Channel allocation schemes

About: Channel allocation schemes is a research topic. Over the lifetime, 10656 publications have been published within this topic receiving 182117 citations.

Interference management for 4G cellular standards [WIMAX/LTE UPDATE]

Abstract: 4G cellular standards are targeting aggressive spectrum reuse (frequency reuse 1) to achieve high system capacity and simplify radio network planning. The increase in system capacity comes at the expense of SINR degradation due to increased intercell interference, which severely impacts cell-edge user capacity and overall system throughput. Advanced interference management schemes are critical for achieving the required cell edge spectral efficiency targets and to provide ubiquity of user experience throughout the network. In this article we compare interference management solutions across the two main 4G standards: IEEE 802.16m (WiMAX) and 3GPP-LTE. Specifically, we address radio resource management schemes for interference mitigation, which include power control and adaptive fractional frequency reuse. Additional topics, such as interference management for multitier cellular deployments, heterogeneous architectures, and smart antenna schemes will be addressed in follow-up papers.

Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications Over Cognitive Radio Networks

Abstract: In this paper, we propose a dynamic channel-selection solution for autonomous wireless users transmitting delay-sensitive multimedia applications over cognitive radio networks. Unlike prior works that seldom consider the requirement of the application layer, our solution explicitly considers various rate requirements and delay deadlines of heterogeneous multimedia users. Note that the users usually possess private utility functions, application requirements, and distinct channel conditions in different frequency channels. To efficiently manage available spectrum resources in a decentralized manner, information exchange among users is necessary. Hence, we propose a novel priority virtual queue interface that determines the required information exchanges and evaluates the expected delays experienced by various priority traffics. Such expected delays are important for multimedia users due to their delay-sensitivity nature. Based on the exchanged information, the interface evaluates the expected delays using priority queuing analysis that considers the wireless environment, traffic characteristics, and the competing users' behaviors in the same frequency channel. We propose a dynamic strategy learning (DSL) algorithm deployed at each user that exploits the expected delay and dynamically adapts the channel selection strategies to maximize the user's utility function. We simulate multiple video users sharing the cognitive radio network and show that our proposed solution significantly reduces the packet loss rate and outperforms the conventional single-channel dynamic resource allocation by almost 2 dB in terms of video quality.

Channel surfing: defending wireless sensor networks from interference

Abstract: Wireless sensor networks are susceptible to interference that can disrupt sensor communication. In order to cope with this disruption, we explore channel surfing, whereby the sensor nodes adapt their channel assignments to restore network connectivity in the presence of interference. We explore two different approaches to channel surfing: coordinated channel switching, where the entire sensor network adjusts its channel; and spectral multiplexing, where nodes in a jammed region switch channels while nodes on the boundary of a jammed region act as radio relays between different spectral zones. For spectral multiplexing, we have devised both synchronous and asynchronous strategies to facilitate the spectral scheduling needed to improve network fidelity when sensor nodes operate on multiple channels. In designing these algorithms, we have taken a system-oriented approach that has focused on exploring actual implementation issues under realistic network settings. We have implemented these proposed methods on a testbed of 30 Mica2 sensor nodes, and the experimental results show that these strategies can each repair network connectivity in the presence of interference without introducing significant overhead.

Pilot-aided channel estimation for OFDM/OQAM

Abstract: OFDM/offsetQAM is an interesting alternative to classical OFDM modulation, as it does not require the use of guard interval. This characteristic makes its spectral efficiency optimal. On the other hand, this modulation is less robust to Rayleigh fading channel. Indeed, when classical channel estimation used for OFDM modulation is applied straightforwardly to OFDM/OQAM modulation, an intrinsic inter-symbol-interference is observed. This deeply degrades its performances. In this paper, we theoretically explain this phenomenon and propose a reliable method to significantly reduce it. Results of different methods of pilot-aided channel estimation over delay-Doppler channels are shown in this paper.

Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game

Abstract: We consider dynamic spectrum access among cognitive radios from an adaptive, game theoretic learning perspective. Spectrum-agile cognitive radios compete for channels temporarily vacated by licensed primary users in order to satisfy their own demands while minimizing interference. For both slowly varying primary user activity and slowly varying statistics of "fast" primary user activity, we apply an adaptive regret based learning procedure which tracks the set of correlated equilibria of the game, treated as a distributed stochastic approximation. This procedure is shown to perform very well compared with other similar adaptive algorithms. We also estimate channel contention for a simple CSMA channel sharing scheme.