Adaptive Resource Allocation for Interference Management in Small Cell Networks
We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Elsherif, Ahmed R [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
adaptive graph coloring approach interference management algorithm mobility management (mobile radio) |
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| Systematik: |
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| Übergeordnetes Werk: |
Enthalten in: IEEE transactions on communications - New York, NY : IEEE, 1972, 63(2015), 6, Seite 2107-2125 |
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| Übergeordnetes Werk: |
volume:63 ; year:2015 ; number:6 ; pages:2107-2125 |
| Links: |
|---|
| DOI / URN: |
10.1109/TCOMM.2015.2420676 |
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| Katalog-ID: |
OLC1965367305 |
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| 520 | |a We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. | ||
| 650 | 4 | |a enterprise deployment | |
| 650 | 4 | |a adaptive graph coloring approach | |
| 650 | 4 | |a exponential complexity | |
| 650 | 4 | |a Resource management | |
| 650 | 4 | |a global-optimum solution | |
| 650 | 4 | |a small cell network | |
| 650 | 4 | |a Interference | |
| 650 | 4 | |a radiofrequency interference | |
| 650 | 4 | |a cellular radio | |
| 650 | 4 | |a fractional frequency reuse | |
| 650 | 4 | |a resource allocation | |
| 650 | 4 | |a interference management algorithm | |
| 650 | 4 | |a wireless network | |
| 650 | 4 | |a mobility management (mobile radio) | |
| 650 | 4 | |a FFR | |
| 650 | 4 | |a Computer architecture | |
| 650 | 4 | |a adaptive resource allocation | |
| 650 | 4 | |a graph colouring | |
| 650 | 4 | |a Color | |
| 650 | 4 | |a channel feedback | |
| 650 | 4 | |a linear complexity | |
| 650 | 4 | |a Radio spectrum management | |
| 650 | 4 | |a suboptimal channel assignment | |
| 650 | 4 | |a Macrocell networks | |
| 650 | 4 | |a multiple neighboring femtocellular network | |
| 650 | 4 | |a communication complexity | |
| 650 | 4 | |a Femtocells | |
| 650 | 4 | |a computational complexity | |
| 650 | 4 | |a Wireless networks | |
| 650 | 4 | |a Algorithms | |
| 650 | 4 | |a Graph coloring | |
| 650 | 4 | |a Electromagnetic interference | |
| 650 | 4 | |a Control | |
| 700 | 0 | |a Wei-Peng Chen |4 oth | |
| 700 | 1 | |a Ito, Akira |4 oth | |
| 700 | 0 | |a Zhi Ding |4 oth | |
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10.1109/TCOMM.2015.2420676 doi PQ20160617 (DE-627)OLC1965367305 (DE-599)GBVOLC1965367305 (PRQ)c2355-1a714555eabc27d8a637e3dee035d2aa065660deaea80e00b8f6200643e204cb0 (KEY)0043613520150000063000602107adaptiveresourceallocationforinterferencemanagemen DE-627 ger DE-627 rakwb eng 620 DNB SA 5540 AVZ rvk Elsherif, Ahmed R verfasserin aut Adaptive Resource Allocation for Interference Management in Small Cell Networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. enterprise deployment adaptive graph coloring approach exponential complexity Resource management global-optimum solution small cell network Interference radiofrequency interference cellular radio fractional frequency reuse resource allocation interference management algorithm wireless network mobility management (mobile radio) FFR Computer architecture adaptive resource allocation graph colouring Color channel feedback linear complexity Radio spectrum management suboptimal channel assignment Macrocell networks multiple neighboring femtocellular network communication complexity Femtocells computational complexity Wireless networks Algorithms Graph coloring Electromagnetic interference Control Wei-Peng Chen oth Ito, Akira oth Zhi Ding oth Enthalten in IEEE transactions on communications New York, NY : IEEE, 1972 63(2015), 6, Seite 2107-2125 (DE-627)129300624 (DE-600)121987-X (DE-576)014493063 0090-6778 nnns volume:63 year:2015 number:6 pages:2107-2125 http://dx.doi.org/10.1109/TCOMM.2015.2420676 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080992 http://search.proquest.com/docview/1689299511 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MKW GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_2004 SA 5540 AR 63 2015 6 2107-2125 |
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10.1109/TCOMM.2015.2420676 doi PQ20160617 (DE-627)OLC1965367305 (DE-599)GBVOLC1965367305 (PRQ)c2355-1a714555eabc27d8a637e3dee035d2aa065660deaea80e00b8f6200643e204cb0 (KEY)0043613520150000063000602107adaptiveresourceallocationforinterferencemanagemen DE-627 ger DE-627 rakwb eng 620 DNB SA 5540 AVZ rvk Elsherif, Ahmed R verfasserin aut Adaptive Resource Allocation for Interference Management in Small Cell Networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. enterprise deployment adaptive graph coloring approach exponential complexity Resource management global-optimum solution small cell network Interference radiofrequency interference cellular radio fractional frequency reuse resource allocation interference management algorithm wireless network mobility management (mobile radio) FFR Computer architecture adaptive resource allocation graph colouring Color channel feedback linear complexity Radio spectrum management suboptimal channel assignment Macrocell networks multiple neighboring femtocellular network communication complexity Femtocells computational complexity Wireless networks Algorithms Graph coloring Electromagnetic interference Control Wei-Peng Chen oth Ito, Akira oth Zhi Ding oth Enthalten in IEEE transactions on communications New York, NY : IEEE, 1972 63(2015), 6, Seite 2107-2125 (DE-627)129300624 (DE-600)121987-X (DE-576)014493063 0090-6778 nnns volume:63 year:2015 number:6 pages:2107-2125 http://dx.doi.org/10.1109/TCOMM.2015.2420676 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080992 http://search.proquest.com/docview/1689299511 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MKW GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_2004 SA 5540 AR 63 2015 6 2107-2125 |
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10.1109/TCOMM.2015.2420676 doi PQ20160617 (DE-627)OLC1965367305 (DE-599)GBVOLC1965367305 (PRQ)c2355-1a714555eabc27d8a637e3dee035d2aa065660deaea80e00b8f6200643e204cb0 (KEY)0043613520150000063000602107adaptiveresourceallocationforinterferencemanagemen DE-627 ger DE-627 rakwb eng 620 DNB SA 5540 AVZ rvk Elsherif, Ahmed R verfasserin aut Adaptive Resource Allocation for Interference Management in Small Cell Networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. enterprise deployment adaptive graph coloring approach exponential complexity Resource management global-optimum solution small cell network Interference radiofrequency interference cellular radio fractional frequency reuse resource allocation interference management algorithm wireless network mobility management (mobile radio) FFR Computer architecture adaptive resource allocation graph colouring Color channel feedback linear complexity Radio spectrum management suboptimal channel assignment Macrocell networks multiple neighboring femtocellular network communication complexity Femtocells computational complexity Wireless networks Algorithms Graph coloring Electromagnetic interference Control Wei-Peng Chen oth Ito, Akira oth Zhi Ding oth Enthalten in IEEE transactions on communications New York, NY : IEEE, 1972 63(2015), 6, Seite 2107-2125 (DE-627)129300624 (DE-600)121987-X (DE-576)014493063 0090-6778 nnns volume:63 year:2015 number:6 pages:2107-2125 http://dx.doi.org/10.1109/TCOMM.2015.2420676 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080992 http://search.proquest.com/docview/1689299511 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MKW GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_2004 SA 5540 AR 63 2015 6 2107-2125 |
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10.1109/TCOMM.2015.2420676 doi PQ20160617 (DE-627)OLC1965367305 (DE-599)GBVOLC1965367305 (PRQ)c2355-1a714555eabc27d8a637e3dee035d2aa065660deaea80e00b8f6200643e204cb0 (KEY)0043613520150000063000602107adaptiveresourceallocationforinterferencemanagemen DE-627 ger DE-627 rakwb eng 620 DNB SA 5540 AVZ rvk Elsherif, Ahmed R verfasserin aut Adaptive Resource Allocation for Interference Management in Small Cell Networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. enterprise deployment adaptive graph coloring approach exponential complexity Resource management global-optimum solution small cell network Interference radiofrequency interference cellular radio fractional frequency reuse resource allocation interference management algorithm wireless network mobility management (mobile radio) FFR Computer architecture adaptive resource allocation graph colouring Color channel feedback linear complexity Radio spectrum management suboptimal channel assignment Macrocell networks multiple neighboring femtocellular network communication complexity Femtocells computational complexity Wireless networks Algorithms Graph coloring Electromagnetic interference Control Wei-Peng Chen oth Ito, Akira oth Zhi Ding oth Enthalten in IEEE transactions on communications New York, NY : IEEE, 1972 63(2015), 6, Seite 2107-2125 (DE-627)129300624 (DE-600)121987-X (DE-576)014493063 0090-6778 nnns volume:63 year:2015 number:6 pages:2107-2125 http://dx.doi.org/10.1109/TCOMM.2015.2420676 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080992 http://search.proquest.com/docview/1689299511 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MKW GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_2004 SA 5540 AR 63 2015 6 2107-2125 |
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10.1109/TCOMM.2015.2420676 doi PQ20160617 (DE-627)OLC1965367305 (DE-599)GBVOLC1965367305 (PRQ)c2355-1a714555eabc27d8a637e3dee035d2aa065660deaea80e00b8f6200643e204cb0 (KEY)0043613520150000063000602107adaptiveresourceallocationforinterferencemanagemen DE-627 ger DE-627 rakwb eng 620 DNB SA 5540 AVZ rvk Elsherif, Ahmed R verfasserin aut Adaptive Resource Allocation for Interference Management in Small Cell Networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. enterprise deployment adaptive graph coloring approach exponential complexity Resource management global-optimum solution small cell network Interference radiofrequency interference cellular radio fractional frequency reuse resource allocation interference management algorithm wireless network mobility management (mobile radio) FFR Computer architecture adaptive resource allocation graph colouring Color channel feedback linear complexity Radio spectrum management suboptimal channel assignment Macrocell networks multiple neighboring femtocellular network communication complexity Femtocells computational complexity Wireless networks Algorithms Graph coloring Electromagnetic interference Control Wei-Peng Chen oth Ito, Akira oth Zhi Ding oth Enthalten in IEEE transactions on communications New York, NY : IEEE, 1972 63(2015), 6, Seite 2107-2125 (DE-627)129300624 (DE-600)121987-X (DE-576)014493063 0090-6778 nnns volume:63 year:2015 number:6 pages:2107-2125 http://dx.doi.org/10.1109/TCOMM.2015.2420676 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7080992 http://search.proquest.com/docview/1689299511 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MKW GBV_ILN_40 GBV_ILN_65 GBV_ILN_70 GBV_ILN_2004 SA 5540 AR 63 2015 6 2107-2125 |
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Adaptive Resource Allocation for Interference Management in Small Cell Networks |
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We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. |
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We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. |
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We consider a femto cellular network consisting of multiple neighboring femtocells, e.g., in an enterprise deployment such as shopping malls, stadiums, or corporate premises. We present a practical but suboptimal channel assignment and interference management algorithm for fractional frequency reuse (FFR) wireless networks. More specifically, we propose an adaptive graph coloring approach for resource allocation with the goal of interference management among femtocells as well as achieving fairness among users. While the global-optimum solution has exponential complexity, our proposed scheme has a linear complexity in the number of femtocells. Although suboptimal, we have evaluated our algorithm in small scenarios, where direct evaluation is possible, and found that the achieved minimum user rate using the proposed algorithm is 85% of the optimal minimum rate. Additionally, we have analyzed several practical design considerations of our proposal such as channel feedback, latency, and computational complexity. We demonstrate the performance of our proposed solution against various alternatives and show that it provides better performance under various environment parameters. For example, in a dense femtocell deployment, the performance was improved by 47% over a full frequency reuse scheme. |
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