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Register a new userA General Characterization of Sync Word for Asynchronous Communication
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R M Sundaram
Publication date
2016
fields
Informatics Engineering
and research's language is
English
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We study a problem of sequential frame synchronization for a frame transmitted uniformly in $A$ slots. For a discrete memoryless channel (DMC), Venkat Chandar et al showed that the frame length $N$ must scale with $A$ as $e^{N alpha(Q)} > A$ for the frame synchronization error to go to zero (asymptotically with $A$). Here, $Q$ denotes the transition probabilities of the DMC and $alpha(Q)$, defined as the synchronization threshold, characterizes the scaling needed of $N$ for asymptotic error free frame synchronization. We show that the asynchronous communication framework permits a natural tradeoff between the sync frame length $N$ and the channel (usually parameterised by the input). For an AWGN channel, we study this tradeoff between the sync frame length $N$ and the input symbol power $P$ and characterise the scaling needed of the sync frame energy $E = N P$ for optimal frame synchronisation.
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In cite{Chandar2008}, Chandar et al studied a problem of sequential frame synchronization for a frame transmitted randomly and uniformly among $A$ slots. For a discrete memory-less channel (DMC), they showed that the frame length $N$ must scale as $e^{alpha(Q)N}>A$ for the frame detection error to go to zero asymptotically with $A$. $alpha(Q)$ is the synchronization threshold and $Q$ is channel transition probability. We study the sequential frame synchronisation problem for a fading channel and additive noise and seek to characterise the effect of fading. For a discrete ON-OFF fading channel (with ON probability $p$) and additive noise (with channel transition probabilities $Q_n$), we characterise the synchronisation threshold of the composite channel $alpha(Q)$ and show that $alpha(Q)leq p,alpha(Q_n)$. We then characterize the synchronization threshold for Rayleigh fading and AWGN channel as a function of channel parameters. The asynchronous framework permits a trade-off between sync frame length, $N$, and channel, $Q$, to support asynchronism. This allows us to characterize the synchronization threshold with sync frame energy instead of sync frame length.
We characterize the practical photon-counting receiver in optical scattering communication with finite sampling rate and electrical noise. In the receiver side, the detected signal can be characterized as a series of pulses generated by photon-multiplier (PMT) detector and held by the pulse-holding circuits, which are then sampled by the analog-to-digit convertor (ADC) with finite sampling rate and counted by a rising-edge pulse detector. However, the finite small pulse width incurs the dead time effect that may lead to sub-Poisson distribution on the recorded pulses. We analyze first-order and second-order moments on the number of recorded pulses with finite sampling rate at the receiver side under two cases where the sampling period is shorter than or equal to the pulse width as well as longer than the pulse width. Moreover, we adopt the maximum likelihood (ML) detection. In order to simplify the analysis, we adopt binomial distribution approximation on the number of recorded pulses in each slot. A tractable holding time and decision threshold selection rule is provided aiming to maximize the minimal Kullback-Leibler (KL) distance between the two distributions. The performance of proposed sub-Poisson distribution and the binomial approximation are verified by the experimental results. The equivalent arrival rate and holding time predicted by the of sub-Poisson model and the associated proposed binomial distribution on finite sampling rate and the electrical noise are validated by the simulation results. The proposed the holding time and decision threshold selection rule performs close to the optimal one.
This work addresses the physical layer channel code design for an uncoordinated, frame- and slot-asynchronous random access protocol. Starting from the observation that collisions between two users yield very specific interference patterns, we define a surrogate channel model and propose different protograph low-density parity-check code designs. The proposed codes are both tested in a setup where the physical layer is abstracted, as well as on a more realistic channel model, where finite-length physical layer simulations of the entire asynchronous random access scheme, including decoding are carried out. We find that the abstracted physical layer model overestimates the performance when short blocks are considered. Additionally, the optimized codes show gains in supported channel traffic - a measure of the number of terminals that can be concurrently accommodated on the channel - of around 17% at a packet loss rate of 10^{-2} w.r.t. off-the-shelf codes.
This paper considers the massive connectivity problem in an asynchronous grant-free random access system, where a huge number of devices sporadically transmit data to a base station (BS) with imperfect synchronization. The goal is to design algorithms for joint user activity detection, delay detection, and channel estimation. By exploiting the sparsity on both user activity and delays, we formulate a hierarchical sparse signal recovery problem in both the single-antenna and the multiple-antenna scenarios. While traditional compressed sensing algorithms can be applied to these problems, they suffer high computational complexity and often require the perfect statistical information of channel and devices. This paper solves these problems by designing the Learned Approximate Message Passing (LAMP) network, which belongs to model-driven deep learning approaches and ensures efficient performance without tremendous training data. Particularly, in the multiple-antenna scenario, we design three different LAMP structures, namely, distributed, centralized and hybrid ones, to balance the performance and complexity. Simulation results demonstrate that the proposed LAMP networks can significantly outperform the conventional AMP method thanks to their ability of parameter learning. It is also shown that LAMP has robust performance to the maximal delay spread of the asynchronous users.
We show a near optimal direct-sum theorem for the two-party randomized communication complexity. Let $fsubseteq X times Ytimes Z$ be a relation, $varepsilon> 0$ and $k$ be an integer. We show, $$mathrm{R}^{mathrm{pub}}_varepsilon(f^k) cdot log(mathrm{R}^{mathrm{pub}}_varepsilon(f^k)) ge Omega(k cdot mathrm{R}^{mathrm{pub}}_varepsilon(f)) enspace,$$ where $f^k= f times ldots times f$ ($k$-times) and $mathrm{R}^{mathrm{pub}}_varepsilon(cdot)$ represents the public-coin randomized communication complexity with worst-case error $varepsilon$. Given a protocol $mathcal{P}$ for $f^k$ with communication cost $c cdot k$ and worst-case error $varepsilon$, we exhibit a protocol $mathcal{Q}$ for $f$ with external-information-cost $O(c)$ and worst-error $varepsilon$. We then use a message compression protocol due to Barak, Braverman, Chen and Rao [2013] for simulating $mathcal{Q}$ with communication $O(c cdot log(ccdot k))$ to arrive at our result. To show this reduction we show some new chain-rules for capacity, the maximum information that can be transmitted by a communication channel. We use the powerful concept of Nash-Equilibrium in game-theory, and its existence in suitably defined games, to arrive at the chain-rules for capacity. These chain-rules are of independent interest.
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