In this article, we present a layered radio environment map architecture along with its applications to the self-organizing network functionalities of heterogeneous LTE radio access networks comprising macrocells and femtocells. In this architecture, the functional blocks reappear with different spatial and temporal granularity at different architectural layers. Although the radio environment map is one of the key promising technologies to enable future cognitive radio networks, it can be already applied to provide limited cognitive capabilities to today's commercial networks too. We explain why, and show how, this architecture can support today¿s LTE self-organizing network functions like automatic neighbor relation and minimization of drive tests, and also allow the smooth introduction of new radio access technologies through refarming. We also demonstrate some of the quantitative benefits adopting radio environment map technologies can bring using the minimization of drive tests as an example.

Traditional design of wireless networks mainly focuses on system capacity and spectral efficiency. As green networking is an inevitable trend, energy-efficient design for future wireless networks becomes paramount. In this paper, we address energy-efficient resource management in downlink orthogonal frequency division multiple access networks. The focus is targeted toward multi-cell networks, which are composed of multiple base stations (BSs) sharing the available radio resources. Consequently, greater emphasis is given to techniques that take inter-cell interference into account. Resource management in our context refers to the task of allocating the radio resources in order to maximize energy efficiency. We devise resource management techniques that jointly tackle the problems of scheduling and power control. Accordingly, we adopt two different approaches: a centralized approach, where BSs coordinate in order to reach a globally optimal energy-efficient solution, and a distributed approach, where BSs selfishly strive to maximize their own energy efficiency. We portray the centralized approach as a convex optimization problem, whereas we have recourse to non-cooperative game theory to model the distributed approach. In particular, we show that the non-cooperative game converges to a unique Nash equilibrium in low- and high-interference scenarios. We perform thorough numerical simulations to quantify the discrepancy between the centralized and distributed approaches, and identify the conditions where they have precedence over the state of the art. Moreover, the simulation results highlight the fast convergence of our algorithms, which is a precious asset for realistic deployments.

TD-CDMA TDD technique allows UMTS to utilize the bandwidth and the rare radio resource more efficiently if dynamic channel allocation is used. This technique is suited especially for systems that offer highly asymmetric services. However, the rate of symmetry is not the same in all cells. Hence, it is possible that in some slots, called crossed slots, a set of cells is active in downlink and another set is active in uplink. Inter-BS and inter-MS interferences arise in these slots and can degrade dramatically the QoS. In this paper, we introduce a scheme to prevent mobiles that can introduce very high inter-mobile interference from being active during crossed slots. In this scheme, a mobile can be active during a crossed slot with mobiles of a neighboring cell, if the path gain between the mobile and the neighboring base station is less than a given threshold. For high loads, this scheme has shown better results than common switching point technique where crossed slots are forbidden and other interference avoidance methods.

The paper investigates the use of Radio Environment Maps (REMs) as a tool for Interference Management (IM) in two-tier cellular networks comprising macro- and femto-cells. The REMs are databases that provide, through different instances distributed over network elements, a variety of network- and user-related context information for improving IM and Radio Resource Management (RRM) procedures. In this context, the focus in this paper is to present the benefit of using REM information on practical power control schemes for the Femtocell downlink transmission in co-channel two-tier deployment.

Activity patterns of primary users have significant influence on the opportunities for secondary use of spectrum. In this paper we explore this impact in terms of spatial spectrum reuse opportunities. More specifically, we model the primary user activity as a Semi-Markov ON/OFF process with varying distributions of holding times of ON and OFF states. We have used realistic holding time distributions obtained from extensive measurement campaigns. These activity patterns are combined with a collection of primary user transmitter locations, based on a real deployed cellular network. Based on these, we study the impact of activity model parameters on opportunities of spatial spectrum reuse. The results indicate that for the scenarios studied here the overall duty cycle defined by the activity pattern plays the key role also in determining spatial spectrum opportunities. We also discuss applications of the obtained results, including development of lightweight models for occurrences of spectrum opportunities over both time and space.

In this paper we propose a heuristic algorithm that exploits additional information that can be in general known by a secondary network willing to opportunistically access the spectrum allocated to a primary network. The algorithm aims at finding the maximum allowed transmission power with which a secondary node can transmit while respecting primary constraints. It is designed to be used in the presence of multiple primary transmitters with known positions but without information about their activity patterns. The estimation of the allowed transmission power is derived using a semi-analytical model characterizing interference probability. The latter is defined as the probability that the interference generated by the secondary node to any of the users in a primary cell exceeds a fixed threshold. The main idea is to autonomously determine a detection threshold based on the relative position of the secondary node towards base stations. Simulation results in a simple scenario are analyzed in order to explain the behavior of the algorithm. In addition, more results are introduced to evaluate the performance of the algorithm in more realistic scenarios.