2,195 research outputs found
Next Generation M2M Cellular Networks: Challenges and Practical Considerations
In this article, we present the major challenges of future machine-to-machine
(M2M) cellular networks such as spectrum scarcity problem, support for
low-power, low-cost, and numerous number of devices. As being an integral part
of the future Internet-of-Things (IoT), the true vision of M2M communications
cannot be reached with conventional solutions that are typically cost
inefficient. Cognitive radio concept has emerged to significantly tackle the
spectrum under-utilization or scarcity problem. Heterogeneous network model is
another alternative to relax the number of covered users. To this extent, we
present a complete fundamental understanding and engineering knowledge of
cognitive radios, heterogeneous network model, and power and cost challenges in
the context of future M2M cellular networks
Sparse Message Passing Based Preamble Estimation for Crowded M2M Communications
Due to the massive number of devices in the M2M communication era, new
challenges have been brought to the existing random-access (RA) mechanism, such
as severe preamble collisions and resource block (RB) wastes. To address these
problems, a novel sparse message passing (SMP) algorithm is proposed, based on
a factor graph on which Bernoulli messages are updated. The SMP enables an
accurate estimation on the activity of the devices and the identity of the
preamble chosen by each active device. Aided by the estimation, the RB
efficiency for the uplink data transmission can be improved, especially among
the collided devices. In addition, an analytical tool is derived to analyze the
iterative evolution and convergence of the SMP algorithm. Finally, numerical
simulations are provided to verify the validity of our analytical results and
the significant improvement of the proposed SMP on estimation error rate even
when preamble collision occurs.Comment: submitted to ICC 2018 with 6 pages and 4 figure
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
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