相关论文: Study of Adaptive Activity-Aware Iterative Detecti…

To realize orthogonal frequency division multiplexing (OFDM)-based grant-free access for wideband systems under frequency-selective fading, existing device activity detection and channel estimation methods need substantial accuracy…

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…

Achieving high image quality is an important aspect in an increasing number of wireless multimedia applications. These applications require resource efficient error correction hardware to detect and correct errors introduced by the…

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art…

We present a new analytical framework on the uplink data detection for massive multiple-input multiple-output systems with 1-bit analog-to-digital converters (ADCs). We first characterize the expected values of the soft-estimated symbols…

This paper provides a solution for the activity detection and channel estimation problem in grant-free access with correlated device activity patterns. In particular, we consider a machine-type communications (MTC) network operating in…

In this paper, we consider a simple coding scheme for spatial modulation (SM), where the same set of active transmit antennas is repeatedly used over consecutive multiple transmissions. Based on a Gaussian approximation, an approximate…

This paper investigates multi-target detection in an integrated sensing and communication (ISAC) system within a cell-free massive MIMO (CF-mMIMO) framework. We adopt a user-centric approach for communication user equipments (UEs) and a…

This paper presents a learning-based approach to detecting failures in reactive systems. The technique is based on inferring models of multiple implementations of a common specification which are pair-wise cross-checked for equivalence. Any…

This paper presents a low complexity detector for multiple-input multiple-output (MIMO) systems based on the recently proposed orthogonal time frequency space (OTFS) modulation. In the proposed detector, the copies of the transmitted…

A canonical scenario in Machine-Type Communications (MTC) is the one featuring a large number of devices, each of them with sporadic traffic. Hence, the number of served devices in a single LTE cell is not determined by the available…

Massive Machine-Type Communications (mMTC) are one of the three types of services that should be supported by 5G networks. These are distinguished by the need to serve a large number of devices which are characterized by nonintensive…

Many current traffic monitoring systems employ deep packet inspection (DPI) in order to analyze network traffic. These systems include intrusion detection systems, software for network traffic accounting, traffic classification, or systems…

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…

This paper considers sparse device activity detection for cellular machine-type communications with non-orthogonal signatures using the approximate message passing algorithm. This paper compares two network architectures, massive…

Grant-free random access and uplink non-orthogonal multiple access (NOMA) have been introduced to reduce transmission latency and signaling overhead in massive machine-type communication (mMTC). In this paper, we propose two novel…

Feasibility of using unlicensed spectrum for ultra reliable low latency communications (URLLC) is still a question for beyond 5G wireless networks. Low latency access to the channel and efficiently sharing spectrum among the multiple users…

Approximating nonlinear systems as linear ones is a common workaround to apply control tools tailored for linear systems. This motivates our present work where we developed a data-driven model predictive controller (MPC) based on the…

A dual adaptive model predictive control (MPC) algorithm is presented for linear, time-invariant systems subject to bounded disturbances and parametric uncertainty in the state-space matrices. Online set-membership identification is…

This paper presents an uncertainty compensation-based robust adaptive model predictive control (MPC) framework for linear systems with both matched and unmatched nonlinear uncertainties subject to both state and input constraints. In…