Related papers: Centralized Power Control in Cognitive Radio Netwo…
Spectrum shortage is a fundamental problem in wireless networks and this problem becomes increasingly acute with the rapid proliferation of wireless devices. To address this problem, spectrum sharing in the context of cognitive radio…
The recent advancement in deep learning (DL) for automatic modulation classification (AMC) of wireless signals has encouraged numerous possible applications on resource-constrained edge devices. However, developing optimized DL models…
The growth of wireless devices affects the availability of limited frequencies or spectrum bands as it has been known that spectrum bands are a natural resource that cannot be added. Meanwhile, the licensed frequencies are idle most of the…
The proliferation of the Internet of Things (IoTs) and pervasive use of many different types of mobile computing devices make wireless communication spectrum a precious resource. In order to accommodate the still fast increasing number of…
In this paper, a safe and learning-based control framework for model predictive control (MPC) is proposed to optimize nonlinear systems with a non-differentiable objective function under uncertain environmental disturbances. The control…
Secured opportunistic Medium Access Control (MAC) and complexity reduction in channel estimation are proposed in the Cross layer design Cognitive Radio Networks deploying the secured dynamic channel allocation from the endorsed channel…
Model Predictive Control (MPC) provides an optimal control solution based on a cost function while allowing for the implementation of process constraints. As a model-based optimal control technique, the performance of MPC strongly depends…
Powerful spectrum decision schemes enable cognitive radios (CRs) to find transmission opportunities in spectral resources allocated exclusively to the primary users. One of the key effecting factor on the CR network throughput is the…
Regression test case prioritization (RTCP) aims to improve the rate of fault detection by executing more important test cases as early as possible. Various RTCP techniques have been proposed based on different coverage criteria. Among them,…
Spectrum efficiency and energy efficiency are two critical issues in designing wireless networks. Through dynamic spectrum access, cognitive radios can improve the spectrum efficiency and capacity of wireless networks. On the other hand,…
In this paper, we propose a low-complexity, secrecy capacity achieving polar coding scheme for the cognitive interference channel with confidential messages (CICC) under the strong secrecy criterion. Existing polar coding schemes for…
Cognitive radio (CR) technology enables an intelligent wireless communication system. CR provides an efficient solution for the inefficient spectrum utilization by allowing dynamic and opportunistic spectrum access. In designing CR…
In this paper, the problem of optimal power allocation in Cognitive Radio (CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on providing limited feedback solutions aiming at maximizing the secondary system rate…
Model predictive control (MPC) is a promising technique for motion cueing in driving simulators, but its high computation time limits widespread real-time application. This paper proposes a hybrid algorithm that combines filter-based and…
Cognitive radio networks (CRNs) are considered a promising solution for spectrum resources scarcity and efficient channel utilization. In this letter, multi-dimensional analytical Markov model based on reservation channel access scheme and…
A robust model predictive control (MPC) method is presented for linear, time-invariant systems affected by bounded additive disturbances. The main contribution is the offline design of a disturbance-affine feedback gain whereby the…
We consider a cognitive radio network consisting of a primary cellular system and a secondary cognitive machine-to-machine (M2M) system, and study the throughput enhancement problem of the latter system employing universal-filtered…
Interference coordination improves data rates and reduces outages in cellular networks. Accurately evaluating the gains of coordination, however, is contingent upon using a network topology that models realistic cellular deployments. In…
This paper presents a video coding scheme that combines traditional optimization methods with deep learning methods based on the Enhanced Compression Model (ECM). In this paper, the traditional optimization methods adaptively adjust the…
This paper investigates the compress-and-forward scheme for an uplink cloud radio access network (C-RAN) model, where multi-antenna base-stations (BSs) are connected to a cloud-computing based central processor (CP) via capacity-limited…