Current Issue : July - September Volume : 2016 Issue Number : 3 Articles : 4 Articles
The forecast for future 10 yearsââ?¬â?¢ traffic demand shows an increase in 1000 scales and more than 100 billion connections of Internet\nof Things, which imposes a big challenge for future mobile communication technology beyond year 2020. The mobile industry is\nstruggling in the challenges of high capacity demand but low cost for future mobile network when it starts to enable a connected\nmobile world. 5G is targeted to shed light on these contradictory demands towards year 2020. This paper firstly forecasts the vision\nof mobile communicationââ?¬â?¢s application in the daily life of the society and then figures out the traffic trends and demands for next\n10 years from the Mobile Broadband (MBB) service and Internet of Things (IoT) perspective, respectively.The requirements from\nthe specific service and user demands are analyzed, and the specific requirements from typical usage scenarios are calculated by\nthe defined performance indicators. To achieve the target of affordable 5G service, the requirements from network deployment and\noperation perspective are also captured. Finally, the capabilities and the efficiency requirements of the 5G system are demonstrated\nas a flower. To realize the vision of 5G, ââ?¬Å?information a finger away, everything in touch,ââ?¬Â 5G will provide the fiber-like access data\nrate, ââ?¬Å?zeroââ?¬Â latency user experience, and connecting to more than 100 billion devices and deliver a consistent experience across a\nvariety of scenarios with the improved energy and cost efficiency by over a hundred of times....
Communication systems in practice are subject to many technical/technological constraints and restrictions. Multiple\ninput, multiple output (MIMO) processing in current wireless communications, as an example, mostly employs\ncodebook-based pre-coding to save computational complexity at the transmitters and receivers. In such cases,\nclosed form expressions for capacity or bit-error probability are often unattainable; effects of realistic signal processing\nalgorithms on the performance of practical communication systems rather have to be studied in simulation\nenvironments. The Vienna LTE-A Uplink Simulator is a 3GPP LTE-A standard compliant MATLAB-based link level\nsimulator that is publicly available under an academic use license, facilitating reproducible evaluations of signal\nprocessing algorithms and transceiver designs in wireless communications. This paper reviews research results that\nhave been obtained by means of the Vienna LTE-A Uplink Simulator, highlights the effects of single-carrier\nfrequency-division multiplexing (as the distinguishing feature to LTE-A downlink), extends known link adaptation\nconcepts to uplink transmission, shows the implications of the uplink pilot pattern for gathering channel state\ninformation at the receiver and completes with possible future research directions....
A device-to-device (D2D) group works as relay nodes to aid the information delivery from a source to a destination in cellular\ncommunication network.Within this system, we propose a communication mechanism to aid traditional cellular communication\nand correspondingly borrow some channel resource from traditional cellular communication system for D2D communication. On\none side, to aid cellular communication, we propose a modified A lamouti scheme which does not modify the operation at the base\nstation. This makes our proposed scheme consistent with previous cellular communication system. On the other side, there are\nmany competitive D2D groups that want to potentially utilize the borrowed channel resource from traditional cellular system for\ndelivering their own information.We model this competition as a game and utilize game theory technique to solve this competition\nproblem....
The service provided by current mobile networks is not adapted to spatio-temporal fluctuations in traffic demand,\nbut such fluctuations offer opportunities for energy savings. In particular, significant gains in energy efficiency are\nrealizable by disengaging temporarily redundant hardware components of base stations. We therefore propose a\nnovel optimization framework that considers both the load-dependent energy radiated by the antennas and the\nremaining forms of energy needed for operating the base stations. The objective is to reduce the energy consumption\nof mobile networks, while ensuring that the data rate requirements of the users are met throughout the coverage\narea. Building upon sparse optimization techniques, we develop a majorization-minimization algorithm with the\nability to identify energy-efficient network configurations. The iterative algorithm is load-aware, has low\ncomputational complexity, and can be implemented in an online fashion to exploit load fluctuations on a short time\nscale. Simulations show that the algorithm can find network configurations with the energy consumption similar to\nthat obtained with global optimization tools, which cannot be applied to real large networks. Although we consider\nonly one currently deployed cellular technology, the optimization framework is general, potentially applicable to a\nlarge class of access technologies....
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