Joint power and bandwidth allocation in IEEE802.22 based cognitive LTE network

• Published in: Computer networks (Amsterdam, Netherlands : 1999) Vol. 71; pp. 117 - 129
• Main Authors: Asheralieva, Alia, Mahata, Kaushik
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 04.10.2014; Elsevier; Elsevier Sequoia S.A
• Subjects: 3GPP LTE; Algorithms; Applied sciences; Assignment problem; Bandwidth; Bandwidths; Channels; Computer science; control theory; systems; Computer systems and distributed systems. User interface; CRN; Energy efficiency; Equipments and installations; Exact sciences and technology; IEEE standards; IEEE802.22; Mobile communication systems; Mobile radiocommunication systems; Networks; Partnerships; Radiocommunications; Resource allocation; Software; Spectrum allocation; Studies; Systems, networks and services of telecommunications; Telecommunications; Telecommunications and information theory; Teletraffic; Wireless communication; Wireless networks; 3GPP LTE; IEEE802.22; CRN; Resource allocation; Network architecture; Downlink; Power allocation; Optimal strategy; Optimal allocation; Coding; Bandwidth; Queue; Energy spectrum; Stability; Cellular radio; Frequency allocation; Buffer system; Bandwidth allocation; Energy savings; Cognitive theory; Wireless network; Capacity constraint; Transmission rate; Mobile computing; Signal to noise ratio
• ISSN: 1389-1286; 1872-7069
• DOI: 10.1016/j.comnet.2014.06.014

We investigate the problem of energy-efficient dynamic spectrum access (DSA) in a cognitive Third Generation Partnership Project (3GPP) long-term evolution (LTE) network based on IEEE802.22 architecture. In this architecture, the network resources are allocated to the end-users and the evolved NodeBs (eNBs) by the spectrum manager (SM) using some optimal resource allocation strategy. In particular, we propose to assign the bandwidth and transmission power to the uplink and downlink of LTE system so that the total transmission power is minimized subject to capacity constraints, queue stability constraints, and some integer restrictions on the bandwidth. To find the buffer occupancy in the system, we use modified Shannon expression which depends on signal-to-noise ratio (SNR) and modulation and coding scheme (MCS). Unlike previous works, the proposed resource allocation algorithm is derived based on realistic assumptions, such as discrete spectrum resources, relation between transmission rate, MCS and the channel quality. Performance of the algorithm is evaluated using simulations in OPNET environment. The algorithm shows consistent performance improvement when compared with other relevant resource allocation techniques.