A Hybrid Underlay/Overlay Transmission Mode for Cognitive Radio Networks with Statistical Quality-of-Service Provisioning

In order to achieve better statistical Quality-of-Service (QoS) provisioning for cognitive radio networks (CRN), in this paper, we develop a hybrid underlay/overlay transmission mode for CRNs. Specifically, by applying the theory of effective capacity and taking PN's activity statistics into consideration, we first analyze the maximum achievable throughput of the CRN under two dominant transmission modes, namely underlay and overlay, respectively, and provide efficient algorithms to derive optimal transmission strategies for the two modes. Following the analyses, we then propose a hybrid underlay/overlay transmission mode, through which the cognitive users' QoS requirements can be better guaranteed and network throughput can be further improved. Moreover, we analyze the optimal transmission strategies for both underlay and overlay modes under two limiting cases. Analyses indicate that 1) for the loose QoS requirement, optimal transmission strategies for both underlay and overlay modes become the water-filling algorithm; and 2) for the stringent QoS requirement, the cognitive user will transmit with constant rate. Furthermore, the impact of imperfect channel estimations on our proposed transmission mode is discussed. Simulation results are provided to demonstrate the impacts of delay QoS requirements and PN's activity statistics on maximizing the delay-constrained throughput for both underlay and overlay modes and verify the effectiveness of our proposed transmission mode. Moreover, for the overlay mode, we observe that 1) a unique optimal sensing time exists under the given QoS constraint; and 2) the optimal sensing time surprisingly increases as the QoS constraint gets more stringent.

[1]  Dan Xu,et al.  Efficient and Fair Bandwidth Allocation in Multichannel Cognitive Radio Networks , 2012, IEEE Transactions on Mobile Computing.

[2]  Chintha Tellambura,et al.  Optimal Bandwidth and Power Allocation for Sum Ergodic Capacity Under Fading Channels in Cognitive Radio Networks , 2010, IEEE Transactions on Signal Processing.

[3]  Ying-Chang Liang,et al.  Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity , 2008, IEEE Transactions on Wireless Communications.

[4]  Sonia Aïssa,et al.  Capacity and power allocation for spectrum-sharing communications in fading channels , 2009, IEEE Transactions on Wireless Communications.

[5]  Uday B. Desai,et al.  Distributed Power Allocation for Secondary Users in a Cognitive Radio Scenario , 2012, IEEE Transactions on Wireless Communications.

[6]  Dapeng Wu,et al.  Effective capacity: a wireless link model for support of quality of service , 2003, IEEE Trans. Wirel. Commun..

[7]  Sami Akin,et al.  Cognitive radio transmission under QoS constraints and interference limitations , 2012, EURASIP Journal on Wireless Communications and Networking.

[8]  Ananthram Swami,et al.  Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework , 2007, IEEE Journal on Selected Areas in Communications.

[9]  A. Goldsmith,et al.  Variable-rate variable-power MQAM for fading channels , 1996, Proceedings of Vehicular Technology Conference - VTC.

[10]  Ying-Chang Liang,et al.  Optimal Power Allocation Strategies for Fading Cognitive Radio Channels with Primary User Outage Constraint , 2011, IEEE Journal on Selected Areas in Communications.

[11]  Yichen Wang,et al.  Power Allocation for Statistical QoS Provisioning in Opportunistic Multi-Relay DF Cognitive Networks , 2013, IEEE Signal Processing Letters.

[12]  Jeffrey H. Reed,et al.  Outage probability based comparison of underlay and overlay spectrum sharing techniques , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[13]  Hsiao-Hwa Chen,et al.  Adaptive power allocation with quality-of-service guarantee in cognitive radio networks , 2009, Comput. Commun..

[14]  Yichen Wang,et al.  Resource allocation and access strategy selection for QoS provisioning in cognitive networks , 2012, 2012 IEEE International Conference on Communications (ICC).

[15]  Pravin Varaiya,et al.  Capacity of fading channels with channel side information , 1997, IEEE Trans. Inf. Theory.

[16]  Sami Akin,et al.  Effective Capacity Analysis of Cognitive Radio Channels for Quality of Service Provisioning , 2010, IEEE Trans. Wirel. Commun..

[17]  Jia Tang,et al.  Quality-of-Service Driven Power and Rate Adaptation over Wireless Links , 2007, IEEE Transactions on Wireless Communications.

[18]  Gi-Hong Im,et al.  Joint Sensing Adaptation and Resource Allocation for Cognitive Radio with Imperfect Sensing , 2012, IEEE Transactions on Communications.

[19]  K. B. Letaief,et al.  Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks , 2009, IEEE Transactions on Wireless Communications.

[20]  Leila Musavian,et al.  Effective capacity of delay-constrained cognitive radio in Nakagami fading channels , 2010, IEEE Transactions on Wireless Communications.

[21]  Sami Akin,et al.  Performance Analysis of Cognitive Radio Systems under QoS Constraints and Channel Uncertainty , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[22]  Leila Musavian,et al.  Fundamental capacity limits of cognitive radio in fading environments with imperfect channel information , 2009, IEEE Transactions on Communications.

[23]  Jing Lv,et al.  Comparison of underlay and overlay spectrum sharing strategies in MISO cognitive channels , 2012, 2012 7th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM).

[24]  Yonghong Zeng,et al.  Sensing-Throughput Tradeoff for Cognitive Radio Networks , 2008, IEEE Trans. Wirel. Commun..

[25]  Cheng-Shang Chang,et al.  Stability, queue length, and delay of deterministic and stochastic queueing networks , 1994, IEEE Trans. Autom. Control..

[26]  Victor C. M. Leung,et al.  Orthogonal Transmissions for Spectrum Underlay MISO Cognitive Radio , 2012, IEEE Transactions on Wireless Communications.

[27]  Halim Yanikomeroglu,et al.  Access Strategies for Spectrum Sharing in Fading Environment: Overlay, Underlay, and Mixed , 2010, IEEE Transactions on Mobile Computing.

[28]  Bang Chul Jung,et al.  Power allocation policies with full and partial inter-system channel state information for cognitive radio networks , 2013, Wirel. Networks.

[29]  Mansoor Shafi,et al.  Capacity Limits and Performance Analysis of Cognitive Radio With Imperfect Channel Knowledge , 2010, IEEE Transactions on Vehicular Technology.

[30]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.