With the rapid expansion of the wireless communication, there has been a rapid growth in the demand for the mobile traffic. Moreover, the wireless traffic not only expands in traffic volume but also in the diversity of applications and requirements with the rise of the Internet of Things (IoT) concept. The insatiable demand for both the traffic volume and the ever-expanding IoT applications poses a great challenge on the design of the next generation, i.e. the 5G, communication system.

Time reversal (TR) technology has been proposed as a promising candidate for the 5G system with several promising characteristics, such as easy densification, asymmetric and heterogeneous design. TR system utilizes large bandwidth and observes detailed, location-specific channel impulse responses (CIR). With the detail CIR information, the TR system designs waveforms to concentrate transmitted energy to the intended users via the unique spatial temporal focusing effect. In this dissertation, we propose a TR indoor positioning system and medium access control design based on this unique effect.

We begin by proposing the time reversal resonating strength (TRRS) to quantify the similarity between the location information embedded CIRs. The TR indoor positioning system identifies the unknown users by calculating the TRRS between the CIR of the unknown user and the CIRs in the database. We built the system prototype and are the first-ever to perform precise indoor positioning at 1 to 2 cm resolution in both line-of-sight and non-line-of-sight scenario using one pair of transmitter and receiver both equipped with a single antenna. Based on the positioning system, we propose an indoor tracking system by collecting CIRs at several regions of interest and track unknown users when they pass it. To facilitate deployment, we built a prototype to automate CIR collection and the experiments show that the system detects the users correctly with very low false alarm rate.

In the second part, we design the medium access control scheme to maximize system sum rate and guarantee quality of service to the users in a downlink scenario. The system objective and constraints are transformed into a mixed integer quadratically constraint quadratic programming and can be solved efficiently. We then investigate rate adaptation scheme via selection of optimal backoff factors in TR system. The rate adaptation scheme effectively increases the system-wise performance and the fairness among users.