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Building the Autonomous Networks of the Future
Published in Mazin Gilbert, Artificial Intelligence for Autonomous Networks, 2018
Stephen Terrill, Mattias Lidström
The private consumer is typical of many network users today. This can include households with a broadband connection through to mobile broadband users with mobile devices of different types (phones, tablets, computers, watches, or other wearables).
The Beginning
Published in Saad Z. Asif, 5G Mobile Communications Concepts and Technologies, 2018
The 1G analog systems are no longer operational, which only provided voice services and had no support for data. The 2G digital systems are currently operational and support voice and limited data services. The 3G systems support voice, low speed data, and enable a number of data services. The 4G systems enable mobile broadband in the true sense, targeting 100 Mbps or higher on the move.
Widget Deconstruction #1: Smartphone
Published in John D. Cressler, Silicon Earth, 2017
4G smartphones not only provide the usual voice and other services of 3G, but also provide high data rate mobile broadband Internet access, for example, to laptops with wireless modems, and to other mobile devices. Cool apps include IP telephony (voice over Internet), some serious gaming services, high-definition mobile TV, video conferencing, 3D television, cloud computing, etc. These 4G networks employ the Mobile WiMAX standard (first used in South Korea in 2007), and the Long Term Evolution (LTE) standard (first used in Oslo, Norway, and Stockholm, Sweden, in 2009). To enhance data rates in 4G, one utilizes, for instance, MIMO transceivers (multiple-in-multiple-out), essentially parallel radio data paths (and lots of wraparound DSP and circuitry) to boost system performance and data throughput. Bandwidth goals include 100 Mb/s for fast moving communications (cars, trains) and 1 Gb/s for slow moving communications (walking, standing). Hint: you can do fun things at 1 Gb/s data bandwidths! 4G networks are already making inroads into the global cellular infrastructure. Yep, and 5G is already in the works! Much higher frequency now (millimeter-wave; 24–60 GHz) for bigger data pipes, but with the same basic goal—boost data rates on-the-fly and enable more fun apps!
Opportunistic forwarding for user-provided networks
Published in International Journal of Parallel, Emergent and Distributed Systems, 2018
Efthymios Koutsogiannis, Lefteris Mamatas, Vassilis Tsaoussidis
Example incentive mechanisms for UPNs are: (i) the Less Than Best Effort approaches [15–17] that offer guest users the resources that are not utilized by the SAP users; (ii) the Messages on oFfer (MooF) [14] mechanism which is a credit-based incentive mechanism enabling device to device data exchange; (iii) the SMART [58] that is a credit-based schema assuming a central authority for virtual banking and the nodes decide to participate based on each particular reward and the requested class of service; and (iv) the Practical incentive (Pi) [59] that combines both reputation- and credit-based approaches, giving a credit when the message arrives to the destination and a better reputation even if the message does not reach the target. For example, the mobile broadband Internet access may have a diverse cost and performance, which may not be true for a WiFi connection in the area. Furthermore, the latency may be significantly lower for local services. The Open Garden [8] and the Karma [7] startups implemented two interesting mobile UPN models. The former approach exploits the diversity of user requirements and capabilities through crowd sourcing and the latter allows mobile users to become mobile WiFi hotspots, in exchange of a compensation. A categorization of the different UPN incentive models, including the mobile UPN approaches, can be found at [60].
Fractional sequential likelihood ascent search detector for interference cancelation in massive MIMO systems in 5G technology
Published in International Journal of Electronics, 2021
Anju V. Kulkarni, Radhika Menon, Pramodkumar H. Kulkarni
This section illustrates the proposed model of massive-MIMO for mitigating the interference. The massive-MIMO is described as a cellular system in which the number of transmitter antennas, receiver antennas, and number of users is large. The major concept in massive-MIMO is its capability to spin multipath propagation, which is a major issue in wireless communication among users. The system model is designed due to the encouragement of potential interference mitigation techniques to enhance system performance. Numerous standardised channel models have started to emerge that define the fifth-generation 3D channels. Thus, this work provides a base to devise a technique for mitigating the interference generated, while transmitting the signals to the receiver. Figure 1 describes the block diagram of massive-MIMO for interference mitigation. Here, the users and the access points are spatially-distributed thereby, providing higher signal strength with improved quality. Interference mitigation using the signals received from the packets with the different access points is done at the receiver side. Thus, in order to eradicate the interference generated in AP, a newly designed algorithm named Fractional-SLAS, which is the modification of the existing SLAS (Maciel et al., 2018) using the fractional calculus (Bhaladhare & Jinwala, 2014) is employed. Thus, the proposed technique in massive-MIMO provides the cellular network with high speed, low latency, and resilience for next-generation mobile broadband applications. Hence, the massive MIMO along with small cells are employed as an important part in 5 G for mitigating the interference.