Related papers: Optimizing Wi-Fi Channel Selection in a Dense Neig…
With the emergence of new technologies and a growing number of wireless networks, we face the problem of radio spectrum shortages. As a result, identifying the wireless channel spectrum to exploit the channel's idle state while also…
Pixel antenna is a promising antenna technology that enables flexible adjustment of radiation characteristics and enhancement of wireless systems through antenna coding. This work proposes a novel deep learning-based antenna coding…
Coloring is used in wireless networks to improve communication efficiency, mainly in terms of bandwidth, energy and possibly end-to-end delays. In this research report, we define the h-hop node coloring problem, with h any positive integer.…
The accelerating penetration of physical environments by objects with information processing and wireless communication capabilities requires approaches to find potential communication partners and discover services. In the present work, we…
Wireless sensor networks (WSNs) are becoming increasingly utilized in applications that require remote collection of data on environmental conditions. In particular dense WSNs are emerging as an important sensing platforms for the Internet…
We consider a distributed learning setup where a sparse signal is estimated over a network. Our main interest is to save communication resource for information exchange over the network and reduce processing time. Each node of the network…
Fiber-Wireless (FiWi) access networks have been widely deployed due to the complementary advantages of high-capacity fiber backhaul and ubiquitous wireless front end. To meet the increasing demands for bandwidth-hungry applications, access…
It is known that data rates in standard cellular networks are limited due to inter-cell interference. An effective solution of this problem is to use the multi-cell cooperation idea. In Cloud Radio Access Network, which is a candidate…
Dense Convolutional Network has been continuously refined to adopt a highly efficient and compact architecture, owing to its lightweight and efficient structure. However, the current Dense-like architectures are mainly designed manually, it…
Based on various existing wireless fingerprint location algorithms in intelligent sports venues, a high-precision and fast indoor location algorithm improved weighted k-nearest neighbor (I-WKNN) is proposed. In order to meet the complex…
In dense deployments of residential WiFi networks individual users suffer performance degradation due to both contention and interference. While Radio Resource Management (RRM) is known to mitigate this effects its application in…
Ultra-densely deploying access points (APs) to support the increasing data traffic would significantly escalate the cell-edge problem resulting from traditional cellular networks. By removing the cell boundaries and coordinating all APs for…
The exploitation of already deployed wireless local area networks (WLAN)s (e.g., WiFi access points (AP)s) has attracted considerable attention, as an efficient and practical method to improve the performance of beyond 4G wireless networks.…
Massive MIMO is a variant of multiuser MIMO, where the number of antennas $M$ at the base-station is large, and generally much larger than the number of spatially multiplexed data streams to/from the users. It has been observed that in many…
This paper considers the discrete convexity of a cross-layer on-off transmission control problem in wireless communications. In this system, a scheduler decides whether or not to transmit in order to optimize the long-term quality of…
We study optimal user-network association in an integrated 802.11 WLAN and 3G-UMTS hybrid cell. Assuming saturated resource allocation on the downlink of WLAN and UMTS networks and a single QoS class of mobiles arriving at an average…
The use of a very large number of antennas at each base station site (referred to as "Massive MIMO") is one of the most promising approaches to cope with the predicted wireless data traffic explosion. In combination with Time Division…
WiFi fingerprint-based indoor localization schemes deliver highly accurate location data by matching the received signal strength indicator (RSSI) with an offline database using machine learning (ML) or deep learning (DL) models. However,…
Artificial Intelligence (AI) solutions for wireless location estimation are likely to prevail in many real-world scenarios. In this work, we demonstrate for the first time how the Cramer-Rao upper bound on localization accuracy can…
Designing decentralized policies for wireless communication networks is a crucial problem, which has only been partially solved in the literature so far. In this paper, we propose the Decentralized Markov Decision Process (Dec-MDP)…