It is estimated that by 2020 the traffic in wireless access networks will increase drastically as compared to the 2010 level. To meet this challenge, it needs the huge increase of spectrum, very high spectrum efficiency, dense deployment of small cells, and highly energy efficient solutions. Combining these together, we believe that the cognitive wireless access network would be a promising solution. In this paper, we study the energy efficient spectrum access problem in dynamic spectrum access (DSA) based wireless access networks, in which densely deployed access points (AP) provide open access to mobile terminals (MT) by spectrum opportunities enabled by primary users (PU). The question is how the spectrum is allocated to MT via AP so that the bit/energy to deliver the data is maximized. We separate the problem into the channel selection problem of AP and the AP association problem of MT, and propose the distributed AP channel selection algorithm and MT association algorithm, which are run on the AP and MT separately, with a joint goal to improve the bit/energy delivery by the efficient use of spectrum. The proposed algorithms only rely on local information exchange to estimate inter-cell interference, and are therefore scalable to large networks. The performance of the proposed algorithms are evaluated by simulation. It shows in average around 10% bit/energy improvement over the algorithms which randomly allocate channels and associate MTs.

Keywords: cognitive radio system, wireless access network, channel assignment, energy efficiency, interference control

  The Cognitive Radio paradigm is aimed to optimize the utilization of licensed spectrum bands thanks to coexistence within the same network of licensed (primary) and cognitive (secondary) users. In this context, one of the most important key aspects is represented by an efficient resource allocation between secondary and primary users. Modeling it as an optimization problem, this paper provides a modified version of the well-known Iterated Water-Filling algorithm and a novel approach based on a game theory framework to solve this issue in a distributed and fair way. In particular, the proposed game is formulated as an S-Modular Game, since it provides useful tools for the definition of multi objective distributed algorithms in the context of radio communications. This paper provides also a performance comparison among the proposed solutions and the Simulated Annealing algorithm, that represents one of the most frequently used technique in this context.

Keywords: cognitive radio, resource allocation, game theory, energy efficiency

  In cognitive radio networks, the secondary users need to coordinate among themselves to reap the benefits of cooperative spectrum sensing. In this paper, we study and analyse the energy efficiency of two generic cooperative sensing schemes in an ad hoc WLAN backdrop – distributed cooperative sensing scheme and centralized cluster based cooperative sensing scheme. We further propose corresponding enhanced and adaptive versions of these two schemes where only a fraction of nodes sense in each sensing cycle, as opposed to all the nodes in the network. Using an analytical energy model for sensing, we quantify the energy costs of each of these schemes and perform a comparative numerical analysis to demonstrate the amount of energy savings of the proposed cooperative schemes over their generic counterparts and non-cooperative schemes.

Keywords: cognitive radio, cooperative sensing, energy efficiency, WLAN

  Cooperative relaying has recently appeared as one of the widely recognized features for future wireless communication systems. The great potential of cooperative communication in increasing system capacity and enhancing power efficiency has attracted large efforts over the last few years. In this paper, we propose a Cooperation Loop as a reference model for all algorithms in relay based cooperative wireless networks. Using this model, we discuss cooperative relay based protocols in IEEE 802.11 standards and limits posed to cognitive approaches. We show the potential location area of relay nodes as well as the performance bounds of capacity gain, delay and power efficiency achieved in relay based scenarios for any cooperative cognitive algorithms.

Keywords: cooperation, cognitive, IEEE 802.11 MAC protocols, capacity, energy efficiency

  Wi-Fi technology, plays a major role in society thanks to its widespread availability, ease of use and low cost. To assure its long term viability in terms of capacity and ability to share the spectrum efficiently, it is of paramount to study the spectrum utilization and congestion mechanisms in live environments. In this paper the service level in the 2.4 GHz ISM band is investigated with focus on todays IEEE 802.11 WLAN systems with support for the 802.11e extension. Here service level means the overall Quality of Service (QoS), i.e. can all devices fulfill their communication needs? A cross-layer approach is used, since the service level can be measured at several levels of the protocol stack. The focus is on monitoring at both the Physical (PHY) and the Medium Access Control (MAC) link layer simultaneously by performing respectively power measurements with a spectrum analyzer to assess spectrum utilization and packet sniffing to measure the congestion. Compared to traditional QoS analysis in 802.11 networks, packet sniffing allows to study the occurring congestion mechanisms more thoroughly. The monitoring is applied for the following two cases. First the influence of interference between WLAN networks sharing the same radio channel is investigated in a controlled environment. It turns out that retry rate, Clear-To-Send (CTS), Request-To-Send (RTS) and (Block) Acknowledgment (ACK) frames can be used to identify congestion, whereas the spectrum analyzer is employed to identify the source of interference. Secondly, live measurements are performed at three locations to identify this type of interference in real-live situations. Results show inefficient use of the wireless medium in certain scenarios, due to a large portion of management and control frames compared to data content frames (i.e. only 21% of the frames is identified as data frames).

Keywords: interference, IEEE 802.11e, ISM band, congestion, cross-layer, spectrum sensing