# A Biologically-Inspired Power Control Algorithm for Energy-Efficient Cellular Networks
## 1 Introduction  
The worldwide reduction of energy consumption, and therefore of greenhouse gas emissions, is now one of the most urgent challenges of our age. At the same time, the rapid growth in wireless communication networks requires huge amounts of energy to provide wide bandwidths for numerous mobile devices. With the rapid growth of the mobile market, service providers have increased the number of base stations (BSs) in an attempt to attract more subscribers. However, most of the energy used to operate a cellular network is consumed by BSs, and service providers therefore require energy-efficient BSs in order to reduce their operational expenditure. BSs consume energy in three operational functions: in radio transmission, in baseband processing and in the feeder. Among these, the radio part consumes more than 80% of the energy of a BS to amplify the transmitting signal [1; 2; 3]. Therefore, reducing the transmission power of the BS could yield a substantial energy savings in the cellular network. It has been recognized that a tradeoff exists between the energy consumed at a transmitter and the signal quality at a receiver (e.g., data rate or outage probability) according to the allocated transmission power [4; 5; 6; 7; 8]. Considering this tradeoff, many authors have tried to minimize energy consumption while satisfying the required signal quality by controlling the transmission power. Long-term transmitpower control (TPC) algorithms, known as a \"cell-breathing\" or a \"cell-zooming\" technique, have been proposed to minimize the energy consumption of a BS according to variations in the traffic load with a certain cell throughput constraint [9; 10; 11]. In these schemes, a cell experiencing a heavy load or interference reduces its size by decreasing the transmission power of the BS, while neighboring cells cover those users who cannot be served by the overloaded cell, by increasing the transmission power of the BS. Furthermore, signal-to-interference plus noise ratio (SINR)-based TPC algorithms use the minimum transmit power level necessary to guarantee the required SINR at the receiving node, in an attempt to achieve not only interference mitigation, but also power savings [12; 13; 14]. Similarly, the transmit power is minimized based on channel state information (CSI) while maintaining a constant outage probability or bit error rate (BER) at the receiver under fading environments [15; 16; 17; 18; 19]. Moreover, an optimized transmit power is derived at each BS to maximize the overall network capacity under a quality of service (QoS) constraint, such that energy efficiency is improved [20; 21; 22; 23]. Furthermore, recently, the joint power control and resource allocation problems in heterogeneous cellular networks have been investigated, and the practical distributed subchannel and power allocation algorithms have been developed in order to improve the network capacity and the user fairness [24; 25; 26]. As reviewed above, a common strategy used by most TPC algorithms is to minimize the transmit power consumption while ensuring the required QoS (_i.e._, SINR, rate or BER) of each mobile station (MS) [12; 13; 14; 15; 16; 17; 18; 19]. This strategy provides satisfactory operation in low interference environments. However, if the interference level increases, the transmission power must increase, eventually reaching a maximum value. In this case, an outage (_i.e._, where the required QoS is violated) may occur even though a high transmission power is used. Therefore, the power minimization approach that is subject to a constant SINR requirement is somewhat constrained in such an interference-limited environment. Moreover, in this power minimization method, the target SINR is a key parameter that closely affects both QoS performance and energy efficiency. However, it is difficult to determine an appropriate target SINR according to the interference level, because this requires a complex calculation and a significant overhead for sharing channel information between all MSs and all BSs [12; 13; 14].