Related papers: Interference Mitigation In Wireless Mesh Networks …
Wireless Mesh Network (WMN) is surely one of the prominent networks in the modern era which is widely used in numerous evolving applications, viz. broadband home networking (BHN), community and neighbourhood networks (CNN), coordinated…
Integrated sensing and communication is a key feature in next-generation wireless networks, enabling joint data transmission and environmental radar sensing on shared spectrum. In multi-user scenarios, simultaneous transmissions cause…
In Multi-Radio Multi-Channel (MRMC) Wireless Mesh Networks (WMN), Partially Overlapped Channels (POC) has been used to increase the parallel transmission. But adjacent channel interference is very severe in MRMC environment; it decreases…
Given a wireless network where some pairs of communication links interfere with each other, we study sufficient conditions for determining whether a given set of minimum bandwidth Quality of Service (QoS) requirements can be satisfied. We…
In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network optimization approaches. While effective, the generative AI…
Interference-aware resource allocation of time slots and frequency channels in single-antenna, halfduplex radio wireless sensor networks (WSN) is challenging. Devising distributed algorithms for such task further complicates the problem.…
Given a wireless network where some pairs of communication links interfere with each other, we study sufficient conditions for determining whether a given set of minimum bandwidth quality-of-service (QoS) requirements can be satisfied. We…
Deep learning-based approaches have been developed to solve challenging problems in wireless communications, leading to promising results. Early attempts adopted neural network architectures inherited from applications such as computer…
A central problem in the operation of large wireless networks is how to deal with interference -- the unwanted signals being sent by transmitters that a receiver is not interested in. This thesis looks at ways of combating such…
Due to mutual interference between users, power allocation problems in wireless networks are often non-convex and computationally challenging. Graph neural networks (GNNs) have recently emerged as a promising approach to tackling these…
Interference is a major impediment to the performance of a wireless network as it has a significant adverse impact on Network Capacity. There has been a gradual and consistent densification of WiFi networks due to Overlapping Basic Service…
In multi-radio multi-channel (MRMC) WMNs, interference alleviation is affected through several network design techniques e.g., channel assignment (CA), link scheduling, routing etc., intelligent CA schemes being the most effective tool for…
Signal processing is crucial for satisfying the high data rate requirements of future sixth-generation (6G) wireless networks. However, the rapid growth of wireless networks has brought about massive data traffic, which hinders the…
The aggressive densification of modern wireless networks necessitates judicious resource allocation to mitigate severe mutual interference. However, classical iterative algorithms remain computationally prohibitive for real-time…
In single channel wireless networks, concurrent transmission at different links may interfere with each other. To improve system throughput, a scheduling algorithm is necessary to choose a subset of links at each time slot for data…
The interference graph, depicting the intra- and inter-cell interference channel gains, is indispensable for resource allocation in multi-cell networks.However, there lacks viable methods of interference graph estimation (IGE) for…
Due to the high demand of Internet access by users, and the tremendous success of wireless technologies, Wireless Mesh Networks (WMNs) have become a promising solution. IGW Placement and Selection (GPS) are significantly investigated…
Reconfigurable intelligent surface (RIS) is considered as a promising solution for next-generation wireless communication networks due to a variety of merits, e.g., customizing the communication environment. Therefore, deploying multiple…
Graph neural networks (GNNs) have been shown promising in improving the efficiency of learning communication policies by leveraging their permutation properties. Nonetheless, existing works design GNNs only for specific wireless policies,…
In modern wireless networks, interference is no longer negligible since each cell becomes smaller to support high throughput. The reduced size of each cell forces to install many cells, and consequently causes to increase inter-cell…