Power and Rate Adaptive Pushing Over Fading Channels
Proactive caching is capable of reducing access latency and improving network throughput, thereby attracting attention from both industry and academia. However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an...
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Veröffentlicht in: | IEEE transactions on wireless communications 2021-10, Vol.20 (10), p.6436-6450 |
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description | Proactive caching is capable of reducing access latency and improving network throughput, thereby attracting attention from both industry and academia. However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an energy-efficient content pushing policy by carefully adapting the transmit rate and power in pushing and on-demand delivery phases, while assuring delivery delay constraints. To this end, the average delay, delay-outage probability, and EE are analyzed for a general adaptive pushing policy based on the saddle point approximation. According to these results, we formulate EE maximization problems under average delay and delay-outage constraints, respectively, for two special types of adaptive pushing policies, namely, opportunistic pushing and water-filling-based pushing. Due to the high complexity of the grid search for solving the formulated problems, suboptimal algorithms are presented based on gradient descent and golden section search methods. Moreover, we mathematically derive the scaling property and numerically obtain request probability and delivery delay thresholds for content pushing. Simulations show that the presented pushing policies achieve higher EE than on-demand transmissions, especially when the content item is popular and the tolerable delivery delay is small. |
doi_str_mv | 10.1109/TWC.2021.3073977 |
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However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an energy-efficient content pushing policy by carefully adapting the transmit rate and power in pushing and on-demand delivery phases, while assuring delivery delay constraints. To this end, the average delay, delay-outage probability, and EE are analyzed for a general adaptive pushing policy based on the saddle point approximation. According to these results, we formulate EE maximization problems under average delay and delay-outage constraints, respectively, for two special types of adaptive pushing policies, namely, opportunistic pushing and water-filling-based pushing. Due to the high complexity of the grid search for solving the formulated problems, suboptimal algorithms are presented based on gradient descent and golden section search methods. 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However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an energy-efficient content pushing policy by carefully adapting the transmit rate and power in pushing and on-demand delivery phases, while assuring delivery delay constraints. To this end, the average delay, delay-outage probability, and EE are analyzed for a general adaptive pushing policy based on the saddle point approximation. According to these results, we formulate EE maximization problems under average delay and delay-outage constraints, respectively, for two special types of adaptive pushing policies, namely, opportunistic pushing and water-filling-based pushing. Due to the high complexity of the grid search for solving the formulated problems, suboptimal algorithms are presented based on gradient descent and golden section search methods. Moreover, we mathematically derive the scaling property and numerically obtain request probability and delivery delay thresholds for content pushing. Simulations show that the presented pushing policies achieve higher EE than on-demand transmissions, especially when the content item is popular and the tolerable delivery delay is small.</description><subject>Algorithms</subject><subject>Caching</subject><subject>Channels</subject><subject>Content pushing</subject><subject>Delay</subject><subject>delay constraints</subject><subject>Delays</subject><subject>Energy consumption</subject><subject>Energy efficiency</subject><subject>Fading</subject><subject>Policies</subject><subject>proactive caching</subject><subject>Probability</subject><subject>Pushing</subject><subject>Quality of experience</subject><subject>rate and power adaptation</subject><subject>request delay information</subject><subject>Resource management</subject><subject>Saddle points</subject><subject>scaling property</subject><subject>Search methods</subject><subject>Throughput</subject><subject>Wireless communication</subject><issn>1536-1276</issn><issn>1558-2248</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtLw0AUhQdRsFb3gpuA68Q7r8xkWYKtQqFFKi6HmeTGptSkzqQV_70JKa7ugXse8BFyTyGhFLKnzUeeMGA04aB4ptQFmVApdcyY0JeD5mlMmUqvyU0IOwCqUiknRKzbH_SRbcrozXYYzUp76OoTRutj2NbNZ7Q69e-5LQedb23T4D7ckqvK7gPene-UvM-fN_lLvFwtXvPZMi44511srXSsylRmVemUZg6cFppbyQQXWJWlRVk5qrHQBRYOqXSKKVmkXIJAp_iUPI69B99-HzF0ZtcefdNPGiY1UAAu0t4Fo6vwbQgeK3Pw9Zf1v4aCGdiYno0Z2Jgzmz7yMEZqRPy3Z4KmrC_8AxNQXqQ</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Xie, Zhanyuan</creator><creator>Lin, Zhiyuan</creator><creator>Chen, Wei</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an energy-efficient content pushing policy by carefully adapting the transmit rate and power in pushing and on-demand delivery phases, while assuring delivery delay constraints. To this end, the average delay, delay-outage probability, and EE are analyzed for a general adaptive pushing policy based on the saddle point approximation. According to these results, we formulate EE maximization problems under average delay and delay-outage constraints, respectively, for two special types of adaptive pushing policies, namely, opportunistic pushing and water-filling-based pushing. Due to the high complexity of the grid search for solving the formulated problems, suboptimal algorithms are presented based on gradient descent and golden section search methods. 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subjects | Algorithms Caching Channels Content pushing Delay delay constraints Delays Energy consumption Energy efficiency Fading Policies proactive caching Probability Pushing Quality of experience rate and power adaptation request delay information Resource management Saddle points scaling property Search methods Throughput Wireless communication |
title | Power and Rate Adaptive Pushing Over Fading Channels |
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