548 research outputs found
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
Cross Layer Aware Adaptive MAC based on Knowledge Based Reasoning for Cognitive Radio Computer Networks
In this paper we are proposing a new concept in MAC layer protocol design for
Cognitive radio by combining information held by physical layer and MAC layer
with analytical engine based on knowledge based reasoning approach. In the
proposed system a cross layer information regarding signal to interference and
noise ratio (SINR) and received power are analyzed with help of knowledge based
reasoning system to determine minimum power to transmit and size of contention
window, to minimize backoff, collision, save power and drop packets. The
performance analysis of the proposed protocol indicates improvement in power
saving, lowering backoff and significant decrease in number of drop packets.
The simulation environment was implement using OMNET++ discrete simulation tool
with Mobilty framework and MiXiM simulation library.Comment: 8 page
Optimization and Learning in Energy Efficient Cognitive Radio System
Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized.
Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity.
In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network
Cross-layer aided energy-efficient routing design for ad hoc networks
In this treatise, we first review some basic routing protocols conceived for ad hoc networks, followed by some design examples of cross-layer operation aided routing protocols. Specifically, cross-layer operation across the PHYsical layer (PHY), the Data Link layer (DL) and even the NETwork layer (NET) is exemplified for improving the energy efficiency of the entire system. Moreover, the philosophy of Opportunistic Routing (OR) is reviewed for the sake of further reducing the system's energy dissipation with the aid of optimized Power Allocation (PA). The system's end-to-end throughput is also considered in the context of a design example
Applications of Repeated Games in Wireless Networks: A Survey
A repeated game is an effective tool to model interactions and conflicts for
players aiming to achieve their objectives in a long-term basis. Contrary to
static noncooperative games that model an interaction among players in only one
period, in repeated games, interactions of players repeat for multiple periods;
and thus the players become aware of other players' past behaviors and their
future benefits, and will adapt their behavior accordingly. In wireless
networks, conflicts among wireless nodes can lead to selfish behaviors,
resulting in poor network performances and detrimental individual payoffs. In
this paper, we survey the applications of repeated games in different wireless
networks. The main goal is to demonstrate the use of repeated games to
encourage wireless nodes to cooperate, thereby improving network performances
and avoiding network disruption due to selfish behaviors. Furthermore, various
problems in wireless networks and variations of repeated game models together
with the corresponding solutions are discussed in this survey. Finally, we
outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference
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