Analisis Implementasi Algoritma Auction pada Komunikasi Device to Device (D2D) untuk Frekuensi 2,3 Ghz

Komunikasi D2D inband underlaying merupakan skema representative dimana user D2D dan seluler user menggunakan spectrum yang sama yaitu spectrum seluler pada frekuensi 2,3 Ghz. Komunikasi antara pasangan D2D dan cellular user (CU)  mengakibatkan adanya interferensi  yang diakibatkan oleh D2D Tx (transmitter) mengalami interferensi terhadap eNB dan CU mengalami interferensi terhadap D2D Rx (receiver). Untuk mengatasi masalah tersebut, dapat digunakan metode alokasi resource (resource block allocation). Tujuan penelitian ini untuk menganalisis performansi komunikasi D2D dengan menganalisis parameter data rate, energy efficiency, dan spectral efficiency . Dari simulasi variasi jumlah pasangan D2D simulasi dilakukan 20,25,30,..,100 dan jumlah CUE tetap sebanyak 50 user. dimulai dari 20 sampai 100 dengan kenaikan jumlah pasangan D2D sebesar 10 diperoleh 9 jumlah data pasangan D2D. Nilai rata-rata data rate yang diperoleh algoritma  auction adalah 1,9745x108 bps. Dan nilai energy efficiency dan spectral efficiency dari algoritma auction masing-masing bernilai 4,6352x106 bps/watt dan  21,9396 bps/Hz

Establishing effective communications in disaster affected areas and artificial intelligence based detection using social media platform

Floods, earthquakes, storm surges and other natural disasters severely affect the communication infrastructure and thus compromise the effectiveness of communications dependent rescue and warning services. In this paper, a user centric approach is proposed to establish communications in disaster affected and communication outage areas. The proposed scheme forms ad hoc clusters to facilitate emergency communications and connect end-users/ User Equipment (UE) to the core network. A novel cluster formation with single and multi-hop communication framework is proposed. The overall throughput in the formed clusters is maximized using convex optimization. In addition, an intelligent system is designed to label different clusters and their localities into affected and non-affected areas. As a proof of concept, the labeling is achieved on flooding dataset where region specific social media information is used in proposed machine learning techniques to classify the disaster-prone areas as flooded or unflooded. The suitable results of the proposed machine learning schemes suggest its use along with proposed clustering techniques to revive communications in disaster affected areas and to classify the impact of disaster for different locations in disaster-prone areas

IoT-Enabled Social Relationships Meet Artificial Social Intelligence

With the recent advances of the Internet of Things, and the increasing accessibility of ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as relationship explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as Artificial Social Intelligence (ASI) that has the potential to tackle the social relationship explosion problem. This paper discusses the role of IoT in social relationships detection and management, the problem of social relationships explosion in IoT and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.Comment: Submitted to IEEE internet of things journa

Social-Aware Resource Allocation and Optimization for D2D Communication

The undiminished growth of research activities to converge social awareness with D2D communication has paved the way for facilitating and providing significant benefits to users. Realizing these benefits depends on efficiently addressing several main technical challenges associated with the convergence. Although there are many research studies related to social networks and D2D communication, convergence of these two areas leads to further research efforts to implement social-aware D2D communication. In this article, we discuss recent advances in the domain of D2D communication from the perspective of social-aware resource allocation and optimization. We also categorize and classify the literature by devising a taxonomy based on channel-centric attributes, objectives, solving approaches, networking technologies, characteristics, and communication types. Moreover, we also outline the key requirements with the aim of providing guidelines for the domain researchers and designers to enable the social-aware resource allocation for D2D communication. Several open research challenges are presented as future research directions. © 2002-2012 IEEE

Social-aware resource allocation and optimization for D2D communication

The undiminished growth of research activities to converge social awareness with D2D communication has paved the way for facilitating and providing significant benefits to users. Realizing these benefits depends on efficiently addressing several main technical challenges associated with the convergence. Although there are many research studies related to social networks and D2D communication, convergence of these two areas leads to further research efforts to implement social-aware D2D communication. In this article, we discuss recent advances in the domain of D2D communication from the perspective of social-aware resource allocation and optimization. We also categorize and classify the literature by devising a taxonomy based on channel-centric attributes, objectives, solving approaches, networking technologies, characteristics, and communication types. Moreover, we also outline the key requirements with the aim of providing guidelines for the domain researchers and designers to enable the social-aware resource allocation for D2D communication. Several open research challenges are presented as future research directions. © 2002-2012 IEEE