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In this paper, we investigate dynamic base station (BS) switching to reduce energy consumption in wireless cellular networks. Specifically, we formulate a general energy minimization problem pertaining to BS switching that is known to be a difficult combinatorial problem and requires high computational complexity as well as large signaling overhead. We propose a practically implementable switching-on/off based energy saving (SWES) algorithm that can be operated in a distributed manner with low computational complexity. A key design principle of the proposed algorithm is to turn off a BS one by one that will minimally affect the network by using a newly introduced notion of network-impact, which takes into account the additional load increments brought to its neighboring BSs. In order to further reduce the signaling and implementation overhead over the air and backhaul, we propose three other heuristic versions of SWES that use the approximate values of network-impact as their decision metrics. We describe how the proposed algorithms can be implemented in practice at the protocol-level and also estimate the amount of energy savings through a first-order analysis in a simple setting. Extensive simulations demonstrate that the SWES algorithms can significantly reduce the total energy consumption, e.g., we estimate up to 50-80% potential savings based on a real traffic profile from a metropolitan urban area.Index Terms-Energy saving, base station switching on/off, green cellular networks.

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Ahstract-This paper develops an energy-aware hierarchical cell configuration framework that encompasses both deployment and operation in downlink cellular networks. Specifically, we first formulate a general problem pertaining to total energy con sumption minimization while satisfying the requirement of area spectral efficiency (ASE), and then decompose it into deployment problem at peak time and operation problem at off-peak time.For the deployment problem, we start from an observation about various topologies including the real deployment of BSs that there is a strong correlation between the area covered by an additional micro BS and the increment of ASE. Under such an assumption, we prove the submodularity of ASE function with respect to micro BS deployment and propose a greedy algorithm that is shown to be a constant-factor approximation of optimal deployment. Although the greedy algorithm can be also applied as an offline centralized solution for the operation problem, we further propose online distributed algorithms with low complexity and signaling overhead to have more practical solutions. Extensive simulations based on the acquired real BS topologies and traffic profiles show that the proposed algorithms can significantly reduce the energy consumption.

This paper presents a new duplex approach which does not require guard resources suitable for indoor 2 × 2 MIMO environments. In the proposed duplex, two virtual channels in the spatial domain are generated by precoding and postcoding MIMO channels, not to use guard resources in either the time or frequency domain. In addition, this system can achieve selection diversity since the generation of virtual channels is not unique for the given channels information. We will show the generation of the virtual channel, and that the capacity and reliability of the communication links improves when the problem of the guard resource is addressed and selection diversity is utilized.