5G has been a rather hot research topic for a while and this trend stays unchanged or even gains more momentum in Globecom 2015 in San Diego. Indeed, there were 4 tutorials dedicated to 5G and a couple more related topics like green network, fog network, full duplex, quantum communications, etc. There’are also several workshops for 5G and many more technical 5G symposiums. Meanwhile, there’re also growing focuses on IoT, indoor networks, caching, etc.
Commercialization of technologies is getting faster and faster than ever, even results from fundamental research. It is not clear who is leading, academia or industry. Those who discover something first and commercialize fast will earn huge returns quickly. For example, in the presentation, “indoor mm-Wave Channel Measurements: Comparative Study of 2.9 GHz and 29 GHz”, Qualcomm reported similar measured channel properties of 2.9 GHz and 29 GHz in indoor environment and is still trying to figure out why! But measurement is measurement! Theory always need to be corrected to follow facts. If the reported results are true and may even be universal for a broad band of spectrum, a lot will have to be changed.
Peiliang and I presented our recent research results on “‘Area Spectral and Energy Efficiency Analysis of Cellular Networks with Cell DTX'”. The research on the SE and EE of the overall network has always been a challenging area because of its complexity in analysis and non-concavity from interference terms.
However we successfully obtained the network spectral efficiency and energy efficiency as functions of network traffic load.
It is shown that the network spectral efficiency increases monotonically in traffic load, while the optimal network energy efficiency depends on the ratio of the sleep-mode power consumption to the active-mode power consumption of base stations. If the ratio is larger than a certain threshold, the network energy efficiency increases monotonically with network traffic load and is maximized when the network is fully loaded. What’s more, the power ratio threshold depends solely on the wireless channel propagation, i.e. path loss exponent
α. For example, the ratio is 56% for α = 4, indicating that in this propagation environment, if the sleep power consumption is more than 56% of the active mode power consumption, the network should be always fully loaded to maximize network energy efficiency, as sleeping won’t save you much. Otherwise, there is an optimal load that the network should work on so that the energy efficiency is maximized.