Efficient Coexistence of LTE With WiFi in the Licensed and Unlicensed Spectrum Aggregation

TLDR

LTE‑Advanced now exploits unlicensed bands through licensed assisted access, but efficient coexistence with WiFi requires advanced intelligent techniques. This paper investigates LAA and proposes enhanced Q‑learning and double Q‑learning techniques for carrier selection and discontinuous transmission to improve LTE‑A and WiFi coexistence. The authors implement LAA functionalities in an open‑source LTE‑A downlink simulator and apply Q‑learning and double Q‑learning to model unlicensed band activity and optimize carrier selection and power control. Simulation results demonstrate that exploiting unlicensed bands with these learning methods benefits next‑generation mobile networks.

Abstract

The exploitation of unlicensed bands by the LTE-advanced (LTE-A) system has become a reality through the proposal of licensed assisted access (LAA) that relies on the carrier aggregation concept within the 3GPP framework. The efficient coexistence of LTE-A and WiFi in the unlicensed spectrum bands requires advanced intelligent techniques. This paper first investigates the concept of LAA, which consists of four main functionalities: 1) carrier selection (CS); 2) listen-before-talk; 3) discontinuous transmission (DTX); and 4) transmit power control (TPC). Second, the LAA functionality implementation is provided using an open source LTE-A downlink link level simulator. Third, we devise an enhanced learning technique for CS and DTX for efficient coexistence among LTE-A and WiFi users. In particular, we provide a Q-learning mechanism for the advanced learning of the unlicensed band activity resulting in the efficient coexistence. Finally, we enhance the coexistence further through a double Q-learning method as a proposal for CS that takes into account both DTX and TPC improving both LTE and WiFi performance. Simulation results are provided for all the use cases that reveal the benefit of exploiting unlicensed bands in next generation mobile cellular networks.