Erlang analysis of cellular networks using stochastic Petri nets and user-in-the-loop extension for demand control

Abstract—Cellular networks face severe challenges due to the expected growth of application data rate demand with an increase rate of 100 % per year. Over-provisioning capacity has been the standard approach to reduce the risk of overload situations. Traditionally in telephony networks, call blocking and overload probability have been analyzed using the Erlang-B and Erlang-C formulas, which model limited capacity communication systems without or with session request buffers, respectively. While a closed-form expression exists for the blocking probability for constant load and service, a steady-state Markov chain (MC) analysis can always provide more detailed data, as long as the Markov property of the arrival and service processes hold. However, there is a significant modeling advantage by using the stochastic Petri net (SPN) paradigm to model the details of such a system. In addition, software tool support allows getting numeric analysis results quickly by solving the state probabilities in the background and without the need to run any simulation. Because of this efficiency, the equivalent SPN model of the Engset, Erlang-B and Erlang-C situation is introduced as novelty in this paper. Going beyond the original Erlang scenario, the user-in-the-loop (UIL) approach of demand shaping by closed-loop control is studied as an extension. In UIL, demand control is implemented by a dynamic usage-based tariff which motivates users to reduce or postpone the use of applications on their smart phone in times of light to severe congestion. In this paper, the effect of load on the price and demand reduction is modeled with an SPN based on the classical Erlang Markov chain structure. Numeric results are easily obtained and presented in this paper, including probability density functions (PDF) of the load situation, and a parameter analysis showing the effectiveness of UIL to reduce the overload probability. Keywords—User-in-the-loop (UIL); demand shaping; demand control; congestion; Erlang; stochastic Petri-net (SPN). I

First survey results of quantified user behavior in user-in-the-loop scenarios for sustainable wireless networks

Traffic in mobile radio networks is expected to continue to increase by 100% per year. This imposes a big challenge for future generations (4G and 5G) of access technologies which were previously dimensioned for over-provisioning esp