Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148952
Yifan Pan, Lin Gao, Jingjing Luo, Tong Wang, Jiaqi Luo
Mobile Edge Computing (MEC) is a promising solution to tackle the upcoming computing tsunami in 5G era, by effectively utilizing the idle resource at the mobile edge. In this work, we study such an MEC scenario, where mobile devices at edge share their heterogeneous resources with each other, hence forming a multi-dimensional resource crowdsourcing (sharing) framework. We are interested in the problem of how to optimally offload tasks to mobile devices under this framework, aiming at minimizing the total energy cost and maximizing the overall task completion. To study the problem, we first propose a general task model, where each task is divided into multiple sequential subtasks according to their functionalities as well as resource requirements. Then, based on the task model, we propose a Joint Energy Consumption and Task Failure Probability Minimization Problem, which decides when and where each subtask will be offloaded to. The problem is challenging to solve, mainly due to the inherent constraints between the scheduling of different subtasks. Therefore, we propose several linearization methods to relax the constraints, and convert the original problem into an integer linear programming (ILP), which can be solved by many classic methods effectively. We further perform simulations, which show that our proposed solution outperforms the existing solutions (with indivisible tasks or without resource sharing) in terms of both the total cost and the task failure probability. Precisely, our proposed solution can reduce the total cost by $25%sim 85%$ and the task failure probability by $10%sim 35%$.
{"title":"A Multi-Dimensional Resource Crowdsourcing Framework for Mobile Edge Computing","authors":"Yifan Pan, Lin Gao, Jingjing Luo, Tong Wang, Jiaqi Luo","doi":"10.1109/ICC40277.2020.9148952","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148952","url":null,"abstract":"Mobile Edge Computing (MEC) is a promising solution to tackle the upcoming computing tsunami in 5G era, by effectively utilizing the idle resource at the mobile edge. In this work, we study such an MEC scenario, where mobile devices at edge share their heterogeneous resources with each other, hence forming a multi-dimensional resource crowdsourcing (sharing) framework. We are interested in the problem of how to optimally offload tasks to mobile devices under this framework, aiming at minimizing the total energy cost and maximizing the overall task completion. To study the problem, we first propose a general task model, where each task is divided into multiple sequential subtasks according to their functionalities as well as resource requirements. Then, based on the task model, we propose a Joint Energy Consumption and Task Failure Probability Minimization Problem, which decides when and where each subtask will be offloaded to. The problem is challenging to solve, mainly due to the inherent constraints between the scheduling of different subtasks. Therefore, we propose several linearization methods to relax the constraints, and convert the original problem into an integer linear programming (ILP), which can be solved by many classic methods effectively. We further perform simulations, which show that our proposed solution outperforms the existing solutions (with indivisible tasks or without resource sharing) in terms of both the total cost and the task failure probability. Precisely, our proposed solution can reduce the total cost by $25%sim 85%$ and the task failure probability by $10%sim 35%$.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131990369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149355
Jiayuan Xiong, Li You, Yufei Huang, D. W. K. Ng, Wen Wang, Xiqi Gao
This paper considers the application of reconfigurable intelligent surfaces (RISs) to assist multiuser multipleinput multiple-output multiple access channel (MIMO-MAC) systems. In contrast to most existing works on RIS-assisted systems assuming the availability of full channel state information (CSI), only partial CSI is required in our investigation, including the instantaneous CSI of the channel from a RIS to a base station and the statistical CSI of the channels from user terminals (UTs) to the RIS. We investigate the joint design of both the transmit covariance matrices of the UTs and the RIS phase shift matrix under the system global energy efficiency (GEE) maximization criterion. To maximize the GEE, we first obtain closed-form solutions for the eigenvectors of the optimal transmit covariance matrices of the UTs. Then, we derive an asymptotic expression of the objective function with the aid of random matrix theory to reduce the computational cost. We further propose a lowcomplexity algorithm to tackle the GEE maximization problem with guaranteed convergence, capitalizing on the approaches of alternating optimization, fractional programming, and sequential optimization. Numerical results substantiate the effectiveness of the proposed approach as well as the GEE performance gains provided by RIS-assisted MIMO-MAC systems.
{"title":"Reconfigurable Intelligent Surfaces Assisted MIMO-MAC with Partial CSI","authors":"Jiayuan Xiong, Li You, Yufei Huang, D. W. K. Ng, Wen Wang, Xiqi Gao","doi":"10.1109/ICC40277.2020.9149355","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149355","url":null,"abstract":"This paper considers the application of reconfigurable intelligent surfaces (RISs) to assist multiuser multipleinput multiple-output multiple access channel (MIMO-MAC) systems. In contrast to most existing works on RIS-assisted systems assuming the availability of full channel state information (CSI), only partial CSI is required in our investigation, including the instantaneous CSI of the channel from a RIS to a base station and the statistical CSI of the channels from user terminals (UTs) to the RIS. We investigate the joint design of both the transmit covariance matrices of the UTs and the RIS phase shift matrix under the system global energy efficiency (GEE) maximization criterion. To maximize the GEE, we first obtain closed-form solutions for the eigenvectors of the optimal transmit covariance matrices of the UTs. Then, we derive an asymptotic expression of the objective function with the aid of random matrix theory to reduce the computational cost. We further propose a lowcomplexity algorithm to tackle the GEE maximization problem with guaranteed convergence, capitalizing on the approaches of alternating optimization, fractional programming, and sequential optimization. Numerical results substantiate the effectiveness of the proposed approach as well as the GEE performance gains provided by RIS-assisted MIMO-MAC systems.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132044399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149092
Jonathan Prados-Garzon, T. Taleb, Miloud Bagaa
Time-Sensitive Networking (TSN) and Deterministic Networking (DetNet) standards come to satisfy the needs of many industries for deterministic network services. That is the ability to establish a multi-hop path over an IP network for a given flow with deterministic Quality of Service (QoS) guarantees in terms of latency, jitter, packet loss, and reliability. In this work, we propose a reinforcement learning-based solution, which is dubbed LEARNET, for the flow scheduling in deterministic asynchronous networks. The solution leverages predictive data analytics and reinforcement learning to maximize the network operator’s revenue. We evaluate the performance of LEARNET through simulation in a fifth-generation (5G) asynchronous deterministic backhaul network where incoming flows have characteristics similar to the four critical 5GQoS Identifiers (5QIs) defined in Third Generation Partnership Project (3GPP) TS 23.501 V16.1.0. Also, we compared the performance of LEARNET with a baseline solution that respects the 5QIs priorities for allocating the incoming flows. The obtained results show that, for the scenario considered, LEARNET achieves a gain in the revenue of up to 45% compared to the baseline solution.
{"title":"LEARNET: Reinforcement Learning Based Flow Scheduling for Asynchronous Deterministic Networks","authors":"Jonathan Prados-Garzon, T. Taleb, Miloud Bagaa","doi":"10.1109/ICC40277.2020.9149092","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149092","url":null,"abstract":"Time-Sensitive Networking (TSN) and Deterministic Networking (DetNet) standards come to satisfy the needs of many industries for deterministic network services. That is the ability to establish a multi-hop path over an IP network for a given flow with deterministic Quality of Service (QoS) guarantees in terms of latency, jitter, packet loss, and reliability. In this work, we propose a reinforcement learning-based solution, which is dubbed LEARNET, for the flow scheduling in deterministic asynchronous networks. The solution leverages predictive data analytics and reinforcement learning to maximize the network operator’s revenue. We evaluate the performance of LEARNET through simulation in a fifth-generation (5G) asynchronous deterministic backhaul network where incoming flows have characteristics similar to the four critical 5GQoS Identifiers (5QIs) defined in Third Generation Partnership Project (3GPP) TS 23.501 V16.1.0. Also, we compared the performance of LEARNET with a baseline solution that respects the 5QIs priorities for allocating the incoming flows. The obtained results show that, for the scenario considered, LEARNET achieves a gain in the revenue of up to 45% compared to the baseline solution.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130252684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149014
Xu Chen, Li You, Xiaohang Song, Fan Jiang, Wen Wang, Xiqi Gao, G. Fettweis
To alleviate the blockage effects involved in millimeter-wave propagation, we investigate network massive multiple-input multiple-output (MIMO) transmission where only statistical channel state information is available at base stations (BSs). We first establish a network massive MIMO transmission model over millimeter-wave bands using per-beam synchronization. We Figure out that the beam domain is in favor of performing transmission in this scenario. We also demonstrate that BSs can work individually when sending signals to user terminals. Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation. By exploiting the sequential optimization method and random matrix theory, an iterative algorithm with guaranteed convergence is further proposed to solve the problem. Numerical results reveal that the proposed network massive MIMO transmission approach can effectively alleviate the blockage effects and provide substantial performance gains over the existing transmission approaches.
{"title":"Network Massive MIMO Transmission Over Millimeter-Wave Bands","authors":"Xu Chen, Li You, Xiaohang Song, Fan Jiang, Wen Wang, Xiqi Gao, G. Fettweis","doi":"10.1109/ICC40277.2020.9149014","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149014","url":null,"abstract":"To alleviate the blockage effects involved in millimeter-wave propagation, we investigate network massive multiple-input multiple-output (MIMO) transmission where only statistical channel state information is available at base stations (BSs). We first establish a network massive MIMO transmission model over millimeter-wave bands using per-beam synchronization. We Figure out that the beam domain is in favor of performing transmission in this scenario. We also demonstrate that BSs can work individually when sending signals to user terminals. Based on these insights, the network massive MIMO precoding design is reduced to a network sum-rate maximization problem with respect to beam domain power allocation. By exploiting the sequential optimization method and random matrix theory, an iterative algorithm with guaranteed convergence is further proposed to solve the problem. Numerical results reveal that the proposed network massive MIMO transmission approach can effectively alleviate the blockage effects and provide substantial performance gains over the existing transmission approaches.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134229556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149237
G. Ricardo, G. Neglia, T. Spyropoulos
In 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small(er) cells are combined to offer better Quality of Service (QoS) to wireless users. On top of such networks, edge caching and Coordinated Multi-Point (CoMP) transmissions are used to further improve performance. The problem of optimally utilizing the cache space in dense and heterogeneous cell networks has been extensively studied under the name of “FemtoCaching.” However, related literature usually assumes relatively simple physical layer (PHY) setups and known or stationary content popularity. In this paper, we address these issues by proposing a class of fully distributed and dynamic caching algorithms that take advantage of CoMP capabilities towards minimizing PHY-aware metrics, such as end-to-end (E2E) delay. Our policies outperform existing dynamic solutions that are PHY-unaware, under both synthetic and real (non-stationary) request processes, and converge to efficient centralized solutions, in static setups.
{"title":"Caching Policies for Delay Minimization in Small Cell Networks with Joint Transmissions","authors":"G. Ricardo, G. Neglia, T. Spyropoulos","doi":"10.1109/ICC40277.2020.9149237","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149237","url":null,"abstract":"In 5G and beyond network architectures, operators and content providers base their content distribution strategies on Heterogeneous Networks, where macro and small(er) cells are combined to offer better Quality of Service (QoS) to wireless users. On top of such networks, edge caching and Coordinated Multi-Point (CoMP) transmissions are used to further improve performance. The problem of optimally utilizing the cache space in dense and heterogeneous cell networks has been extensively studied under the name of “FemtoCaching.” However, related literature usually assumes relatively simple physical layer (PHY) setups and known or stationary content popularity. In this paper, we address these issues by proposing a class of fully distributed and dynamic caching algorithms that take advantage of CoMP capabilities towards minimizing PHY-aware metrics, such as end-to-end (E2E) delay. Our policies outperform existing dynamic solutions that are PHY-unaware, under both synthetic and real (non-stationary) request processes, and converge to efficient centralized solutions, in static setups.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131842600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149434
B. Qiu, Ling Wang, Jian Xie, Zhaolin Zhang, Yuexian Wang
In this paper, an efficient multi-beam transmission scheme that uses symbol-level precoding based on frequency diverse array (FDA) is proposed to enhance the physical layer security (PLS). Unlike the usual maximization of secrecy rate, we assume that the position information of passive eavesdropper (Eve) is not available at transmitter, which is a more realistic assumption. We use a minimum transmission message power criterion to design the precoder, subject to constraint on received signals at symbol level for per legitimate user (LU). This guarantees the valid reception of LUs to obtain the corresponding symbols under transmission messages power minimization. Then, after accurate calculation of the transmission message power, the remaining power can be allocated to artificial noise (AN), which deteriorates the quality of received signals at other regions. Numerical simulations show the validity and effectiveness of the proposed scheme.
{"title":"Multi-beam Symbol-Level Precoding in Directional Modulation Based on Frequency Diverse Array","authors":"B. Qiu, Ling Wang, Jian Xie, Zhaolin Zhang, Yuexian Wang","doi":"10.1109/ICC40277.2020.9149434","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149434","url":null,"abstract":"In this paper, an efficient multi-beam transmission scheme that uses symbol-level precoding based on frequency diverse array (FDA) is proposed to enhance the physical layer security (PLS). Unlike the usual maximization of secrecy rate, we assume that the position information of passive eavesdropper (Eve) is not available at transmitter, which is a more realistic assumption. We use a minimum transmission message power criterion to design the precoder, subject to constraint on received signals at symbol level for per legitimate user (LU). This guarantees the valid reception of LUs to obtain the corresponding symbols under transmission messages power minimization. Then, after accurate calculation of the transmission message power, the remaining power can be allocated to artificial noise (AN), which deteriorates the quality of received signals at other regions. Numerical simulations show the validity and effectiveness of the proposed scheme.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130735983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/icc40277.2020.9149174
A. Tolio, Davide Boem, Thomas Marchioro, L. Badia
LoRa is a low-power wide-area network solution that is recently gaining popularity in the context of the Internet of Things due to its ability to handle massive number of devices. One of the main challenges faced by LoRa implementations is the allocation of Spreading Factors to the devices. While the assignment of these parameters is virtually simple to execute, scalability and complexity issues hint at its implementation through a game theoretic approach. This would offer the advantage of being readily implementable in vast networks of devices with limited hardware capabilities. Hence, we formulate the SF allocation problem as a Bayesian game, of which we compute the Bayesian Nash equilibria. We also implement the procedure in the ns- 3 network simulator and evaluate the resulting performance, showing that our approach is scalable and robust, and also offers room for improvement with respect to existing approaches.
{"title":"Spreading Factor Allocation in LoRa Networks through a Game Theoretic Approach","authors":"A. Tolio, Davide Boem, Thomas Marchioro, L. Badia","doi":"10.1109/icc40277.2020.9149174","DOIUrl":"https://doi.org/10.1109/icc40277.2020.9149174","url":null,"abstract":"LoRa is a low-power wide-area network solution that is recently gaining popularity in the context of the Internet of Things due to its ability to handle massive number of devices. One of the main challenges faced by LoRa implementations is the allocation of Spreading Factors to the devices. While the assignment of these parameters is virtually simple to execute, scalability and complexity issues hint at its implementation through a game theoretic approach. This would offer the advantage of being readily implementable in vast networks of devices with limited hardware capabilities. Hence, we formulate the SF allocation problem as a Bayesian game, of which we compute the Bayesian Nash equilibria. We also implement the procedure in the ns- 3 network simulator and evaluate the resulting performance, showing that our approach is scalable and robust, and also offers room for improvement with respect to existing approaches.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133067809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9149308
Sareh Majidi Ivari, Màrius Caus, M. Vázquez, M. Soleymani, Y. Shayan, A. Pérez-Neira
This paper investigates the application of multicast non-orthogonal multiple access (MC-NOMA) schemes to the forward link of a satellite communication system. In multicast transmission each frame contains information of multiple users. To benefit from the theory developed in NOMA, the proposed scheme creates two groups of users within each beam. The analysis conducted in this work reveals that the user grouping has an impact on the performance. In the light of this observation, power allocation and user clustering techniques have been derived to either maximize the sum-rate or achieve max-min fairness. The numerical simulation results show that MC-NOMA outperforms multicast orthogonal multiple access (MC-OMA) schemes, where different groups are served in orthogonal resources. Moreover, the gain of MC-NOMA over the MC-OMA becomes more prominent as number of users per group and the transmit power increases. The results show the minimum-rate and the sum-rate of MC-NOMA can be increased by a factor 2 and 1.45 with respect to MC-OMA, respectively.
{"title":"Power Allocation and User Clustering in Multicast NOMA based Satellite Communication Systems","authors":"Sareh Majidi Ivari, Màrius Caus, M. Vázquez, M. Soleymani, Y. Shayan, A. Pérez-Neira","doi":"10.1109/ICC40277.2020.9149308","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9149308","url":null,"abstract":"This paper investigates the application of multicast non-orthogonal multiple access (MC-NOMA) schemes to the forward link of a satellite communication system. In multicast transmission each frame contains information of multiple users. To benefit from the theory developed in NOMA, the proposed scheme creates two groups of users within each beam. The analysis conducted in this work reveals that the user grouping has an impact on the performance. In the light of this observation, power allocation and user clustering techniques have been derived to either maximize the sum-rate or achieve max-min fairness. The numerical simulation results show that MC-NOMA outperforms multicast orthogonal multiple access (MC-OMA) schemes, where different groups are served in orthogonal resources. Moreover, the gain of MC-NOMA over the MC-OMA becomes more prominent as number of users per group and the transmit power increases. The results show the minimum-rate and the sum-rate of MC-NOMA can be increased by a factor 2 and 1.45 with respect to MC-OMA, respectively.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133339006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148919
F. Parente, F. Calmon, J. Filho
Wireless communications are affected by several aspects of the multipath fading channel, including clustering, nonlinearity, correlation, scattered waves, and specular components. These aspects have been incorporated into many existing probabilistic fading models. The more aspects are covered, the more complicated is the resulting model. In many cases, the model or the associated system performance or both cannot be obtained in a closed form. As a result, little insight is gained into how each aspect of fading ultimately impacts key metrics such as symbol error rate and outage probability. In this work, we provide a novel asymptotic analysis at high signal-to-noise ratio that yields simple, general, and unified closed-form expressions for the diversity and coding gains of the symbol error rate and outage probability. We cover generalized fading scenarios and all the referred fading aspects. Our results give a handy, yet thorough, characterization of the system performance as impacted by multiple physical aspects of the multipath fading phenomenon. We provide further insights to reveal that all the addressed fading aspects affect the coding gain, whereas only the clustering and nonlinearity affect the diversity gain.
{"title":"High-SNR Performance in Gaussian-Class Fading","authors":"F. Parente, F. Calmon, J. Filho","doi":"10.1109/ICC40277.2020.9148919","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148919","url":null,"abstract":"Wireless communications are affected by several aspects of the multipath fading channel, including clustering, nonlinearity, correlation, scattered waves, and specular components. These aspects have been incorporated into many existing probabilistic fading models. The more aspects are covered, the more complicated is the resulting model. In many cases, the model or the associated system performance or both cannot be obtained in a closed form. As a result, little insight is gained into how each aspect of fading ultimately impacts key metrics such as symbol error rate and outage probability. In this work, we provide a novel asymptotic analysis at high signal-to-noise ratio that yields simple, general, and unified closed-form expressions for the diversity and coding gains of the symbol error rate and outage probability. We cover generalized fading scenarios and all the referred fading aspects. Our results give a handy, yet thorough, characterization of the system performance as impacted by multiple physical aspects of the multipath fading phenomenon. We provide further insights to reveal that all the addressed fading aspects affect the coding gain, whereas only the clustering and nonlinearity affect the diversity gain.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"491 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133340105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ICC40277.2020.9148779
Ciyuan Zhang, B. Peleato
Coded caching utilizes pre-fetching during off-peak hours and multi-casting for delivery in order to balance the traffic load in communication networks. Most of the existing research focuses on reducing the peak transmission rates with homogeneous file popularities, despite modern systems are often able to categorize users by their preferences and tend to care more about the average rather than peak rate. This paper considers a scenario with heterogeneous user profiles and analyzes the average transmission rates for three coded caching schemes under the assumption that each user can only request a subset of the total available files. In addition, it evaluates the average rate of the three schemes when the number of files is much larger than the number of users and the amount of cache memory. Furthermore, it proposes methods of cache allocations which minimize the average rate when the users have relatively small storage. Our results demonstrate connections between cache distributions which result in minimal average rate and peak rate.
{"title":"On the Average Rate for Coded Caching with Heterogeneous User Profiles","authors":"Ciyuan Zhang, B. Peleato","doi":"10.1109/ICC40277.2020.9148779","DOIUrl":"https://doi.org/10.1109/ICC40277.2020.9148779","url":null,"abstract":"Coded caching utilizes pre-fetching during off-peak hours and multi-casting for delivery in order to balance the traffic load in communication networks. Most of the existing research focuses on reducing the peak transmission rates with homogeneous file popularities, despite modern systems are often able to categorize users by their preferences and tend to care more about the average rather than peak rate. This paper considers a scenario with heterogeneous user profiles and analyzes the average transmission rates for three coded caching schemes under the assumption that each user can only request a subset of the total available files. In addition, it evaluates the average rate of the three schemes when the number of files is much larger than the number of users and the amount of cache memory. Furthermore, it proposes methods of cache allocations which minimize the average rate when the users have relatively small storage. Our results demonstrate connections between cache distributions which result in minimal average rate and peak rate.","PeriodicalId":106560,"journal":{"name":"ICC 2020 - 2020 IEEE International Conference on Communications (ICC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132294220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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