Irregular Repetition Slotted ALOHA Research Articles

On the Minimum Average Age of Information in IRSA for Grant-Free mMTC

We consider the optimal design of the frame-based irregular repetition slotted ALOHA (IRSA) protocol for minimizing the average age of information (AAoI) in grant-free massive machine-type communications (mMTC). To this end, we first characterize the AAoI as a function of the number of user elements (UEs), the frame duration, and the repetition distribution of IRSA. We present this characterization for IRSA schemes with packet recovery at the end of frame and packet generation either at the beginning of the frame or just in time before first transmission in a frame. We also propose and characterize the AAoI of a novel early packet recovery method which further reduces the average age of information. In all cases, the analysis reveals that, as a function of normalized channel traffic (defined as the ratio of number of UEs to frame duration), the AAoI first decreases linearly due to more frequent updates received from the UEs, and increases sharply beyond a critical point due to packet recovery failures caused by collisions. We then consider the problem of minimizing AAoI by optimizing over the normalized channel traffic and repetition distribution for all the proposed sampling and recovery schemes. The optimization problem is challenging since the objective function is semi-analytical and can only be completely characterized using simulations. In an asymptotic regime where the number of UEs as well as the frame size is large, we characterize the AAoI using upper and lower bounds. We also obtain a locally optimal normalized channel traffic and repetition distribution using differential evolution. Based on the insights obtained from the asymptotic analysis, we also propose a pragmatic approach to obtain a normalized channel traffic and repetition distribution for AAoI reduction in the non-asymptotic case. Finally, we empirically show that our AAoI minimizing schemes outperform conventional throughput optimal schemes.

Modern Random Access: An Age of Information Perspective on Irregular Repetition Slotted ALOHA

Age of information (AoI) is gaining attention as a valuable performance metric for many IoT systems, in which a large number of devices report time-stamped updates to a central gateway. This is the case, for instance, of remote sensing, monitoring, or tracking, with broad applications in the industrial, vehicular, and environmental domain. In these settings, AoI provides insights that are complementary to those offered by throughput or latency, capturing the ability of the system to maintain an up-to-date view of the status of each transmitting device. From this standpoint, while a good understanding of the metric has been reached for point-to-point links, relatively little attention has been devoted to the impact that link layer solutions employed in IoT systems may have on AoI. In particular, no result is available for modern random access protocols, which have recently emerged as promising solutions to support massive machine-type communications. To start addressing this gap we provide in this paper the first study of the AoI of a scheme in this family, namely irregular repetition slotted ALOHA (IRSA). By means of a Markovian analysis, we track the AoI evolution at the gateway, prove that the process is ergodic, and derive a compact closed form expression for its stationary distribution. Leaning on this, we compute exact formulations for the average AoI and the age violation probability. The study reveals non-trivial design trade-offs for IRSA and highlights the key role played by the protocol operating frame size. Moreover, a comparison with the performance of a simpler slotted ALOHA strategy highlights a remarkable potential for modern random access schemes in terms of information freshness.

Energy Harvesting Irregular Repetition ALOHA With Replica Concatenation

In this paper, we consider an asynchronous random access scheme called irregular repetition ALOHA (IRA) as a generalization of contention resolution ALOHA (CRA) with varying repetitions. We present an asymptotic performance analysis of CRA and IRA on the collision channel for regular and irregular repetition rates. We also propose an improvement by merging the clean parts of packet replicas in partial collisions, and extend our analysis to this scenario as well. Specific designs of repetition distributions based on the new analysis show that the optimized solutions of irregular repetition slotted ALOHA (IRSA) perform well in both IRA and the enhanced scheme, and they considerably outperform the regular repetition distributions. We also introduce energy harvesting (EH) to both schemes as a practical and sustainable adaptation, where users are able to harvest energy and store it in their finite-capacity batteries. We model the battery state by a discrete-time Markov chain and derive an optimal transmission policy to maximize the asymptotic performance of the system. We provide comprehensive numerical results for both practical and asymptotic scenarios to verify the validity of the proposed analyses, and illustrate the benefits of the proposed systems.

Random Interleaving Multiplexing Based IRSA Random Access System for Satellite-Enabled Internet-of-Things

A random access framework based on random interleaving multiplexing (RIM) is proposed to further improve throughput for internet of things in satellite networks, which resort to the state-of-art physical layer techniques that can resolve multiple packet collisions issue. The interleavers are randomly selected by active devices from a set of available interleavers, which are used to differentiate signals of different devices sharing a subframe that consists of multiple time slots. The message passing detector (MPD) is utilized to decode collided packets. By means of transmission diversity and interference cancellation, the proposed scheme can be linked with the irregular repetition slotted ALOHA (IRSA), the RIM-IRSA protocol is proposed. The analysis of packet loss ratio (PLR) of the RIM-IRSA is given by using the density evolution method, and the optimal degree distributions are given. Simulation results show that the RIM-IRSA outperforms traditional IRSA protocol.

Optimal Irregular Repetition Slotted ALOHA Under Total Transmit Power Constraint in IoT-Oriented Satellite Networks

In this article, we propose an optimal irregular repetition slotted ALOHA (IRSA) under total transmit power constraint for random access (RA) in the Internet-of-Things (IoT)-oriented satellite networks, which is named as an optimal power-limited IRSA (PL-IRSA). In this proposal, the total transmit power for each satellite machine-type device (SMD) within a frame is considered to be the same and equally allocated into its multiple packet replicas. Due to a variant number of packet replicas, the transmit power of each packet replica for different SMDs may be different. The difference of transmit powers of packet replicas and path loss enhance the received power diversity, which is able to improve the throughput by using the capture effect. At the receiver side, we introduce a semi-analytical (SEA) model to approximate the physical-layer decoding and derive an asymptotic packet loss rate (PLR) based on this SEA model. From the derived results, an optimization problem is formulated and solved to find out the optimal degree distributions for different total transmit powers and code rates, which maximize the normalized system throughput. The simulation results demonstrate that the proposed optimal PL-IRSA can lead to significant performance improvement with respect to conventional ones.

Enhancing Irregular Repetition Slotted ALOHA with Polarization Diversity in LEO Satellite Networks

An enhanced irregular repetition slotted ALOHA (IRSA) protocol is proposed by using polarization characteristic of satellite link and MIMO detection in low earth orbit (LEO) satellite networks, which is dubbed polarized MIMO IRSA (PM-IRSA). In the proposed scheme, one or two packets in one slot can be decoded by employing polarized MIMO detection, and more than two collided packets in multiple slots which can construct the virtual MIMO model can be decoded by the MIMO detection algorithm. The performance of the proposed scheme is analyzed with the density evolution (DE) approach and the degree distribution is optimized to maximize the system throughput by using a differential evolution. Numerical results certify our analysis and show that the normalized throughput of the proposed PM-IRSA can achieve 1.89 bits/symbol.

Short Frame Length Approximation for IRSA

In this letter, we propose a short-frame (SF) approximation for the packet loss rate of Irregular Repetition Slotted ALOHA (IRSA) particularly suitable for very short frames, up to 50 slots. The reason for limiting the frame size is to allow low-latency communications, a typical requirement in Industrial Internet of Things (IIoT) applications. We extend the Error Floor approximation (EF) through a recursive evaluation of inter-related stopping sets (STs). The tighter approximation yields the user degree distribution that minimizes the packet loss rate (PLR). For a scenario with 10 slots and 5 users, the degree distribution optimized adopting the SF approximation results in a 20% lower PLR compared to the one optimized with the EF approximation.

Fast Q-learning for Improved Finite Length Performance of Irregular Repetition Slotted ALOHA

Fast Q-learning for Improved Finite Length Performance of Irregular Repetition Slotted ALOHA

Irregular repetition slotted ALOHA with total transmit power limitation

Irregular repetition slotted ALOHA with total transmit power limitation

Fast Q-Learning for Improved Finite Length Performance of Irregular Repetition Slotted ALOHA

In this paper, we study the problem of designing adaptive Medium Access Control (MAC) solutions for wireless sensor networks (WSNs) under the Irregular Repetition Slotted ALOHA (IRSA) protocol. In particular, we optimize the degree distribution employed by IRSA for finite frame sizes. Motivated by characteristics of WSNs, such as the restricted computational resources and partial observability, we model the design of IRSA as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP). We have theoretically analyzed our solution in terms of optimality of the learned IRSA design and derived guarantees for finding near-optimal policies. These guarantees are generic and can be applied in resource allocation problems that exhibit the waterfall effect , which in our setting manifests itself as a severe degradation in the overall throughput of the network above a particular channel load. Furthermore, we combat the inherent non-stationarity of the learning environment in WSNs by advancing classical Q-learning through the use of virtual experience (VE), a technique that enables the update of multiple state-action pairs per learning iteration and, thus, accelerates convergence. Our simulations confirm the superiority of our learning-based MAC solution compared to traditional IRSA and provide insights into the effect of WSN characteristics on the quality of learned policies.

Capacity Region of ALOHA Protocol for Heterogeneous IoT Networks

In an Internet of Things (IoT) network, heterogeneous users with different priorities and service requirements will co-exist. This makes scheduling access to the shared communication medium a major challenge. To tackle this challenge, we consider the application of irregular repetition slotted ALOHA (IRSA), one of the best-performing random access protocols for homogeneous networks, for a heterogeneous multiclass IoT network. To this end, centralized and distributed implementations of the IRSA for multiclass IoT networks is proposed. Then, we focus on finding the network performance boundaries by studying the set of feasible throughput values for each class achieved via IRSA, called the capacity region. In addition to identifying the capacity region, the average and maximum delay of the users’ packet delivery for both centralized and distributed IRSA are investigated. Our throughput and delay analysis reveals that the performance of distributed IRSA achieves that for the centralized implementation as the number of users increases. Further, we use our capacity region analysis to find the optimal IRSA strategy that maximizes the weighted sum-throughput of the network.

T22INVESTIGATION OF PATHWAY-BASED POLYGENIC RISK SCORES USING MACHINE LEARNING PREDICTION AND CLASSIFICATION SCHEMES

Random access protocols like ALOHA have been considered for machine-to-machine (M2M) communication in future networks for their simplicity of operation. This paper evaluates the performance of a Frame Slotted-ALOHA protocol that uses reservation and data packets (FSA-RDP), in a scenario where a controller collects data packets transmitted by a finite number of M2M devices. In FSA-RDP, frames of variable duration are divided in two parts, the reservation and data subframes. During the reservation subframe, active devices send short reservation packets to the controller. The controller assigns reserved slots in the data subframe to those devices that succeeded with the reservation. At devices, the FIFO service discipline and two queue management schemes, tail drop and push-out, have been considered. When the queue size is of one packet, we develop a discrete-time Markov chain to evaluate the protocol performance, including the cumulative distribution function of the delay of data packets that are successfully transmitted. Analytical results are validated by extensive simulations. The simulation model is also used to evaluate the system performance when larger queues are used. In addition, we study the impact that implementing Successive Interference Cancellation (SIC) at the controller has on the system performance. We also evaluate the performance of implementing SIC at the controller together with Irregular Repetition Slotted ALOHA (IRSA) to send the reservation packets. Numerical results show that the protocol efficiency of FSA-RDP is between one and two orders of magnitude larger than the efficiency of conventional Frame Slotted ALOHA, when a perfect channel is assumed. In more realistic channel environments, the use of SIC brings an important performance boost.

Irregular Repetition Slotted ALOHA With Energy Harvesting Nodes

We propose an irregular repetition slotted ALOHA (IRSA) based uncoordinated random access scheme for energy harvesting (EH) nodes. Specifically, we consider the case in which each user has a battery that is recharged with harvested energy from the environment in a probabilistic manner. We analyze this scheme starting with a unit-sized battery at the nodes and extend the analysis to the case of a finite-sized battery. For both scenarios, we derive the asymptotic throughput expressions and obtain the optimized probability distributions for the number of packet replicas of the users. We demonstrate that for the case of IRSA with EH nodes, these optimized distributions perform considerably better than the alternatives, including slotted ALOHA (SA), contention resolution diversity slotted ALOHA (CRDSA), and IRSA, which do not take into account the EH process for both asymptotic and finite frame length scenarios.

Multisatellite Cooperative Random Access Scheme in Low Earth Orbit Satellite Networks

Multisatellite cooperative random access (MSC-RA) scheme is proposed in low earth orbit (LEO) satellite networks. In the scheme, a packet structure based on single carrier interleaved frequency division multiple access (SC-IFDMA) is designed to overcome the effect of users’ propagation delays on the received signals at satellite nodes, which ensures the synchronization of received signals. The transmission model from multiple terminals to multiple satellite nodes in a slot can be equivalent to a virtual multi-input multioutput model, and MSC detection is employed to decode multiple collided packets. The MSC detection can be applied to slotted ALOHA (SA), contention resolution diversity slotted ALOHA (CRDSA), CRDSA-3, and irregular repetition slotted ALOHA (IRSA) protocols, which are dubbed MSC-SA, MSC-CRDSA, MSC-CRDSA-3, and MSC-IRSA, respectively. At the gateway station, the MSC detection and iterative interference cancellation processing are alternately conducted for multiple collided packets at satellite nodes. The performance of these MSC-RA schemes is evaluated via mathematical analysis and computer simulation in terms of throughput, stability and energy efficiency. Simulation results show that MSC-SA, MSC-CRDSA, MSC-CRDSA-3, and MSC-IRSA schemes significantly outperform conventional ones, and the MSC-CRDSA scheme is superior to MSC-SA, MSC-CRDSA-3 and MSC-IRSA schemes.

NOMA-Based Irregular Repetition Slotted ALOHA for Satellite Networks

In this letter, a non-orthogonal multiple access (NOMA) scheme is employed for irregular repetition slotted ALOHA (IRSA). Specifically, packet replicas are transmitted with discrete power levels, which are pre-determined by the NOMA scheme. In this case, most packet collisions can be resolved in the power domain, contributing to a much lower packet loss rate. Density evolution analysis is formulated and the degree distributions are optimized for different numbers of power levels. The simulation results validate our analysis and show that the proposed scheme can outperform existing IRSA schemes.

Performance evaluation of framed slotted ALOHA with reservation packets and succesive interference cancelation for M2M networks

Random access protocols like ALOHA have been considered for machine-to-machine (M2M) communication in future networks for their simplicity of operation. This paper evaluates the performance of a Frame Slotted-ALOHA protocol that uses reservation and data packets (FSA-RDP), in a scenario where a controller collects data packets transmitted by a finite number of M2M devices. In FSA-RDP, frames of variable duration are divided in two parts, the reservation and data subframes. During the reservation subframe, active devices send short reservation packets to the controller. The controller assigns reserved slots in the data subframe to those devices that succeeded with the reservation. At devices, the FIFO service discipline and two queue management schemes, tail drop and push-out, have been considered. When the queue size is of one packet, we develop a discrete-time Markov chain to evaluate the protocol performance, including the cumulative distribution function of the delay of data packets that are successfully transmitted. Analytical results are validated by extensive simulations. The simulation model is also used to evaluate the system performance when larger queues are used. In addition, we study the impact that implementing Successive Interference Cancellation (SIC) at the controller has on the system performance. We also evaluate the performance of implementing SIC at the controller together with Irregular Repetition Slotted ALOHA (IRSA) to send the reservation packets. Numerical results show that the protocol efficiency of FSA-RDP is between one and two orders of magnitude larger than the efficiency of conventional Frame Slotted ALOHA, when a perfect channel is assumed. In more realistic channel environments, the use of SIC brings an important performance boost.

LDMAC: A propagation delay-aware MAC scheme for long-distance UAV networks

Unmanned aerial vehicles (UAVs) are gaining increasing importance in military and civilian applications. A challenging problem is the efficient communication between multiple UAVs and terrestrial base station (BS), where a wireless link has to cover hundreds of miles. These long-distance wireless networks suffer from heterogeneous and varying propagation delays, making conventional medium access control (MAC) protocols inappropriate. In this paper, a propagation delay-aware access scheme, LDMAC, is designed for long-distance UAV networks. It is a joint design of random access and collision-free time slot allocation. UAVs contend for time slots based on improved Irregular Repetition Slotted Aloha (IRSA), and subsequently the BS makes a collision-free, fair and optimized time slot allocation with temporal reuse. Both of the processes take full advantage of propagation delay to efficiently improve system throughput. Simulation results show that LDMAC achieves up to 30% improvement over IRSA with respect to successful decoding rate (SDR), and outperforms competing protocols that include IRSA and dynamic time division multiple access (D-TDMA) in terms of throughput in mobile wireless networks.

Finite-Length Analysis of Irregular Repetition Slotted ALOHA in the Waterfall Region

A finite-length analysis is introduced for irregular repetition slotted ALOHA (IRSA) that enables to accurately estimate its performance in the moderate-to-high packet loss probability regime, i.e., in the so-called waterfall region. The analysis is tailored to the collision channel model, which enables mapping the description of the successive interference cancellation process onto the iterative erasure decoding of low-density parity-check codes. The analysis provides accurate estimates of the packet loss probability of IRSA in the waterfall region as demonstrated by Monte Carlo simulations.

On the Modeling and Performance Assessment of Random Access With SIC

In this paper, we review the key figures of merit to assess the performance of advanced random access (RA) schemes exploiting physical layer coding, repetitions, and collision resolution techniques. We then investigate RA modeling aspects and their impact on the figures of merit for the exemplary advanced RA schemes: contention resolution diversity slotted ALOHA (CRDSA), irregular repetition slotted ALOHA (IRSA), coded slotted ALOHA (CSA) and enhanced spread-spectrum ALOHA (E-SSA). We show that the typical simplifications of the reception model when used to optimize RA schemes lead to inaccurate findings, both in terms of parameter optimization and figures of merit, such as the packet loss ratio (PLR) and throughput. We also derive a generic RA energy efficiency model able to compare the schemes in terms of the energy required to transmit a packet. The combination of achievable RA throughput at the target PLR and energy efficiency, for the same average user power investment per frame and occupied bandwidth, shows that E-SSA, which is an unslotted scheme, provides the best overall performance, while, in terms of the slotted schemes, CRDSA outperforms the more elaborated IRSA and CSA. This surprising results are due to the fact that the IRSA and CSA optimization has so far been performed using RA channel models that are not accurately reflecting the physical layer receiver behavior. We conclude by providing insights on how to include more accurate reception models in the IRSA and CSA design and optimization.

Prioritized Random MAC Optimization Via Graph-Based Analysis

Motivated by the analogy between successive interference cancellation and iterative belief-propagation on erasure channels, irregular repetition slotted ALOHA (IRSA) strategies have received a lot of attention in the design of medium access control protocols. In this work, we consider generic systems where sources in different importance classes compete for a common channel. We propose a new prioritized IRSA algorithm and derive the probability to correctly resolve collisions for data from each source class. We then make use of our theoretical analysis to formulate a new optimization problem for selecting the transmission strategies of heterogenous sources. We optimize both the replication probability per class and the source rate per class, in such a way that the overall system utility is maximized. We then propose a heuristic-based algorithm for the selection of the transmission strategy, which is built on intrinsic characteristics of the iterative decoding methods adopted for recovering from collisions. Experimental results validate the accuracy of the theoretical study and show the gain of well-chosen prioritized transmission strategies for transmission of data from heterogenous classes over shared wireless channels.