437 research outputs found
Probabilistic Rateless Multiple Access for Machine-to-Machine Communication
Future machine to machine (M2M) communications need to support a massive
number of devices communicating with each other with little or no human
intervention. Random access techniques were originally proposed to enable M2M
multiple access, but suffer from severe congestion and access delay in an M2M
system with a large number of devices. In this paper, we propose a novel
multiple access scheme for M2M communications based on the capacity-approaching
analog fountain code to efficiently minimize the access delay and satisfy the
delay requirement for each device. This is achieved by allowing M2M devices to
transmit at the same time on the same channel in an optimal probabilistic
manner based on their individual delay requirements. Simulation results show
that the proposed scheme achieves a near optimal rate performance and at the
same time guarantees the delay requirements of the devices. We further propose
a simple random access strategy and characterized the required overhead.
Simulation results show the proposed approach significantly outperforms the
existing random access schemes currently used in long term evolution advanced
(LTE-A) standard in terms of the access delay.Comment: Accepted to Publish in IEEE Transactions on Wireless Communication
On the Fundamental Limits of Random Non-orthogonal Multiple Access in Cellular Massive IoT
Machine-to-machine (M2M) constitutes the communication paradigm at the basis
of Internet of Things (IoT) vision. M2M solutions allow billions of multi-role
devices to communicate with each other or with the underlying data transport
infrastructure without, or with minimal, human intervention. Current solutions
for wireless transmissions originally designed for human-based applications
thus require a substantial shift to cope with the capacity issues in managing a
huge amount of M2M devices. In this paper, we consider the multiple access
techniques as promising solutions to support a large number of devices in
cellular systems with limited radio resources. We focus on non-orthogonal
multiple access (NOMA) where, with the aim to increase the channel efficiency,
the devices share the same radio resources for their data transmission. This
has been shown to provide optimal throughput from an information theoretic
point of view.We consider a realistic system model and characterise the system
performance in terms of throughput and energy efficiency in a NOMA scenario
with a random packet arrival model, where we also derive the stability
condition for the system to guarantee the performance.Comment: To appear in IEEE JSAC Special Issue on Non-Orthogonal Multiple
Access for 5G System
Random Access Analysis for Massive IoT Networks Under a New Spatio-Temporal Model: A Stochastic Geometry Approach
Massive Internet of Things (mIoT) has provided an auspicious opportunity to
build powerful and ubiquitous connections that faces a plethora of new
challenges, where cellular networks are potential solutions due to their high
scalability, reliability, and efficiency. The Random Access CHannel (RACH)
procedure is the first step of connection establishment between IoT devices and
Base Stations (BSs) in the cellular-based mIoT network, where modelling the
interactions between static properties of physical layer network and dynamic
properties of queue evolving in each IoT device are challenging. To tackle
this, we provide a novel traffic-aware spatio-temporal model to analyze RACH in
cellular-based mIoT networks, where the physical layer network is modelled and
analyzed based on stochastic geometry in the spatial domain, and the queue
evolution is analyzed based on probability theory in the time domain. For
performance evaluation, we derive the exact expressions for the preamble
transmission success probabilities of a randomly chosen IoT device with
different RACH schemes in each time slot, which offer insights into
effectiveness of each RACH scheme. Our derived analytical results are verified
by the realistic simulations capturing the evolution of packets in each IoT
device. This mathematical model and analytical framework can be applied to
evaluate the performance of other types of RACH schemes in the cellular-based
networks by simply integrating its preamble transmission principle
Data Aggregation in Capillary Networks for Machine-to-Machine Communications
As machine-to-machine applications using cellular systems become pervasive, it is an important concern that their deployment does not jeopardize the performance of the cellular systems. Support for a massive number of machines brings technical challenges affecting the performance of the random access channel and efficiency of radio resource allocation. Capillary networks are considered as an extensions to the cellular systems for providing large-scale connectivity. This paper proposes an aggregation scheme for capillary networks connected to the LTE network to improve their communication efficiency. A gateway, an intermediate unit between machines and the base station, aggregates packets from the machines during a predefined time, and then delivers them to the LTE network. In addition, this paper analyzes the trade-offs between random access interaction, resource allocation, and communication latency. Results reveals that accepting the extra latency for accumulating packets can significantly reduce the random access requests and the required resources for the data transmissions.Peer reviewe
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