On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel

Romanov, Elad; Ordentlich, Or

doi:10.3390/e23050605

Cited by 6 publications

(3 citation statements)

References 83 publications

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“…The use of scheduling and feedback for massive connectivity has already been considered in several recent works [18], [19], but for a different context of unsourced random access [20]- [22], where user identification is abstracted, and the goal is to decode a list of transmitted messages. The unsourced paradigm is most suitable when the messages themselves, rather than the identities of the transmitters, are important.…”

Section: A Related Workmentioning

confidence: 99%

Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems

Kang

2022

IEEE Trans. Commun.

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Massive machine-type communications protocols have typically been designed under the assumption that coordination between users requires significant communication overhead and is thus impractical. Recent progress in efficient activity detection and collision-free scheduling, however, indicates that the cost of coordination can be much less than the naive scheme for scheduling. This work considers a scenario in which a massive number of devices with sporadic traffic seek to access a massive multiple-input multiple-output (MIMO) base-station (BS) and explores an approach in which device activity detection is followed by a single common feedback broadcast message, which is used both to schedule the active users to different transmission slots and to assign orthogonal pilots to the users for channel estimation. The proposed coordinated communication scheme is compared to two prevalent contention-based schemes: coded pilot access, which is based on the principle of coded slotted ALOHA, and an approximate message passing scheme for joint user activity detection and channel estimation. Numerical results indicate that scheduled massive access provides significant gains in the number of successful transmissions per slot and in sum rate, due to the reduced interference, at only a small cost of feedback.

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Section: A Related Workmentioning

confidence: 99%

Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems

Kang

2022

IEEE Trans. Commun.

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“…The higher-order binary Markov random field (HoMRF) is a non-convex optimization model widely used in the fields of economy, information theory, quantum computing, machine learning and image analysis [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ]. Recently, a new order reduction method has been developed to optimize HoMRF energies.…”

Section: Introductionmentioning

confidence: 99%

An Order Reduction Design Framework for Higher-Order Binary Markov Random Fields

Chen

Yang

2023

Entropy

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The order reduction method is an important approach to optimize higher-order binary Markov random fields (HoMRFs), which are widely used in information theory, machine learning and image analysis. It transforms an HoMRF into an equivalent and easier reduced first-order binary Markov random field (RMRF) by elaborately setting the coefficients and auxiliary variables of RMRF. However, designing order reduction methods is difficult, and no previous study has investigated this design issue. In this paper, we propose an order reduction design framework to study this problem for the first time. Through study, we find that the design difficulty mainly lies in that the coefficients and variables of RMRF must be set simultaneously. Therefore, the proposed framework decomposes the design difficulty into two processes, and each process mainly considers the coefficients or auxiliary variables of RMRF. Some valuable properties are also proven. Based on our framework, a new family of 14 order reduction methods is provided. Experiments, such as synthetic data and image denoising, demonstrate the superiority of our method.

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“…The finite-length achievability random coding bound to the massive random access problem [ 28 ]—later improved in [ 29 ]—opened the door to a new and flourishing wave of interest in RA solutions. Two main classes arise as promising novel attempts: the first concerns itself with compressed sensing-based solutions represented by works such as [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ], while the second class relies on conventional channel code-based schemes characterized by works such as [ 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. By no means we consider to have given an exhaustive listing of each class.…”

Section: Introductionmentioning

confidence: 99%

Analytical Model of ALOHA and Time- and Frequency-Asynchronous ALOHA with Forward Error Correction for IoT Systems

Clazzer

Grec

2022

Sensors

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The blooming of internet of things (IoT ) services calls for a paradigm shift in the design of communications systems. Short data packets sporadically transmitted by a multitude of low-cost low-power terminals require a radical change in relevant aspects of the protocol stack. For example, scheduling-based approaches may become inefficient at the medium access (MAC ) layer, and alternatives such as uncoordinated access policies may be preferred. In this context random access (RA ) in its simplest form, i.e., additive links on-line Hawaii area (ALOHA ), may again become attractive as also proved by a number of technologies adopting it. The use of forward error correction (FEC ) can improve its performance, yet a comprehensive analytical model including this aspect is still missing. In this paper, we provide a first attempt by deriving exact expressions for the packet loss rate and spectral efficiency of ALOHA with FEC , and extend the result also to time- and frequency-asynchronous ALOHA aided by FEC . We complement our study with extensive evaluations of the expressions for relevant cases of study, including an IoT system served by low-Earth orbit (LEO ) satellites. Non-trivial outcomes show how time- and frequency-asynchronous ALOHA particularly benefit from the presence of FEC and become competitive with ALOHA.

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On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel

Cited by 6 publications

References 83 publications

Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems

Scheduling Versus Contention for Massive Random Access in Massive MIMO Systems

An Order Reduction Design Framework for Higher-Order Binary Markov Random Fields

Analytical Model of ALOHA and Time- and Frequency-Asynchronous ALOHA with Forward Error Correction for IoT Systems

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