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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Changchun Li Lingling Xu Dongfeng Yuan Feijin Shi |
| Copyright Year | 2009 |
| Description | Author affiliation: School of Information Science and Engineering Shandong University Jinan, Shandong, 250100, China (Changchun Li; Lingling Xu; Dongfeng Yuan; Feijin Shi) |
| Abstract | This paper is concerned with a cross-layer design combining adaptive modulation and coding (AMC) at the physical layer with hybrid automatic repeat request (HARQ) at the data link layer (LL) based on the rate compatible convolutional codes. In order to satisfy the prescribed delay and packet error rate (PER) constraints at LL, as well as to maximize the spectral efficiency, we apply the type-II and type-III HARQ to the cross layer design framework. We have derived the closed-form expression of the PER and average spectral efficiency for the transmissions over Nakagami-m communication channel. Numerical results show that the application of the type-III HARQ could achieve the highest spectral efficiency and the lowest PER, but it is the most complex. The type-I HARQ has the lowest spectral efficiency and the highest PER, but it has the lowest complexity. Meanwhile the type-II HARQ has a compromise between them. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 360705 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424443376 |
| DOI | 10.1109/CHINACOM.2009.5339800 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-26 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Convolutional codes Adaptive Modulation and Coding (AMC) Cross layer design Error analysis Hybrid Automatic Repeat reQuest (HARQ) Physical layer Closed-form solution Delay Communication channels Nakagami-m channel Cross-Layer Design Performance analysis Automatic repeat request Modulation coding |
| Content Type | Text |
| Resource Type | Article |
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