Joint Subcarrier and Antenna State Selection for Cognitive Heterogeneous Networks With Reconfigurable Antennas

Reconfigurable antennas (RA) offer an emerging technology that allows wireless devices to alter their antenna states determined by different radiation patterns to maximize received signal strength. In this paper, we consider multiuser orthogonal frequency-division multiple access cognitive heterogeneous networks (HetNets) and we study the potential benefits of employing RA in terms of improving the overall network capacity. In cognitive HetNets, a secondary network is allowed to share the spectrum with the primary network under the condition that the interference level experienced by the primary network is below a predetermined threshold. To satisfy this interference constraint, a secondary user (SU) employs a power control mechanism, which typically limits its transmission power and thus reduces substantially its performance. Moreover, the large number of users expected for next-generation networks brings dense interference to the secondary network and, as such, even efficient interference mitigation and resource allocation techniques can fail in maintaining an acceptable performance level for the network. In this work, we consider utilizing RA technology at SUs to act as an additional resource in terms of selecting antenna radiation patterns that improve received signal strength among SUs. This also limits the mutual interference between the secondary and primary networks. We propose a game theoretical framework for jointly selecting the subcarriers as well as the RA antenna state at each SU that maximizes the overall capacity of the network while meeting the interference target in the primary network. Using potential games that guarantee the existence of a Nash equilibrium, our results show that, by selecting the best RA state and subcarriers for each SU, the capacity of the secondary network increases substantially compared to a scenario with conventional omni-directional antennas.

[1]  Dusit Niyato,et al.  Distributed resource allocation in wireless networks under uncertainty and application of Bayesian game , 2011, IEEE Communications Magazine.

[2]  Alireza Attar,et al.  Collaborative Sub-Channel Allocation in Cognitive LTE Femto-Cells: A Cooperative Game-Theoretic Approach , 2013, IEEE Transactions on Communications.

[3]  Giulio Colavolpe,et al.  Potential Games for Energy-Efficient Power Control and Subcarrier Allocation in Uplink Multicell OFDMA Systems , 2012, IEEE Journal of Selected Topics in Signal Processing.

[4]  Hamid Jafarkhani,et al.  Space-time-state block coded mimo communication systems using reconfigurable antennas , 2009, IEEE Transactions on Wireless Communications.

[5]  Syed A. Jafar,et al.  Aiming Perfectly in the Dark-Blind Interference Alignment Through Staggered Antenna Switching , 2011, IEEE Trans. Signal Process..

[6]  Pradeep Dubey,et al.  Strategic complements and substitutes, and potential games , 2006, Games Econ. Behav..

[7]  Guoan Bi,et al.  A Hierarchical Game Theoretic Framework for Cognitive Radio Networks , 2012, IEEE Journal on Selected Areas in Communications.

[8]  Gang Feng,et al.  A Game-Theoretic Framework for Interference Coordination in OFDMA Relay Networks , 2012, IEEE Transactions on Vehicular Technology.

[9]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[10]  F. Paganini,et al.  New economic perspectives for resource allocation in wireless networks , 2005, Proceedings of the 2005, American Control Conference, 2005..

[11]  Yong Huat Chew,et al.  Performance Analysis of Downlink Multi-Cell OFDMA Systems Based on Potential Game , 2012, IEEE Transactions on Wireless Communications.

[12]  Ross D. Murch,et al.  Improving Space-Time Code Performance in Slow Fading Channels using Reconfigurable Antennas , 2012, IEEE Communications Letters.

[13]  Hao Wu,et al.  Interference mitigation in two-tier OFDMA femtocell networks: A potential game approach , 2012, 2012 International Conference on Wireless Communications and Signal Processing (WCSP).

[14]  L. Shapley,et al.  Potential Games , 1994 .

[15]  F. Richard Yu,et al.  Energy-Efficient Resource Allocation for Heterogeneous Cognitive Radio Networks with Femtocells , 2012, IEEE Transactions on Wireless Communications.

[16]  Bedri A. Cetiner,et al.  Frequency, Radiation Pattern and Polarization Reconfigurable Antenna Using a Parasitic Pixel Layer , 2014, IEEE Transactions on Antennas and Propagation.

[17]  Mérouane Debbah,et al.  On the base station selection and base station sharing in self-configuring networks , 2009, VALUETOOLS.

[18]  Mihaela van der Schaar,et al.  Robust Power Control for Heterogeneous Users in Shared Unlicensed Bands , 2014, IEEE Transactions on Wireless Communications.

[19]  Ang-Hsun Tsai,et al.  Stable Subchannel Allocation for OFDMA Femtocells with Switched Multi-Beam Directional Antennas , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

[20]  J.T. Bernhard,et al.  Performance Study of Pattern Reconfigurable Antennas in MIMO Communication Systems , 2008, IEEE Transactions on Antennas and Propagation.

[21]  Kapil R. Dandekar,et al.  Enhancing wireless security through reconfigurable antennas , 2010, 2010 IEEE Radio and Wireless Symposium (RWS).

[22]  A.M. Sayeed,et al.  Maximizing MIMO Capacity in Sparse Multipath With Reconfigurable Antenna Arrays , 2007, IEEE Journal of Selected Topics in Signal Processing.

[23]  Mohamed-Slim Alouini,et al.  Outage Analysis for Underlay Cognitive Networks Using Incremental Regenerative Relaying , 2013, IEEE Transactions on Vehicular Technology.

[24]  F. Richard Yu,et al.  Interference-aware energy-efficient resource allocation for heterogeneous networks with incomplete channel state information , 2013, 2013 IEEE International Conference on Communications (ICC).

[25]  Halim Yanikomeroglu,et al.  Interference-Aware Energy-Efficient Resource Allocation for OFDMA-Based Heterogeneous Networks With Incomplete Channel State Information , 2015, IEEE Transactions on Vehicular Technology.

[26]  Sudarshan Guruacharya,et al.  Hierarchical Competition for Downlink Power Allocation in OFDMA Femtocell Networks , 2013, IEEE Transactions on Wireless Communications.