Pub Date : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120809
Zhe Chen, Emin Aksehirli
Optimizing capital expenditure (CapEx) has been an increasingly important objective in telco operators’ cell planning process. Traditionally, neighbor cell relation is operationally managed and independent from capacity planning. In this paper, we present SCUT, an algorithm that uses massive mobile usage records to detect clusters of possible capacity-sharing sectors, such that capacity planning can be optimized based on coverage. SCUT analyzes shared usage to build a graph-based model of an operator’s network and identifies its disjoint dense components as best-fit abstractions of clusters. Through analysis and benchmarking on real data, we demonstrate its scalability and potential to improve industry-standard site-based planning. SCUT has been deployed for a telco operator in Southeast Asia.
{"title":"Identifying Cell Sector Clusters Using Massive Mobile Usage Records","authors":"Zhe Chen, Emin Aksehirli","doi":"10.1109/WCNC45663.2020.9120809","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120809","url":null,"abstract":"Optimizing capital expenditure (CapEx) has been an increasingly important objective in telco operators’ cell planning process. Traditionally, neighbor cell relation is operationally managed and independent from capacity planning. In this paper, we present SCUT, an algorithm that uses massive mobile usage records to detect clusters of possible capacity-sharing sectors, such that capacity planning can be optimized based on coverage. SCUT analyzes shared usage to build a graph-based model of an operator’s network and identifies its disjoint dense components as best-fit abstractions of clusters. Through analysis and benchmarking on real data, we demonstrate its scalability and potential to improve industry-standard site-based planning. SCUT has been deployed for a telco operator in Southeast Asia.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129623993","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120504
D. Moura, M. Sousa, P. Vieira, A. Rodrigues, Tiago Rosa Maria Paula Queluz
With the increase in consumption of multimedia content through mobile devices (e.g., smartphones), it is crucial to find new ways of optimizing current and future wireless networks and to continuously give users a better Quality of Experience (QoE) when accessing that content. To achieve this goal, it is necessary to provide Mobile Network Operator (MNO) with real time QoE monitoring for multimedia services (e.g., video streaming, web browsing), enabling a fast network optimization and an effective resource management. This paper proposes a new QoE prediction model for video streaming services over 4G networks, using layer 1 (i.e., Physical Layer) key performance indicators (KPIs). The model estimates the service Mean Opinion Score (MOS) based on a Machine Learning (ML) algorithm, and using real MNO drive test (DT) data, where both application layer and layer 1 metrics are available. From the several considered ML algorithms, the Gradient Tree Boosting (GTB) showed the best performance, achieving a Pearson correlation of 78.9%, a Spearman correlation of 66.8% and a Mean Squared Error (MSE) of 0.114, on a test set with 901 examples. Finally, the proposed model was tested with new DT data together with the network’s configuration. With the use case results, QoE predictions were analyzed according to the context in which the session was established, the radio transmission environment and radio channel quality indicators.
{"title":"A No-Reference Video Streaming QoE Estimator based on Physical Layer 4G Radio Measurements","authors":"D. Moura, M. Sousa, P. Vieira, A. Rodrigues, Tiago Rosa Maria Paula Queluz","doi":"10.1109/WCNC45663.2020.9120504","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120504","url":null,"abstract":"With the increase in consumption of multimedia content through mobile devices (e.g., smartphones), it is crucial to find new ways of optimizing current and future wireless networks and to continuously give users a better Quality of Experience (QoE) when accessing that content. To achieve this goal, it is necessary to provide Mobile Network Operator (MNO) with real time QoE monitoring for multimedia services (e.g., video streaming, web browsing), enabling a fast network optimization and an effective resource management. This paper proposes a new QoE prediction model for video streaming services over 4G networks, using layer 1 (i.e., Physical Layer) key performance indicators (KPIs). The model estimates the service Mean Opinion Score (MOS) based on a Machine Learning (ML) algorithm, and using real MNO drive test (DT) data, where both application layer and layer 1 metrics are available. From the several considered ML algorithms, the Gradient Tree Boosting (GTB) showed the best performance, achieving a Pearson correlation of 78.9%, a Spearman correlation of 66.8% and a Mean Squared Error (MSE) of 0.114, on a test set with 901 examples. Finally, the proposed model was tested with new DT data together with the network’s configuration. With the use case results, QoE predictions were analyzed according to the context in which the session was established, the radio transmission environment and radio channel quality indicators.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128204576","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120839
Bandarage Rajith D. K. Madduma, G. Messier, A. Fapojuwo
In most industrial applications, failed nodes will be repaired, but these repairs take time. For critical system applications, network operators need to understand how their networks function immediately after a failure but before a repair is possible. In this paper, we introduce an extension to the frame-level optimized routing/ scheduling algorithm to improve reliability and energy efficiency and compare it with the other industrial routing algorithms considering the oil refinery wireless sensor networks. We present a structured performance evaluation approach for studying the impact of the routing/scheduling algorithm on the post-failure/pre-repair regime. Simulation results show that the proposed algorithm exerts a positive impact on network performance: highly-reliable, low-latency, energyefficient, and fitting with most industrial applications.
{"title":"Impact of Packet Routing Scheme on Post-Failure Industrial Wireless Sensor Networks","authors":"Bandarage Rajith D. K. Madduma, G. Messier, A. Fapojuwo","doi":"10.1109/WCNC45663.2020.9120839","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120839","url":null,"abstract":"In most industrial applications, failed nodes will be repaired, but these repairs take time. For critical system applications, network operators need to understand how their networks function immediately after a failure but before a repair is possible. In this paper, we introduce an extension to the frame-level optimized routing/ scheduling algorithm to improve reliability and energy efficiency and compare it with the other industrial routing algorithms considering the oil refinery wireless sensor networks. We present a structured performance evaluation approach for studying the impact of the routing/scheduling algorithm on the post-failure/pre-repair regime. Simulation results show that the proposed algorithm exerts a positive impact on network performance: highly-reliable, low-latency, energyefficient, and fitting with most industrial applications.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"48 21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128499358","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120482
A. Bhowal, R. S. Kshetrimayum
Underwater optical wireless communication (UOWC) is an alternative to the existing acoustic and radio frequency (RF) underwater communication. In this paper, advanced schemes of UOWC like transmit laser selection (TLS) and TLS combined with optical spatial modulation (TLS-OSM) are proposed for weak oceanic turbulence based UOWC cooperative communication, which can enhance the performance of conventional UOWC communication. The performance is analyzed in terms of average symbol error probability (ASEP) and corroborated by Monte Carlo simulations. It is observed that TLS can achieve a signal to noise ratio (SNR) gain of at least 2 dB over the existing methods while TLS-OSM achieves a SNR gain of at least 3 dB over TLS scheme at any ASEP value of more than $10^{-2}$, thereby validating the efficiency of our schemes.
{"title":"Transmit laser selection for dual hop decode and forward UOWC cooperative communication","authors":"A. Bhowal, R. S. Kshetrimayum","doi":"10.1109/WCNC45663.2020.9120482","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120482","url":null,"abstract":"Underwater optical wireless communication (UOWC) is an alternative to the existing acoustic and radio frequency (RF) underwater communication. In this paper, advanced schemes of UOWC like transmit laser selection (TLS) and TLS combined with optical spatial modulation (TLS-OSM) are proposed for weak oceanic turbulence based UOWC cooperative communication, which can enhance the performance of conventional UOWC communication. The performance is analyzed in terms of average symbol error probability (ASEP) and corroborated by Monte Carlo simulations. It is observed that TLS can achieve a signal to noise ratio (SNR) gain of at least 2 dB over the existing methods while TLS-OSM achieves a SNR gain of at least 3 dB over TLS scheme at any ASEP value of more than $10^{-2}$, thereby validating the efficiency of our schemes.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128740465","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120765
Xinrui Tan, Hongjia Li, Liming Wang, Zhen Xu
Bring-Your-Own-Device (BYOD) has been widely viewed as a definite trend among enterprises in which employees bring and use their personal smartphones for work. Despite the perceived opportunities of increasing productivity and reducing costs, BYOD raises severe security and privacy concerns: the corporate networks and data are directly exposed to malware apps running on the personal smartphones. This highlights the necessity for performing real-time mobile malware detection in BYOD environments. Deep learning seems to be a natural choice to handle such detection, due to its state-of-the-art detection effectiveness. However, deep learning inference is usually too computationally complex for resource-constrained smartphones, and the communication overhead of cloud-based inference may be unacceptable. As a result, it is hard to seek the tradeoff between the real-time demand and optimality of detection accuracy. In this paper, we tackle this issue by proposing an endedge coordinated inference approach that can support highlyaccurate and average latency guaranteed malware detection. Our proposed approach integrates the early-exit and model partitioning methods to allow fast, correct and smartphonelocalized inference to occur frequently. Extensive evaluations are carried out, demonstrating that our proposed approach offers a good compromise between detection accuracy and efficiency.
{"title":"End-Edge Coordinated Inference for Real-Time BYOD Malware Detection using Deep Learning","authors":"Xinrui Tan, Hongjia Li, Liming Wang, Zhen Xu","doi":"10.1109/WCNC45663.2020.9120765","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120765","url":null,"abstract":"Bring-Your-Own-Device (BYOD) has been widely viewed as a definite trend among enterprises in which employees bring and use their personal smartphones for work. Despite the perceived opportunities of increasing productivity and reducing costs, BYOD raises severe security and privacy concerns: the corporate networks and data are directly exposed to malware apps running on the personal smartphones. This highlights the necessity for performing real-time mobile malware detection in BYOD environments. Deep learning seems to be a natural choice to handle such detection, due to its state-of-the-art detection effectiveness. However, deep learning inference is usually too computationally complex for resource-constrained smartphones, and the communication overhead of cloud-based inference may be unacceptable. As a result, it is hard to seek the tradeoff between the real-time demand and optimality of detection accuracy. In this paper, we tackle this issue by proposing an endedge coordinated inference approach that can support highlyaccurate and average latency guaranteed malware detection. Our proposed approach integrates the early-exit and model partitioning methods to allow fast, correct and smartphonelocalized inference to occur frequently. Extensive evaluations are carried out, demonstrating that our proposed approach offers a good compromise between detection accuracy and efficiency.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129018910","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120651
Xinbo Wang, Li Guo, Chao Dong, Xidong Mu
In millimeter-wave (mmWave) communication systems, hybrid beamforming is regarded as an effective way to increase the spectral efficiency of the massive multiple-input multiple-output (MIMO) system. Assuming perfect channel state information (CSI) is known at the transmitter, we focus on a downlink massive multi-user MIMO system which supports multi-stream per user. In the above scenario, we investigate the hybrid beamforming problem with strong correlation between users’ channels, where the existing schemes have performance loss. To tackle this problem, this paper proposes the channel correlation cancelation-based hybrid beamforming (CCCHB) algorithm which considers the correlation between channels and decomposes the optimization of overall spectrum efficiency of the users to a series of sub-rate optimization problems. And the block diagonalization (BD) technique is used in the equivalent channel to eliminate inter-user interference. Simulation results illustrate that the performance of the proposed scheme outperforms the existing algorithm, especially significant when there exists high correlation between users’ channels.
{"title":"Channel Correlation Cancelation-Based Hybrid Beamforming for Massive Multiuser MIMO Systems","authors":"Xinbo Wang, Li Guo, Chao Dong, Xidong Mu","doi":"10.1109/WCNC45663.2020.9120651","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120651","url":null,"abstract":"In millimeter-wave (mmWave) communication systems, hybrid beamforming is regarded as an effective way to increase the spectral efficiency of the massive multiple-input multiple-output (MIMO) system. Assuming perfect channel state information (CSI) is known at the transmitter, we focus on a downlink massive multi-user MIMO system which supports multi-stream per user. In the above scenario, we investigate the hybrid beamforming problem with strong correlation between users’ channels, where the existing schemes have performance loss. To tackle this problem, this paper proposes the channel correlation cancelation-based hybrid beamforming (CCCHB) algorithm which considers the correlation between channels and decomposes the optimization of overall spectrum efficiency of the users to a series of sub-rate optimization problems. And the block diagonalization (BD) technique is used in the equivalent channel to eliminate inter-user interference. Simulation results illustrate that the performance of the proposed scheme outperforms the existing algorithm, especially significant when there exists high correlation between users’ channels.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124736217","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120821
G. Choudhary, M. Kanagarathinam, Harikrishnan Natarajan, K. Arunachalam, Sujith Rengan Jayaseelan, Gaurav Sinha, D. Das
To improve the performance of the Transmission Control Protocol (TCP), the Quick UDP Internet Connections (QUIC) was introduced. However, from the recent literature, in the wireless networks, QUIC does not fully utilize the link capacity, because of varying network wireless medium characteristics for an application. To the best of our knowledge, for the first time, this paper has proposed two novel protocols to overcome the wireless network’s challenges, by MultiPipe (multi sessions) QUIC protocol (MP-QUIC). The two MP-QUIC’s novel protocols are (i) Round Robin MP-QUIC (RR-MP-QUIC) and (ii) Cross-Layer Burst Aware MP-QUIC (CBA-MP-QUIC). In RR-MP-QUIC, multiple pipes are created between source as well as destination and assign a pipe to each object in a round-robin manner. We set up the testbed over live air commercial network. The experimental results reveal that the RR-MP-QUIC Page Load Time (PLT) of a web page decreases by 76% with respect to QUIC. Furthermore, to improve the performance of RR-MPQUIC, we proposed CBA-MP-QUIC, which optimally creates pipes, efficiently schedules the objects and understands with respect to cross-layer (wireless channel characteristics and load in data link layer) parameters. Hence this adapts dynamically to the network conditions and maintains fairness between the applications in User Equipment (UE) and within the same application. Experimental result of CBA-MP-QUIC on live air improves the web page PLT by 143% with respect to QUIC.
为了提高传输控制协议(TCP)的性能，引入了快速UDP Internet连接(QUIC)。然而，从最近的文献来看，在无线网络中，QUIC并没有充分利用链路容量，因为不同的网络无线介质的特性不同。据我们所知，本文首次提出了两种新的协议来克服无线网络的挑战，即MultiPipe(多会话)QUIC协议(MP-QUIC)。MP-QUIC的两个新协议是(i)轮询MP-QUIC (RR-MP-QUIC)和(ii)跨层突发感知MP-QUIC (CBA-MP-QUIC)。在RR-MP-QUIC中，在源和目标之间创建多个管道，并以轮询方式为每个对象分配一个管道。我们在实时航空商业网络上建立了测试平台。实验结果表明，相对于QUIC, rp - mp -QUIC的网页加载时间(PLT)减少了76%。此外，为了提高RR-MPQUIC的性能，我们提出了CBA-MP-QUIC，它可以最优地创建管道，有效地调度对象，并理解跨层(无线信道特性和数据链路层中的负载)参数。因此，这可以动态地适应网络条件，并保持用户设备(UE)和同一应用程序中的应用程序之间的公平性。CBA-MP-QUIC在现场空气中的实验结果表明，与QUIC相比，CBA-MP-QUIC可将网页PLT提高143%。
{"title":"Novel MultiPipe QUIC Protocols to Enhance the Wireless Network Performance","authors":"G. Choudhary, M. Kanagarathinam, Harikrishnan Natarajan, K. Arunachalam, Sujith Rengan Jayaseelan, Gaurav Sinha, D. Das","doi":"10.1109/WCNC45663.2020.9120821","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120821","url":null,"abstract":"To improve the performance of the Transmission Control Protocol (TCP), the Quick UDP Internet Connections (QUIC) was introduced. However, from the recent literature, in the wireless networks, QUIC does not fully utilize the link capacity, because of varying network wireless medium characteristics for an application. To the best of our knowledge, for the first time, this paper has proposed two novel protocols to overcome the wireless network’s challenges, by MultiPipe (multi sessions) QUIC protocol (MP-QUIC). The two MP-QUIC’s novel protocols are (i) Round Robin MP-QUIC (RR-MP-QUIC) and (ii) Cross-Layer Burst Aware MP-QUIC (CBA-MP-QUIC). In RR-MP-QUIC, multiple pipes are created between source as well as destination and assign a pipe to each object in a round-robin manner. We set up the testbed over live air commercial network. The experimental results reveal that the RR-MP-QUIC Page Load Time (PLT) of a web page decreases by 76% with respect to QUIC. Furthermore, to improve the performance of RR-MPQUIC, we proposed CBA-MP-QUIC, which optimally creates pipes, efficiently schedules the objects and understands with respect to cross-layer (wireless channel characteristics and load in data link layer) parameters. Hence this adapts dynamically to the network conditions and maintains fairness between the applications in User Equipment (UE) and within the same application. Experimental result of CBA-MP-QUIC on live air improves the web page PLT by 143% with respect to QUIC.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129883181","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120783
Yuanqi Chen, Yongjie Guan, Tao Han
While webcast platforms on mobile devices are becoming more and more prevalent, inspection for irregularities is getting harder and harder. To solve this problem, the convolution neural network(CNN) has been applied to recognize or detect specified objections in pictures and videos. However, when supervising large platforms, it isn’t very easy to collect mountain piles of video data and send them to the computation center. Other problems like long time delay and the high computational burden will reduce system performance, especially when dealing with data from live streams. This paper presents a method to coordinate mobile devices with remote servers(computers or embedded systems) to achieve real-time monitoring of live streams. The system can make use of computational capacity on mobile devices and reduce the cost of sending data while guaranteeing accuracy for supervision.
{"title":"Distributed Video Analysis for Mobile Live Broadcasting Services","authors":"Yuanqi Chen, Yongjie Guan, Tao Han","doi":"10.1109/WCNC45663.2020.9120783","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120783","url":null,"abstract":"While webcast platforms on mobile devices are becoming more and more prevalent, inspection for irregularities is getting harder and harder. To solve this problem, the convolution neural network(CNN) has been applied to recognize or detect specified objections in pictures and videos. However, when supervising large platforms, it isn’t very easy to collect mountain piles of video data and send them to the computation center. Other problems like long time delay and the high computational burden will reduce system performance, especially when dealing with data from live streams. This paper presents a method to coordinate mobile devices with remote servers(computers or embedded systems) to achieve real-time monitoring of live streams. The system can make use of computational capacity on mobile devices and reduce the cost of sending data while guaranteeing accuracy for supervision.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126788837","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120669
Fred Wiffen, M. Z. Bocus, A. Doufexi, W. Chin
In this work we propose a fronthaul compression scheme for distributed MIMO systems with multi-antenna receivers, in which, prior to signal quantisation, dimension reduction is performed at each receiver by matched filtering the received signal with a subset of the local user channel vectors. By choosing these matched filter vectors based on global channel information, a high proportion of the potential capacity may be captured by a small number of signal components, which can then be compressed efficiently using local signal compression. We outline a greedy algorithm for selecting the matched filtering vectors for each receiver, and a local transform coding approach for quantising them, giving expressions for the resulting system sum and user capacities. We then show that the scheme is easily modified to account for imperfect CSI at the receivers. Numerical results show that with a low signal dimension the scheme is able to operate very close to the cut-set bound in the fronthaul limited regime, and demonstrates significant improvements in rate-capacity trade-off versus local compression at all operating points, particularly at high SNR.
{"title":"MF-based Dimension Reduction Signal Compression for Fronthaul-Constrained Distributed MIMO C-RAN","authors":"Fred Wiffen, M. Z. Bocus, A. Doufexi, W. Chin","doi":"10.1109/WCNC45663.2020.9120669","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120669","url":null,"abstract":"In this work we propose a fronthaul compression scheme for distributed MIMO systems with multi-antenna receivers, in which, prior to signal quantisation, dimension reduction is performed at each receiver by matched filtering the received signal with a subset of the local user channel vectors. By choosing these matched filter vectors based on global channel information, a high proportion of the potential capacity may be captured by a small number of signal components, which can then be compressed efficiently using local signal compression. We outline a greedy algorithm for selecting the matched filtering vectors for each receiver, and a local transform coding approach for quantising them, giving expressions for the resulting system sum and user capacities. We then show that the scheme is easily modified to account for imperfect CSI at the receivers. Numerical results show that with a low signal dimension the scheme is able to operate very close to the cut-set bound in the fronthaul limited regime, and demonstrates significant improvements in rate-capacity trade-off versus local compression at all operating points, particularly at high SNR.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129173592","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 : 2020-05-01DOI: 10.1109/WCNC45663.2020.9120511
Sharan Naribole, E. Knightly
Contention-based uplink radio access might lead to significant degradation in airtime efficiency and energy efficiency as the time spent “awake” by the radio is dependent on the network traffic conditions. In this paper, we design and evaluate LiSCAN, a visible light uni-directional control channel for contention-free uplink radio access. LiSCAN enables a virtual full-duplex operation by broadcasting polling frames (light-polls) across distributed LED luminaires concurrently with data reception over radio. In LiSCAN, each client consists of an additional low-power light sensor, which upon hearing a light-poll directed to it by Access Point (AP), wakes up the radio module only if there is backlogged traffic. To maximize the airtime efficiency, LiSCAN transmits light-polls successively until it detects an uplink radio transmission. LiSCAN’s pipelined polling enables clients to detect failure in uplink packet reception and accordingly abort their transmissions to eliminate collisions at the AP. We simulate LiSCAN and alternate strategies in ns3 network simulator to analyze LiSCAN’s performance under varying traffic conditions. Our results show that LiSCAN can provide significant improvements in the radio airtime efficiency, the sessions delivered with pre-defined service quality requirements and energy savings.
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