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Brendon McBain

Publications and source records attributed to Brendon McBain.

6 recordsLinked to original sources

Ergodic Capacity and Optimal Handover in Satellite Mega-Constellations under Finite Serving Times

Existing analyses of ergodic capacity in satellite mega-constellations often rely on restrictive serving time assumptions or become intractable under realistic handover strategies. This paper develops a framework for characterising the ergodic capacity of low-Earth-orbit (LEO) mega-constellation links under arbitrary handover strategies and serving times. The user--satellite link is modelled as shadowed-Rician fading, and a semi-stochastic satellite channel with persistence is introduced in which visible satellites are drawn from a non-homogeneous binomial point process (NBPP) at each handover and the selected satellite is then propagated using circular orbit dynamics. Under uncoordinated handover decisions, this yields independent serving periods and enables a renewal-theoretic derivation of persistent capacity. This capacity is related to the non-persistent capacity from prior work, and closed-form bounds are provided for efficient evaluation. Optimal handover is then formulated as a non-linear fractional program, yielding an explicit decision rule via a variant of Dinkelbach's algorithm. The results show that a simpler strategy that maximises serving capacity closely approximates the optimum while performing best under SGP4-based orbit prediction and mega-constellation simulation.

cs.IT

Information Rate Decomposition for Noisy Nanopore Channels with Geometric Duplication

This paper studies information rates of noisy duplication channels with memory, motivated by nanopore DNA sequencing. In nanopore sequencing, the measured signal is affected by both inter-symbol interference (ISI), caused by multiple DNA bases residing in the pore, and random sample duplications, where variable translocation speed causes each base to generate a random number of samples. These two effects make direct theoretical analysis difficult. To address this, we derive a new decomposition of the information rate into two interpretable terms: one capturing the channel memory through an auxiliary ISI channel, and another capturing the uncertainty in the segment boundaries caused by random duplications. This decomposition separates the dominant channel distortions and replaces the direct analysis of the full channel with two more readily tractable components. We then study the second term through a soft alignment functional closely related to Soft-DTW, which yields a strong asymptotic equipartition property result and an alternative proof of the Markov-constrained coding theorem. Finally, we develop a lower bound on the information rate that depends on the distribution of jump distances between adjacent nanopore levels. This bound gives a simple geometric explanation of channel synchronisability and provides a tractable framework for computing achievable rates of Oxford nanopore sequencers.

cs.IT

Achievable Rates of Nanopore-based DNA Storage

This paper studies achievable rates of nanopore-based DNA storage when nanopore signals are decoded using a tractable channel model that does not rely on a basecalling algorithm. Specifically, the noisy nanopore channel (NNC) with the Scrappie pore model generates average output levels via i.i.d. geometric sample duplications corrupted by i.i.d. Gaussian noise (NNC-Scrappie). Simplified message passing algorithms are derived for efficient soft decoding of nanopore signals using NNC-Scrappie. Previously, evaluation of this channel model was limited by the lack of DNA storage datasets with nanopore signals included. This is solved by deriving an achievable rate based on the dynamic time-warping (DTW) algorithm that can be applied to genomic sequencing datasets subject to constraints that make the resulting rate applicable to DNA storage. Using a publicly-available dataset from Oxford Nanopore Technologies (ONT), it is demonstrated that coding over multiple DNA strands of $100$ bases in length and decoding with the NNC-Scrappie decoder can achieve rates of at least $0.64-1.18$ bits per base, depending on the channel quality of the nanopore that is chosen in the sequencing device per channel-use, and $0.96$ bits per base on average assuming uniformly chosen nanopores. These rates are pessimistic since they only apply to single reads and do not include calibration of the pore model to specific nanopores.

cs.IT

Stochastic Channel Models for Satellite Mega-Constellations

A general satellite channel model is proposed for communications between a rapidly moving low Earth orbit (LEO) satellite in a mega-constellation and a stationary user on Earth. The channel uses a non-homogeneous binomial point process (NBPP) for modelling the satellite positions, marked with an ascending/descending binary random variable for modelling the satellite directions. Using the marked NBPP, we derive the probability distributions of power gain, propagation delay, and Doppler shift, resulting in a stochastic signal propagation model for the mega-constellation geometry in isolation of other effects. This forms the basis for our proposed channel model as a randomly time-varying channel. The scattering function of this channel is derived to characterise how the received power is spread in the delay-Doppler domain. Global channel parameters such as path loss and channel spread are analysed in terms of the scattering function. The channel statistics and the global channel parameters closely match realistic orbit simulations of the Starlink constellation.

cs.IT

On noisy duplication channels with Markov sources

Channels with noisy duplications have recently been used to model the nanopore sequencer. This paper extends some foundational information-theoretic results to this new scenario. We prove the asymptotic equipartition property (AEP) for noisy duplication processes based on ergodic Markov processes. A consequence is that the noisy duplication channel is information stable for ergodic Markov sources, and therefore the channel capacity constrained to Markov sources is the Markov-constrained Shannon capacity. We use the AEP to estimate lower bounds on the capacity of the binary symmetric channel with Bernoulli and geometric duplications using Monte Carlo simulations. In addition, we relate the AEP for noisy duplication processes to the AEP for hidden semi-Markov processes.

cs.IT

Finite-State Semi-Markov Channels for Nanopore Sequencing

Nanopore sequencing is an emerging DNA sequencing technology that has been proposed for use in DNA storage systems. We propose the noisy nanopore channel model for nanopore sequencing. This model captures duplications, inter-symbol interference, and noisy measurements by concatenating an i.i.d. duplication channel with a finite-state semi-Markov channel. Compared to previous models, this channel models the dominant distortions of the nanopore while remaining tractable. Anticipating future coding schemes, we derive MAP detection algorithms and estimate achievable rates. Given that finite-state semi-Markov channels are a subclass of channels with memory, we conjecture that the achievable rate of the noisy nanopore channel can be optimised using a variation of the generalised Blahut-Arimoto algorithm.

cs.IT