Special Issue: Cognitive radio, software‐defined radio, and adaptive wireless systems
Hüseyin Arslan, Joseph Mitola · Wireless Communications and Mobile Computing · 2007
Today's wireless services have come a long way since the roll out of the conventional voice-centric cellular systems. The demand for wireless access in voice and high rate data multi-media applications has been increasing. New generation wireless communication systems are aimed at accommodating this demand through better resource management and improved transmission technologies. Pushing the adaptive system design further by introducing multi-dimensional awareness, sensing, and learning from its experiences to reason, plan, and decide future actions to meet user needs brings the 'Cognitive Radio' concept into the wireless world. Even though there is no consensus on the formal definition of cognitive radio as of now, the concept has evolved recently to include various meanings in several contexts. One main aspect concerns autonomously exploiting locally unused spectrum to provide new paths to spectrum access. Other aspects include interoperability across several networks; roaming across borders while staying in compliance with local regulations; adapting the system, transmission, and reception parameters without user intervention; and having the ability to understand and follow actions and choices taken by their users, learning to become more responsive over time. The interest in increasing spectrum access and improving spectrum efficiency combined with both the introduction of software-defined radios (SDR) and the realization that machine learning can be applied to radios has created intriguing new possibilities for wireless radio research. This special issue discusses the cognitive radio, SDR, and adaptive radio concepts from several directions. There are many fundamental and practical issues that need to be studied more to ensure the success of these concepts in wireless communication markets. We are delighted that this special issue addresses some of these issues with eight papers selected through a competitive peer review process. In addition to the peer-reviewed papers, one invited paper is included. First, the invited paper discusses the practical implementation of cognitive radio including passing environmental information from the radio to the cognitive engine, using this information and performing real-time control of the radio platform by the cognitive engine. This paper provides a broad view to the readers and relates other technical papers to the larger themes of cognitive radio. A central value proposition of cognitive radio is to use limited radio spectrum resources as efficiently as possible. Opportunistic spectrum usage exploits the unused part of the spectrum to increase capacity. However, this requires spectrum awareness and new techniques for efficient utilization of densely occupied spectrum. The paper entitled 'Spectrum sensing in cognitive radio networks: The cooperation-processing tradeoff' discusses spectral awareness. Local and cooperative spectrum sensing and related issues are discussed under realistic radio channel conditions with fading. Next, in the paper entitled 'Spectrum sharing through distributed coordination in dynamic spectrum access networks,' techniques for the sharing of available spectrum are discussed. Coordination of the spectrum usage to support fair access to spectrum with minimum mutual interference is discussed. Related to these two papers, the fourth paper 'Formalizing the interference temperature model' defines the interference temperature model, and derives algorithms for computing radio frequency (RF) transmission parameters that maximize both capacity and spectral efficiency for a given RF environment. Similar to radio spectrum, radiated power is also a very important resource in wireless communications, especially for wireless sensor networks. The battery power is limited in small wireless devices, so it must be used very efficiently. One important consideration in cognitive radio is system design to adaptively use power as efficiently as possible. The fifth paper 'Efficient duty cycling through prediction and sampling in wireless sensor networks' deals with this issue through an innovative medium-access-control (MAC) layer protocol for wireless sensor networks for an adaptive interface to achieve ultra-low power operation. The next two papers address SDR implementation of cognitive radio. The paper entitled 'Automatic antenna tuning unit for software-defined and cognitive radio' discusses the implementation of an automatic antenna tuning unit system (ATU). Antennas for true SDR and cognitive radio realizations must cover a variety of frequency bands with radiation and reception parameters suited to different wireless standards. This paper covers recent progress in reconfigurable antenna technology. On the other hand, the paper entitled 'DSP implementation of a bit loading algorithm for adaptive wireless multicarrier transceivers' studies fixed-point DSP hardware implementations of an adaptive bit loading algorithm that can increase the capacity of the multicarrier systems like OFDM efficiently via implementation with reasonable computational complexity. The last two papers are related to the optimization of the radio resource and transmission parameters. The paper entitled 'Cognitive engine implementation for wireless multicarrier transceivers' presents a genetic algorithm (GA) driven cognitive engine for single carrier and multicarrier systems. The last paper entitled 'Install or invoke: The optimal trade-off between performance and cost in the design of multi-standard reconfigurable radios' finds the optimal trade-off between performance and cost, via a mathematical model of the design choices represented in a graph of progressively simpler functional modules. We thank the contributors of this special issue for their excellent contributions and for working with us to publish their work. Also, we extend our great appreciation to the reviewers who dedicated their valuable time to provide constructive comments, suggestions, and corrections. Finally, we thank the Editor-in-Chief, Professor Mohsen Guizani, and the staff at Wiley for their guidance. With such support, we believe that this special issue offers a considerable and timely contribution in the area of cognitive radio, and we hope that our readers will benefit from these papers and find them interesting.