Performance Analysis of Spectrum Sensing Methods: A Numerical Approach

Recent enhancement of Long Term Evolution / Advanced (LTE/LTE-A) is aimed to increase the throughput of the Orthogonal Frequency Division Multiplexing (OFDM) system. This is quite obvious where both frequency and time division are employed in order to augment the system capacity. In LTE/LTE-A heterogeneous Networks (Het Nets), femto cells (He Node Bs) are the optimal choice to extend the coverage within indoor environment. Nonetheless, the deployment of such base stations, somewhat to certain extent, does create cross-tier and co-tier interferences with the macro cell users (UEmacro-eNB) that ostensibly can become a critical challenge. It is implied that the unutilized / idle spectrums reallocation might be one of the solutions to mitigate such challenge. However, the errorless spectrum sensing does pose another issue. This paper outlines the investigation findings where spectrum sensing techniques is deployed to maximize the spectrum detection capacity with minimum error in OFDM based Het Nets. In addition, in the attempt to increase the efficiency of spectrum resources, this paper proposes a sensing technique which is imposed over advanced energy detection technique to detect the idle spectrums. The result of the proposed scheme is evaluated using Monte Carlo simulation.

[1]  Jeffrey G. Andrews,et al.  Uplink capacity and interference avoidance for two-tier femtocell networks , 2007, IEEE Transactions on Wireless Communications.

[2]  Yonggyu Lee,et al.  Optimization of Cooperative Inter-Operability in Heterogeneous Networks with Cognitive Ability , 2011, IEEE Communications Letters.

[3]  B.M. Ali,et al.  Cooperative Spectrum Sensing with Distributed Detection Threshold , 2010, 2010 Second International Conference on Network Applications, Protocols and Services.

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

[5]  Jun Wang,et al.  Normalized energy detection based cooperative spectrum sensing with reporting errors in heterogeneous cognitive radio networks , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[6]  Tony Q. S. Quek,et al.  Throughput Optimization, Spectrum Allocation, and Access Control in Two-Tier Femtocell Networks , 2012, IEEE Journal on Selected Areas in Communications.

[7]  Mingsong Chen,et al.  Resource allocation in OFDM-based heterogeneous cognitive radio networks with imperfect spectrum sensing and guaranteed QoS , 2013, 2013 8th International Conference on Communications and Networking in China (CHINACOM).

[8]  Xing Chen,et al.  Detection efficiency of cooperative spectrum sensing in cognitive radio network , 2008 .

[9]  Hui Tian,et al.  Joint Power and Bandwidth Allocation Algorithm with QoS Support in Heterogeneous Wireless Networks , 2012, IEEE Communications Letters.

[10]  Weihua Zhuang,et al.  Decentralized Radio Resource Allocation for Single-Network and Multi-Homing Services in Cooperative Heterogeneous Wireless Access Medium , 2012, IEEE Transactions on Wireless Communications.

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

[12]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[13]  Geoffrey Ye Li,et al.  Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[14]  Hoon Kim,et al.  Joint Resource Allocation for Parallel Multi-Radio Access in Heterogeneous Wireless Networks , 2010 .