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Communications and Networking

Decode-efficient prefix codes for hierarchical memory models

Rishikesh Gajjala

The cost of uncompressing (decoding) data can be prohibitive in certain real-time applications,
for example when predicting using compressed deep learning models. In many scenarios, it is
acceptable to sacrifice to some extent on compression in the interest of fast decoding. In this
work, we are interested in finding the prefix tree having the best decode time under the constraint
that the code length does not exceed a certain threshold for a natural class of algorithms under

Paper Details

Authors:
Rishikesh Gajjala
Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗
Submitted On:
31 March 2020 - 11:39am
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[1] Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗, "Decode-efficient prefix codes for hierarchical memory models", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5050. Accessed: Apr. 04, 2020.
@article{5050-20,
url = {http://sigport.org/5050},
author = {Shashwat Banchhor ; Rishikesh R. Gajjala ; Yogish Sabharwal ; and Sandeep Sen∗ },
publisher = {IEEE SigPort},
title = {Decode-efficient prefix codes for hierarchical memory models},
year = {2020} }
TY - EJOUR
T1 - Decode-efficient prefix codes for hierarchical memory models
AU - Shashwat Banchhor ; Rishikesh R. Gajjala ; Yogish Sabharwal ; and Sandeep Sen∗
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5050
ER -
Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗. (2020). Decode-efficient prefix codes for hierarchical memory models. IEEE SigPort. http://sigport.org/5050
Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗, 2020. Decode-efficient prefix codes for hierarchical memory models. Available at: http://sigport.org/5050.
Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗. (2020). "Decode-efficient prefix codes for hierarchical memory models." Web.
1. Shashwat Banchhor , Rishikesh R. Gajjala , Yogish Sabharwal , and Sandeep Sen∗. Decode-efficient prefix codes for hierarchical memory models [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5050

Functional Epsilon Entropy

Sourya Basu
Daewon Seo
Lav Varshney

We consider the problem of coding for computing with maximal distortion, where the sender communicates with a receiver, which has its own private data and wants to compute a function of their combined data with some fidelity constraint known to both agents. We show that the minimum rate for this problem is equal to the conditional entropy of a hypergraph and design practical codes for the problem. Further, the minimum rate of this problem may be a discontinuous function of the fidelity constraint.

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Authors:
Sourya Basu
Daewon Seo
Lav Varshney
Sourya Basu, Daewon Seo, Lav Varshney
Submitted On:
20 March 2020 - 12:58am
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[1] Sourya Basu, Daewon Seo, Lav Varshney, "Functional Epsilon Entropy", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5008. Accessed: Apr. 04, 2020.
@article{5008-20,
url = {http://sigport.org/5008},
author = {Sourya Basu; Daewon Seo; Lav Varshney },
publisher = {IEEE SigPort},
title = {Functional Epsilon Entropy},
year = {2020} }
TY - EJOUR
T1 - Functional Epsilon Entropy
AU - Sourya Basu; Daewon Seo; Lav Varshney
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5008
ER -
Sourya Basu, Daewon Seo, Lav Varshney. (2020). Functional Epsilon Entropy. IEEE SigPort. http://sigport.org/5008
Sourya Basu, Daewon Seo, Lav Varshney, 2020. Functional Epsilon Entropy. Available at: http://sigport.org/5008.
Sourya Basu, Daewon Seo, Lav Varshney. (2020). "Functional Epsilon Entropy." Web.
1. Sourya Basu, Daewon Seo, Lav Varshney. Functional Epsilon Entropy [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5008

Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources

Bowei Shan

This paper designs a Distributed Arithmetic Coding (DAC) decoder using the depth- first search method. In addition, a method is proposed to control the decoder complexity. Simulation results compare the DFD with the traditional Breadth-First Decoder (BFD)
showing that under the same complexity constraints, the DFD outperforms the BFD when the code length is not too long and the quality of side information is not too poor.

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Authors:
Bowei Shan
Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang
Submitted On:
18 March 2020 - 8:22pm
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[1] Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang, "Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5000. Accessed: Apr. 04, 2020.
@article{5000-20,
url = {http://sigport.org/5000},
author = {Yong Fang; Vladimir Stankovic; Samuel Cheng; En-hui Yang },
publisher = {IEEE SigPort},
title = {Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources},
year = {2020} }
TY - EJOUR
T1 - Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources
AU - Yong Fang; Vladimir Stankovic; Samuel Cheng; En-hui Yang
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5000
ER -
Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang. (2020). Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources. IEEE SigPort. http://sigport.org/5000
Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang, 2020. Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources. Available at: http://sigport.org/5000.
Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang. (2020). "Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources." Web.
1. Yong Fang, Vladimir Stankovic, Samuel Cheng, En-hui Yang. Depth-First Decoding of Distributed Arithmetic Codes for Uniform Binary Sources [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5000

Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO

alireza morsali

Hybrid beamforming has attracted considerable attention in recent years as an efficient and promising technique for the practical implementation of millimeter-Wave (mmWave) massive multiple-input multiple-output (MIMO) wireless systems. In this paper, we investigate hybrid analog/digital beamforming designs based on a single RF chain architecture (SRCA) for mmWave massive-MIMO. We first revisit the SRCA and then explore its shortcomings.

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Authors:
alireza morsali
Alireza Morsali, Sara Norouzi, and Benoit Champagne
Submitted On:
12 November 2019 - 11:07pm
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[1] Alireza Morsali, Sara Norouzi, and Benoit Champagne, "Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4953. Accessed: Apr. 04, 2020.
@article{4953-19,
url = {http://sigport.org/4953},
author = {Alireza Morsali; Sara Norouzi; and Benoit Champagne },
publisher = {IEEE SigPort},
title = {Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO},
year = {2019} }
TY - EJOUR
T1 - Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO
AU - Alireza Morsali; Sara Norouzi; and Benoit Champagne
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4953
ER -
Alireza Morsali, Sara Norouzi, and Benoit Champagne. (2019). Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO. IEEE SigPort. http://sigport.org/4953
Alireza Morsali, Sara Norouzi, and Benoit Champagne, 2019. Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO. Available at: http://sigport.org/4953.
Alireza Morsali, Sara Norouzi, and Benoit Champagne. (2019). "Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO." Web.
1. Alireza Morsali, Sara Norouzi, and Benoit Champagne. Single RF Chain Hybrid Analog/Digital Beamforming for mmWave Massive-MIMO [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4953

Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications

Ryuhei Takahashi

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Authors:
Ryuhei Takahashi
Ryuhei Takahashi, Koji Ishibashi
Submitted On:
8 November 2019 - 11:47am
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[1] Ryuhei Takahashi, Koji Ishibashi, "Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4932. Accessed: Apr. 04, 2020.
@article{4932-19,
url = {http://sigport.org/4932},
author = {Ryuhei Takahashi; Koji Ishibashi },
publisher = {IEEE SigPort},
title = {Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications},
year = {2019} }
TY - EJOUR
T1 - Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications
AU - Ryuhei Takahashi; Koji Ishibashi
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4932
ER -
Ryuhei Takahashi, Koji Ishibashi. (2019). Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications. IEEE SigPort. http://sigport.org/4932
Ryuhei Takahashi, Koji Ishibashi, 2019. Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications. Available at: http://sigport.org/4932.
Ryuhei Takahashi, Koji Ishibashi. (2019). "Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications." Web.
1. Ryuhei Takahashi, Koji Ishibashi. Ambient OFDM Pilot-Aided Delay-Shift Keying and Its Efficient Detection for Ultra Low-Power Communications [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4932

Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering

Hussein Ammar

Power delay profiles (PDPs) are an important factor in the design of wireless networks, e.g., in choosing the length of a cyclic prefix. While distributed networks are receiving increasing attention, the impact of cooperation on the PDP has not been addressed. We address this issue in this paper. Specifically, we analyze a network where each user is served by a cluster of Remote Radio Heads (RRHs) with RRH locations modeled as a Poisson point process.

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Authors:
Hussein Ammar
Raviraj Adve
Submitted On:
13 November 2019 - 11:43am
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[1] Raviraj Adve, "Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4909. Accessed: Apr. 04, 2020.
@article{4909-19,
url = {http://sigport.org/4909},
author = {Raviraj Adve },
publisher = {IEEE SigPort},
title = {Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering},
year = {2019} }
TY - EJOUR
T1 - Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering
AU - Raviraj Adve
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4909
ER -
Raviraj Adve. (2019). Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering. IEEE SigPort. http://sigport.org/4909
Raviraj Adve, 2019. Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering. Available at: http://sigport.org/4909.
Raviraj Adve. (2019). "Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering." Web.
1. Raviraj Adve. Power Delay Profile in Coordinated Distributed Networks: User Centric v/s Disjoint Clustering [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4909

Data Driven QoE-QoS Association Modeling of Conversational Video

HongCheng GU

In recent years, the variety and volume of multimedia services have increased exponentially. Like most of other multimedia services, the conversational video service has stringent quality of service and experience requirements. In order to better support users QoE (Quality of Experience) and allocate network resources more effectively, this paper focuses on the QoS (Quality of Service)-QoE association modeling of conversational video flows.

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Authors:
HongCheng GU
Submitted On:
29 October 2019 - 11:08pm
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[1] , "Data Driven QoE-QoS Association Modeling of Conversational Video", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4901. Accessed: Apr. 04, 2020.
@article{4901-19,
url = {http://sigport.org/4901},
author = { },
publisher = {IEEE SigPort},
title = {Data Driven QoE-QoS Association Modeling of Conversational Video},
year = {2019} }
TY - EJOUR
T1 - Data Driven QoE-QoS Association Modeling of Conversational Video
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4901
ER -
. (2019). Data Driven QoE-QoS Association Modeling of Conversational Video. IEEE SigPort. http://sigport.org/4901
, 2019. Data Driven QoE-QoS Association Modeling of Conversational Video. Available at: http://sigport.org/4901.
. (2019). "Data Driven QoE-QoS Association Modeling of Conversational Video." Web.
1. . Data Driven QoE-QoS Association Modeling of Conversational Video [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4901

Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI

Yongjun Xu

In this paper, a robust power allocation and subchannel assignment algorithm was proposed to maximize the total EE
of SUs for cognitive NOMA systems under taking channel uncertainties and diverse QoS requirements of users into account. The RAA problem was formulated into a non-convex mixed-integer fractional programming problem with the outage probabilities of users and thus difficult to solve. Based on Gaussian CSI error models, we transformed the robust rate constraint and the robust interference power constraint into the convex constraints. By slacking the integer subchannel allocation factor into a continuous variable, the original problem was converted into a convex problem by using the subtractive-form auxiliary variable. Based on the Lagrangian dual approach and the subgradient updating methods, the closed-form solutions were obtained. The effectiveness of the proposed algorithm was verified by comparing it with the existing algorithms.

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Authors:
Yongjun Xu
Yang Yang, Guoquan Li, Zhengqiang Wang
Submitted On:
29 October 2019 - 3:04pm
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[1] Yang Yang, Guoquan Li, Zhengqiang Wang, "Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4900. Accessed: Apr. 04, 2020.
@article{4900-19,
url = {http://sigport.org/4900},
author = {Yang Yang; Guoquan Li; Zhengqiang Wang },
publisher = {IEEE SigPort},
title = {Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI},
year = {2019} }
TY - EJOUR
T1 - Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI
AU - Yang Yang; Guoquan Li; Zhengqiang Wang
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4900
ER -
Yang Yang, Guoquan Li, Zhengqiang Wang. (2019). Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI. IEEE SigPort. http://sigport.org/4900
Yang Yang, Guoquan Li, Zhengqiang Wang, 2019. Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI. Available at: http://sigport.org/4900.
Yang Yang, Guoquan Li, Zhengqiang Wang. (2019). "Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI." Web.
1. Yang Yang, Guoquan Li, Zhengqiang Wang. Joint Subchannel and Power Allocation for Cognitive NOMA Systems with Imperfect CSI [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4900

MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION

yuyang liu

The recently-proposed reinforcement learning for mapless visual navigation can generate an optimal policy for searching different targets. However, most state-of-the-art deep reinforcement learning (DRL) models depend on hard rewards to learn the optimal policy, which can lead to the lack of previous diverse experiences. Moreover, these pre-trained DRL models cannot generalize well to un-trained tasks. To overcome these problems above, in this paper, we propose a Memorybased Parameterized Skills Learning (MPSL) model for mapless visual navigation.

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Authors:
yuyang liu
Yuyang Liu, Yang Cong and Gan Sun
Submitted On:
11 September 2019 - 11:06pm
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[1] Yuyang Liu, Yang Cong and Gan Sun, "MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4598. Accessed: Apr. 04, 2020.
@article{4598-19,
url = {http://sigport.org/4598},
author = {Yuyang Liu; Yang Cong and Gan Sun },
publisher = {IEEE SigPort},
title = {MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION},
year = {2019} }
TY - EJOUR
T1 - MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION
AU - Yuyang Liu; Yang Cong and Gan Sun
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4598
ER -
Yuyang Liu, Yang Cong and Gan Sun. (2019). MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION. IEEE SigPort. http://sigport.org/4598
Yuyang Liu, Yang Cong and Gan Sun, 2019. MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION. Available at: http://sigport.org/4598.
Yuyang Liu, Yang Cong and Gan Sun. (2019). "MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION." Web.
1. Yuyang Liu, Yang Cong and Gan Sun. MEMORY-BASED PARAMETERIZED SKILLS LEARNING FOR MAPLESS VISUAL NAVIGATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4598

When can a System of Subnetworks be Registered Uniquely?

Aditya Singh

Consider a network with N nodes in d dimensions, and M overlapping subsets P_1,...,P_M (subnetworks). Assume that the nodes in a given P_i are observed in a local coordinate system. We wish to register the subnetworks using the knowledge of the observed coordinates. More precisely, we want to compute the positions of the N nodes in a global coordinate system, given P_1,...,P_M and the corresponding local coordinates. Among other applications, this problem arises in divide-and-conquer algorithms for localization of adhoc sensor networks.

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Authors:
Aditya Singh
Aditya V. Singh, Kunal N. Chaudhury
Submitted On:
27 May 2019 - 5:42am
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Unique Point Cloud Registration

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[1] Aditya V. Singh, Kunal N. Chaudhury, "When can a System of Subnetworks be Registered Uniquely?", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4560. Accessed: Apr. 04, 2020.
@article{4560-19,
url = {http://sigport.org/4560},
author = {Aditya V. Singh; Kunal N. Chaudhury },
publisher = {IEEE SigPort},
title = {When can a System of Subnetworks be Registered Uniquely?},
year = {2019} }
TY - EJOUR
T1 - When can a System of Subnetworks be Registered Uniquely?
AU - Aditya V. Singh; Kunal N. Chaudhury
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4560
ER -
Aditya V. Singh, Kunal N. Chaudhury. (2019). When can a System of Subnetworks be Registered Uniquely?. IEEE SigPort. http://sigport.org/4560
Aditya V. Singh, Kunal N. Chaudhury, 2019. When can a System of Subnetworks be Registered Uniquely?. Available at: http://sigport.org/4560.
Aditya V. Singh, Kunal N. Chaudhury. (2019). "When can a System of Subnetworks be Registered Uniquely?." Web.
1. Aditya V. Singh, Kunal N. Chaudhury. When can a System of Subnetworks be Registered Uniquely? [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4560

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