthogonal frequency division multiplexing (OFDM) systems over frequency selective and time varying channels. Namely, we focus on systems with large OFDM symbol lengths where design and complexity constraints have to be taken into account and many of the existing ICI reduction techniques can not be applied. We propose a factor graph (FG) based approach for maximum a posteriori (MAP) symbol detection which exploits the frequency diversity introduced by the ICI in the OFDM symbol. The proposed algorithm provides high diversity orders allowing to outperform the free-ICI performance in high-mobility scenarios with an inherent parallel structure suitable for large OFDM block sizes. The performance of the mentioned near-optimal detection strategy is analyzed over a general bit-interleaved coded modulation (BICM) system applying low-density parity-check (LDPC) codes. The inclusion of pilot symbols is also considered in order to analyze how they assist the detection process

Assuring the integrity of offshore carbon dioxide storage

Carbon capture and storage is a key mitigation strategy proposed for keeping the global temperature rise below 1.5 °C. Offshore storage can provide up to 13% of the global CO2 reduction required to achieve the Intergovernmental Panel on Climate Change goals. The public must be assured that potential leakages from storage reservoirs can be detected and that therefore the CO2 is safely contained. We conducted a controlled release of 675 kg CO2 within sediments at 120 m water depth, to simulate a leak and test novel detection, quantification and attribution approaches. We show that even at a very low release rate (6 kg day−1), CO2 can be detected within sediments and in the water column. Alongside detection we show the fluxes of both dissolved and gaseous CO2 can be quantified. The CO2 source was verified using natural and added tracers. The experiment demonstrates that existing technologies and techniques can detect, attribute and quantify any escape of CO2 from sub-seabed reservoirs as required for public assurance, regulatory oversight and emissions trading schemes