With evolution and popularity of radio access technologies, the radio resource is becoming scarce. However, with fast-growing service demands, the future advanced wireless communication systems are expected to provide ubiquitous mobile broadband coverage to support higher data rate. Therefore, it is becoming an important problem that how to meet the greater demand with limited resources? In this situation, the femtocell has recently gained considerable attention. It is an emerging wireless access point that can improve indoor coverage as well as reduce bandwidth load in the macrocell network, and seem to be more attracted since the indoor traffic is up to 75% of all in 4G network. According to the newest researches, deployment of femtocell base station in public places' applications (campus, enterprise, etc.) is of much broad prospect, which could provide high quality, high rate wireless services to multiple users as well as effectively improved resource utility. However, a key challenge of the public femtocell networks is the utility-based resource management. In public femtocell networks, multi-units are necessary to jointly provide high rate, high quality services to indoor users, but there is often heavy resource competition as well as mutual interference between multiple femtocells. Therefore, it's very critical to optimize the radio resources allocation to meet femtocells' requirement as possible and reduce interference. What is more, using some ingenious resource allocation technique, multiple femtocells can cooperate and improve the system performance further. In this article, we proposed a systematic way to optimize the resource allocation for public femtocell networks, including three schemes of different stages: (1) long-term resource management, which is to allocate spectrum resource between macrocell and femtocell networks; (2) medium-term resource management, which is to allocate radio resources to each femtocell; (3) fast resource management, which is to further enable multiple femtocells to cooperate to improve the network's coverage and capacity. Numerical results show that these radio resource management schemes can effectively improve radio resource utility and system performance of the whole network.