Bluetooth Low Energy (BLE) is a popular wireless communication protocol heavily used in Internet of Things applications. Nowadays, robustness is considered a key requirement in wireless communication. However, radio interference from various sources may affect the performance of BLE devices, leading to channel congestion. Therefore, there is a broadly recognized need of methodologies capable of sensing and avoiding interference. In this paper, two improvements at the data link layer for interference detection and channel selection are proposed to enhance the BLE connection robustness. This paper also presents a wide range of experimental evaluations aiming at validating the improvements and providing insights on both these improvements. Particularly, the communication performance of the BLE link layer is assessed in terms of channel usage distribution, supervision timeout ratio (STR) and packet loss rate (PLR) under different interference environments. Results from these experiments (reliability over 97% and 99% under two different harsh environments) highlight the effects of both improvements on the BLE robustness. Meanwhile, the authority of scheduling the whole mechanism is given to the link layer and even the higher application layer. This paper provides a set of solutions for BLE confronting interference in link layer.

Bluetooth Low Energy (BLE), a short-range and low-power communication protocol, has gained a lot of popularity in recent years. A part of BLE is the Generic Attribute Profile (GATT) which defines the data communication between two devices. During the initial connection between two BLE devices a discovery of services, characteristics and descriptors is required for the GATT to operate. During this discovery phase, the device is unusable as it builds the foundation for further data transactions. When unoptimized, this discovery step can take up to a few seconds, leading to frustrations for the end user or delays in some applications. In this paper, we aim to find guidelines on how to optimize this discovery process. A simulation framework was developed, able to simulate and analyze the packet exchange of the service discovery, while taking link layer parameters into account. The results show that minimizing the connection interval and maximizing the data length leads to the lowest discovery times. Practical experiments in real environment, however, show that the theoretically calculated times are not reachable due to processing overhead and retransmissions. Theoretical results also show that the current BLE discovery process, even after optimizations, has a lot of overhead. To fix the problems with the current protocol, this paper proposes a new Rapid Service Discovery Protocol, which enables a fast and efficient service discovery.

We noted that communication performance of a Bluetooth Low Energy (BLE) connection is heavily affected by the radio interference from other connections or networks. Reliability is becoming a key requirement in BLE for its use in various Internet of Things applications. Hence, there is a widely recognized need for an in-depth study to reveal the parameters impacting BLE reliability under such radio interference. In this article, we investigate how transmission parameters, e.g., number of packets and packet transmission time, influence reliability of the BLE protocol. Specifically, a mathematical model is presented to explore the impact of the transmission parameters on the reliability of a BLE pair under interference caused by other pairs. This mathematical model is able to show the reliability issues from both the side of the BLE connection under interference and the side of the interference itself. The model is validated and novel insights on the common usage of BLE parameters by a wide range of experimental evaluations are provided. Experimental results highlight the correctness of the mathematical model, thus quantify the interplay between transmission parameters and coexistence, also the influence of other related parameters. This research provides a design-level or system-level insight in BLE usage and deployment.