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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Uykan, Z. Jantti, R. |
| Copyright Year | 2015 |
| Description | Author affiliation: COMNET, Sch. of Electr. Eng., Aalto Univ., Espoo, Finland (Jantti, R.) || Electr. Eng., American Univ. of the Middle East, Egaila, Kuwait (Uykan, Z.) |
| Abstract | Mobile Converged Heterogeneous Network (MCN) is seen as a viable solution to the exponentially increasing mobile traffic demand of near-future mobile services. Recently, a new dimension for improving the system performance of TDD based wireless systems has been introduced to the 3GPP standards: Dynamic TDD, which allows cell-specific frame configurations and cell-specific control of the Transmit Order (TO). In this paper, we propose unleashing the TO options in the context of MCNs where base stations are coordinated via a central controller for effective base-station-to-base-station interference cancellation (B2B-IC), and we investigate the corresponding performance improvements. Simulation results for an MCN including macro, micro, pico, femto and small cell networks operating in the same spectrum show that the TO with B2B-IC in MCN provide remarkable performance improvements at the expense of an increase in the signal exchange among the centralized controller and the base stations. |
| Starting Page | 469 |
| Ending Page | 473 |
| File Size | 981077 |
| Page Count | 5 |
| File Format | |
| e-ISBN | 9781479953448 |
| DOI | 10.1109/IWCMC.2015.7289129 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-24 |
| Publisher Place | Croatia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Wireless communication Transmit Order Channel capacity Base-station-to-base-station interference cancellation Heterogeneous Networks Interference Mobile communication Mobile Converged Network Mobile computing Optimization Signal to noise ratio |
| Content Type | Text |
| Resource Type | Article |
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