14,308 research outputs found

    Mobile Broadband Possibilities considering the Arrival of IEEE 802.16m & LTE with an Emphasis on South Asia

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    This paper intends to look deeper into finding an ideal mobile broadband solution. Special stress has been put in the South Asian region through some comparative analysis. Proving their competency in numerous aspects, WiMAX and LTE already have already made a strong position in telecommunication industry. Both WiMAX and LTE are 4G technologies designed to move data rather than voice having IP networks based on OFDM technology. So, they aren't like typical technological rivals as of GSM and CDMA. But still a gesture of hostility seems to outburst long before the stable commercial launch of LTE. In this paper various aspects of WiMAX and LTE for deployment have been analyzed. Again, we tried to make every possible consideration with respect to south Asia i.e. how mass people of this region may be benefited. As a result, it might be regarded as a good source in case of making major BWA deployment decisions in this region. Besides these, it also opens the path for further research and in depth thinking in this issue.Comment: IEEE Publication format, ISSN 1947 5500, http://sites.google.com/site/ijcsis

    Calling Dick Tracy! Or, Cellphone Use, Progress, and a Racial Paradigm

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    The hero and phone-watch from Dick Tracy are evoked regularly in news and studies of cellphone use. This paper argues that the racial paradigm of White law enforcer and Dark law-breaker in the comic strip resonates in contemporary evocations and in discussions of cellphone use and crime. Representations of mobile communication and racialized criminality in Dick Tracy were inspired by the 1930s “war on crime” that intersected with wireless innovations and with lynching. This paper interprets that repeated evocation of the comic strip is a “perverse nostalgia” for an old-fashioned form of law and order premised on racialized violence and viewing

    Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

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    Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig
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