Delay constrained throughput optimization in multi-hop AF relay networks, using limited quantized CSI
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| Title: | Delay constrained throughput optimization in multi-hop AF relay networks, using limited quantized CSI |
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| Authors: | Taki, Mehrdad, Svensson, Tommy, 1970, Nezafati, Mohammad Bagher |
| Source: | Eurasip Journal on Wireless Communications and Networking. 2019(1) |
| Subject Terms: | Amplify and forward relaying, Adaptive modulation and coding, Discrete link adaptation, Delay-QoS constraint, Multi-hop relay |
| Description: | In this paper, we analyze the throughput of multi-hop amplify and forward (AF) relay networks in delay-constrained scenario. Using quantized channel state information (CSI), the transmission rates and powers are discretely adapted with individual average power constraint on each node. A sub-gradient projection-based algorithm is utilized, by which there is no need for probability density functions (PDFs) to solve the optimization problem. Our numerical evaluations show that the sub-gradient projection-based algorithm results in a comparable performance with an analytical approach using PDFs. As shown, a considerably better performance obtained by the designed scheme compared to previous schemes with constant power transmission. More than 70% throughput improvement is achieved by our scheme compared to constant power transmission with just two more feedback bits and a short training time required at the beginning of the transmission. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/510235 https://research.chalmers.se/publication/511370 https://research.chalmers.se/publication/511370/file/511370_Fulltext.pdf |
| Database: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | In this paper, we analyze the throughput of multi-hop amplify and forward (AF) relay networks in delay-constrained scenario. Using quantized channel state information (CSI), the transmission rates and powers are discretely adapted with individual average power constraint on each node. A sub-gradient projection-based algorithm is utilized, by which there is no need for probability density functions (PDFs) to solve the optimization problem. Our numerical evaluations show that the sub-gradient projection-based algorithm results in a comparable performance with an analytical approach using PDFs. As shown, a considerably better performance obtained by the designed scheme compared to previous schemes with constant power transmission. More than 70% throughput improvement is achieved by our scheme compared to constant power transmission with just two more feedback bits and a short training time required at the beginning of the transmission. |
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| ISSN: | 16871499 16871472 |
| DOI: | 10.1186/s13638-019-1423-3 |