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

Dynamic Spectrum Allocation and Sharing in Cognitive Cooperative Networks

The dramatic increase of service quality and channel capacity in wireless networks is severely limited by the scarcity of energy and bandwidth, which are the two fundamental resources for communications. New communications and networking paradigms such as cooperative communication and cognitive radio networks emerged in recent years that can intelligently and efficiently utilize these scarce resources. With the development of these new techniques, how to design efficient spectrum allocation and sharing schemes becomes very important, due to the challenges brought by the new techniques. In this dissertation we have investigated several critical issues in spectrum allocation and sharing and address these challenges. Due to limited network resources in a multiuser radio environment, a particular user may try to exploit the resources for self-enrichment, which in turn may prompt other users to behave the same way. In addition, cognitive users are able to make intelligent decisions on spectrum usage and communication parameters based on the sensed spectrum dynamics and other users' decisions. Thus, it is important to analyze the intelligent behavior and complicated interactions of cognitive users via game-theoretic approaches. Moreover, the radio environment is highly dynamic, subject to shadowing/fading, user mobility in space/frequency domains, traffic variations, and etc. Such dynamics brings a lot of overhead when users try to optimize system performance through information exchange in real-time. Hence, statistical modeling of spectrum variations becomes essential in order to achieve near-optimal solutions on average. In this dissertation, we first study a stochastic modeling approach for dynamic spectrum access. Since the radio spectrum environment is highly dynamic, we model the traffic variations in dynamic spectrum access using continuous-time Markov chains that characterizes future traffic patterns, and optimize access probabilities to reduce performance degradation due to co-channel interference. Second, we propose an evolutionary game framework for cooperative spectrum sensing with selfish users, and develop the optimal collaboration strategy that has better performance than fully cooperating strategy. Further, we study user cooperation enforcement for cooperative networks with selfish users. We model the optimal relay selection and power control problem as a Stackelberg game, and consider the joint benefits of source nodes as buyers and relay nodes as sellers. The proposed scheme achieves the same performance compared to traditional centralized optimization while reducing the signaling overhead. Finally, we investigate possible attacks on cooperative spectrum sensing under the evolutionary sensing game framework, and analyze their damage both theoretically and by simulations

ARQ Protocols in Cognitive Decode-and-Forward Relay Networks: Opportunities Gain

In this paper, two novel automatic-repeat-request (ARQ) based protocols were proposed, which exploit coop- eration opportunity inherent in secondary retransmission to create access opportunities. If the signal was not decoded correctly in destination, another user can be acted as a relay to reduce retransmission rounds by relaying the signal. For comparison, we also propose a Direct ARQ Protocol. Specif- ically, we derive the exact closed-form outage probability of three protocols, which provides an effective means to evalu- ate the effects of several parameters. Moreover, we propose a new metric to evaluate the performance improvement for cognitive networks. Finally, Monte Carlo simulations were presented to validate the theory analysis, and a comparison is made among the three protocols

Interference Alignment for Cognitive Radio Communications and Networks: A Survey

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe