Intensive use of wireless (W-Fi) communication has led to the rapid expansion of wireless infrastructure worldwide, including new base stations and Wi-Fi towers. Due to huge amounts of data transmission requests, network systems consume quite a high amount of power. However, only a small part of this energy is used to supply the system itself; most of it is lost as heat because of the low energy efficiency of the system overall. This unnecessarily increases Wi-Fi’s operational costs, as well as greenhouse gas emissions.
MIT researcher Omer Tanovic from the Department of Electrical Engineering and Computer Science has presented a new signal processing algorithm that increases power efficiency, while ensuring signal quality. Tanovic began with the fact that power efficiency is related to the peak-to-average power ratio (PAPR) of Wi-Fi signals. PAPR represents how much energy is required to send and receive a credible signal. The lower the PAPR value is the more energy-efficient the Wi-Fi system is. Tanovic’s team has addressed the power efficiency issue by decreasing the PAPR value of Wi-Fi signals.
The most energy-consuming component in a cellular network is the power amplifier, which coverts low-power electronic signals to higher-power output. The signal needs to be strong enough (have an adequate signal-to-noise ratio) to reach a cell tower when it is generated by a cell phone. The amplifiers are most efficient when operating near saturation level at maximum output power. The main issue of currently used technology is the fact that it is designed such that the main power amplifier can carry signals with peaks much higher than the average signal power being transmitted. Thus, most of the time they operate inefficiently far from their saturation level. This design has been developed to address requests for a huge volume of a variety of information across the network with far less uniform signals than in the past.
The researchers’ new algorithm has been designed to decrease the PAPR of the signals, allowing the power amplifier to operate at maximum efficiency, thus reducing power losses in the process. Although the optimization system requires infinite latency (infinite delay before transmitting the signal), Tanovic found that the optimal system, including the infinite latency issue, had a desirable fading-memory property that makes it possible to design an approximation of finite latency with an acceptable lag time.
The algorithm is based on an estimate that allows a compromise between precision and latency (delay before transmitting the signal) so that real-time realizations of the algorithm can improve power efficiency without adding too much transmission delay or too much distortion to the signal. The system, tested and applied using the standardized signals for 4G communication, has shown an approximately 50 percent reduction in PAPR while meeting the required quality of digital communication signals. Due to limited space on a microchip, the algorithm can’t take up too much space and needs to be executed quickly, because latency is a crucial factor in Wi-Fi communication.
This concept has the potential to be used in other industry applications, as Tanovic explained: “The algorithm could be adapted to solve other engineering problems with similar frameworks, including envelope tracking and model predictive control.”