Related papers: Massive Machine Type Communication Pilot-Hopping S…
The problem of communication among nodes in an \emph{extended network} is considered, where radio power decay and interference are limiting factors. It has been shown previously that, with simple multi-hopping, the achievable total…
To enable massive machine type communication (mMTC), data aggregation is a promising approach to reduce the congestion caused by a massive number of machine type devices (MTDs). In this work, we consider a two-phase cellular-based mMTC…
It is common practice to use large computational resources to train neural networks, as is known from many examples, such as reinforcement learning applications. However, while massively parallel computing is often used for training models,…
Modern wireless machine-to-machine-type communications aim to provide both ultra reliability and low latency, stringent requirements that appear to be mutually exclusive. From the noisy channel coding theorem, we know that reliable…
In massive machine-type communications (mMTC), grant-free access is a key enabler for a massive number of users to be connected to a base station with low signaling overhead and low latency. In this paper, a two-stage genetic algorithm (GA)…
Massive machine-type communications (mMTC) or massive access is a critical scenario in the fifth generation (5G) and the future cellular network. With the surging density of devices from millions to billions, unique pilot allocation becomes…
Interference management has become a key factor in regulating transmissions in wireless communication networks. To support effective interference management schemes, it can be essential to have prior knowledge about the network topology. In…
Future cellular networks will support a massive number of devices as a result of emerging technologies such as Internet-of-Things and sensor networks. Enhanced by machine type communication (MTC), low-power low-complex devices in the order…
Grant-free transmission is considered as a promising technology to support sporadic data transmission in massive machine-type communications (mMTC). Due to the distributed manner, high collision probability is an inherent drawback of…
We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN) for detecting a stationary random process distributed both in space and time with circularly-symmetric complex Gaussian distribution under the…
In this paper we introduce an optimized Markov Chain Monte Carlo (MCMC) technique for solving the integer least-squares (ILS) problems, which include Maximum Likelihood (ML) detection in Multiple-Input Multiple-Output (MIMO) systems. Two…
Data aggregation is a promising approach to enable massive machine-type communication (mMTC). Here, we first characterize the aggregation phase where a massive number of machine-type devices transmits to their respective aggregator. By…
Machine-to-machine (M2M) wireless systems aim to provide ubiquitous connectivity between machine type communication (MTC) devices without any human intervention. Given the exponential growth of MTC traffic, it is of utmost importance to…
In this paper, we propose low complexity algorithms based on Markov chain Monte Carlo (MCMC) technique for signal detection and channel estimation on the uplink in large scale multiuser multiple input multiple output (MIMO) systems with…
There is an increasing demand of massive machine-type communication (mMTC) to provide scalable access for a large number of devices, which has prompted extensive investigation on grant-free massive random access (RA) in 5G and beyond…
We propose efficient and low-complexity multiuser detection (MUD) algorithms for Gaussian multiple access channel (G-MAC) for short-packet transmission in massive machine type communications. To do so, we first formulate the G-MAC MUD…
Grant-free massive access is an important technique for supporting massive machine-type communications (mMTC) for Internet-of-Things (IoT). Two important features in grant-free massive access are low-complexity devices and short-packet data…
This paper presents an estimation approach within the framework of uplink massive machine-type communications (mMTC) that considers the energy limitations of the devices. We focus on a scenario where a group of sensors observe a set of…
We introduce Glinthawk, an architecture for offline Large Language Model (LLM) inference. By leveraging a two-tiered structure, Glinthawk optimizes the utilization of the high-end accelerators ("Tier 1") by offloading the attention…
For systems and devices, such as cognitive radio and networks, that need to be aware of available frequency bands, spectrum sensing has an important role. A major challenge in this area is the requirement of a high sampling rate in the…