A close examination of performance and power characteristics of 4G LTE networks

Abstract

With the recent advent of 4G LTE networks, there has been increasing interest to better understand the performance and power characteristics, compared with 3G/WiFi networks. In this paper, we take one of the first steps in this direction.Using a publicly deployed tool we designed for Android called 4GTest attracting more than 3000 users within 2 months and extensive local experiments, we study the network performance of LTE networks and compare with other types of mobile networks. We observe LTE generally has significantly higher downlink and uplink throughput than 3G and even WiFi, with a median value of 13Mbps and 6Mbps, respectively. We develop the first empirically derived comprehensive power model of a commercial LTE network with less than 6% error rate and state transitions matching the specifications. Using a comprehensive data set consisting of 5-month traces of 20 smartphone users, we carefully investigate the energy usage in 3G, LTE, and WiFi networks and evaluate the impact of configuring LTE-related parameters. Despite several new power saving improvements, we find that LTE is as much as 23 times less power efficient compared with WiFi, and even less power efficient than 3G, based on the user traces and the long high power tail is found to be a key contributor. In addition, we perform case studies of several popular applications on Android in LTE and identify that the performance bottleneck for web-based applications lies less in the network, compared to our previous study in 3G [24]. Instead, the device's processing power, despite the significant improvement compared to our analysis two years ago, becomes more of a bottleneck.

Energy Efficient Scheduling for Mobile Push Notifications

“…Due to the nature of DRX (Discontinuous Reception) mechanism which involves a state machine similar to the one used by UMTS, we believe the savings could be more significant with LTE networks. As the previous work has shown that the effect of the tail energy is even more drastic in LTE networks than 3G networks [10].…”

“…When the push notifications follow different paths than regular data traffic, it is not possible to piggyback the notification messages to non-notification packets. In addition, it has also been shown that the tail energy is not a grave problem with WiFi [10]. As a result, extending the notification scheduler to WiFi networks does not add substantial value, and our system is exclusive for devices that are only connected to a cellular network.…”

“…The state machine transitions are triggered by the arrival or transmission of data messages and the expiration of inactivity timers as explained in Section 2.1. The power consumption levels in each state and the timer expiration duration values are adopted from [10]. Relevant parameters are summarized in Table 1 e .…”

“…Also note that in this set of simulations, the tail time we use is around 9 seconds which is adopted from [10]. Tail time values are set by the operators and can be as high as 30 seconds.…”

Mobile data traffic offloading over Passpoint hotspots

“…The power consumption values for LTE and WiFi systems are computed based on local experiments done by the authors of [32] on an LTE phone. These values are presented in Table 4, where α u represents the uplink power consumption per Mbps (i.e., the power needed in mW for sending data at a throughput of 1 Mbps), α d is the downlink power consumption per Mbps (i.e., the power needed in mW for receiving data at a throughput of 1 Mbps) and β is the baseline power.…”