We present a new architecture to perform localization (position estimation) in GNSS systems, termed NEPS (Narrowband Efficient Positioning System). The NEPS architecture is composed of three components: a low powered cheap receiver; a communication system which transmits the measurements; and a processing unit which receives the distorted observations (due to quantisation and imperfect transmission medium) and performs the position estimation algorithm. The NEPS is a stand-alone system which is designed to incorporate the quantised measurements as well as the imperfect communication channels between receiver and the backend in order to perform inference on the user's position. Compared with a conventional system, the NEPS consumes less bandwidth, requires lower power consumption and provides faster reporting rates. We derive the joint Maximum Likelihood (ML) for the position and the receiver's clock offset. We then develop an efficient algorithm to solve the resulting non-convex oinferenceptimisation problem. Furthermore, we derive a theoretical performance lower bound on the achievable accuracy via Cramér-Rao lower bound (CRLB). Simulation results show that the performance of the NEPS ML position estimator is close to the theoretical performance bound.