With the huge success of cellular mobile radio communications, demand for wireless services, applications, and technologies is expected to increase further. Such an increase forces recently emerging technologies (e.g., 4G) to coexist with the old ones (e.g., 2G–3G) in next generation wireless networks (NGWNs). In order for NGWNs to support all of these services and applications with the ever-increasing demand, wireless radio interference needs to be handled in an effective manner. Interference is a phenomenon which degrades the overall system capacity, affects the quality of service, and causes call drops and unnecessary handoffs in cellular mobile systems.

Interference is a very important concept from the perspective of military and of national security. Both unintentional and intentional interference, which is also known as jamming, should be cleared away as soon as possible for security reasons. Therefore, identification of interference in a reliable manner is a crucial task for all of the future wireless communications systems.

In this study, identification of radio interference in NGWNs is established. The proposed method takes into account the general characteristics of wireless propagation environments.

Since it is difficult to completely define a general wireless propagation environment, statistical properties of widely used propagation environment classification such as urban and suburban is analyzed. Both first- and second-order of the statistical characteristics of wireless propagation environments are considered.

It is shown that the proposed method can identify the presence of interference under practical scenarios in a reliable manner.

In addition, it is demonstrated that the absence of a priori knowledge about the ambient noise power does not affect the performance of the proposed method.

Interference management is predicted to be an essential part of the system design for emerging NGWNs. Interference is also extremely important for military and national security applications and services. Therefore, identification of any form of interference in a reliable manner is of crucial importance. In this study, a method that can identify the presence of interference reliably under practical scenarios is proposed. The method proposed does need any a priori information to identify the interference.


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