MU-MIMO performance with a circular base station array and semi-orthogonal user selection

Cooperative communication supported by device to device (D2D)-LEO earthed satellite increases the performance of the resilient network and offloads base station. Additionally, network coding in a packet-based cooperative framework provides diversity and speedy recovery of lost packets. Cooperative communication advantages are subject to effective joint admission control strengthened by network coding for multiple interfaces. Joint admission control with network coding involves multiple constraints in terms of user selection, mode assignment, power allocation, and interface-based network codewords, which is challenging to solve collectively. Sub-problematization and its heuristic solution lead to a less complex solution. First, the adaptive terrestrial satellite power sentient network (ATSPSN) algorithm is proposed based on low complex convex linearization of mix integer non-linear problem (MINLP), NP-hard. ATSPSN provides optimum power allocation, mode assignment, and user selection based on joint channel conditions. Second, a multiple access network coding algorithm (MANC) is developed underlying the D2D-satellite network, which provides novel multiple interface random linear network codewords. At the end, the bi-directional matching algorithm aiming for joint admission control with network coding, named JAMANC-stream and JAMANC-batch communication, is proposed. JAMANC algorithm leads to a less complex solution and provides improved results in terms of capacity, power efficiency, and packet completion time. The theoretical lower and upper bounds are also derived for comparative study.

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Antenna and user selection for a cloud base station with (Reverse) Compute and Forward

2012 IEEE Globecom Workshops ◽

10.1109/glocomw.2012.6477580 ◽

2012 ◽

Cited By ~ 6

Author(s):

Song-Nam Hong ◽

Giuseppe Caire

Keyword(s):

Base Station ◽

Cloud Base ◽

User Selection ◽

Selection For

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Sum Rate Analysis for Massive MIMO Downlink With MRC Beamforming and User Selection

Journal of Physics Conference Series ◽

10.1088/1742-6596/2113/1/012025 ◽

2021 ◽

Vol 2113 (1) ◽

pp. 012025

Author(s):

Yiyang Wu ◽

Chang Chang ◽

Fei Xie ◽

Dacheng Ju ◽

Yilun Pan

Keyword(s):

Channel Model ◽

Base Station ◽

Transmission Model ◽

User Selection ◽

Selection Algorithm ◽

User Scheduling ◽

Downlink System ◽

Sum Rate ◽

Simulation Results ◽

Mimo Downlink

Abstract Average allocation of data rate to each user is inefficient since the resource a base station can allocate is limited. Thus, user selection and user scheduling need to be applied into multi-user massive multiple-input multiple-output (MIMO) downlink system. In this paper, we mainly focus on the methods of user selection. First, we establish a downlink system model including transmission model and channel model. Then, two user-rate based user selection algorithms via the signal-to-interference-plus-noise-ratio (SINR) are proposed, where the SINR is generated by MRC beamforming. Finally, simulation results are provided to compare the performance of two proposed algorithms and their fairness towards selected users. In the simulation results, location-based selection algorithm and random selection algorithm are jointly compared. The second proposed algorithm possesses the highest total sum-rate and is the optimal algorithms among the four algorithms.

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Performance evaluation of user selection based on average SNR in base station cooperation multi-user MIMO

2010 IEEE Radio and Wireless Symposium (RWS) ◽

10.1109/rws.2010.5434247 ◽

2010 ◽

Cited By ~ 1

Author(s):

Yohsuke Seki ◽

Osamu Takyu ◽

Yohtaro Umeda

Keyword(s):

Performance Evaluation ◽

Base Station ◽

User Selection ◽

Base Station Cooperation

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Wireless Network Optimization for Federated Learning with Model Compression in Hybrid VLC/RF Systems

Entropy ◽

10.3390/e23111413 ◽

2021 ◽

Vol 23 (11) ◽

pp. 1413

Author(s):

Wuwei Huang ◽

Yang Yang ◽

Mingzhe Chen ◽

Chuanhong Liu ◽

Chunyan Feng ◽

...

Keyword(s):

Wireless Network ◽

Bandwidth Allocation ◽

Optimization Problem ◽

Visible Light Communication ◽

Base Station ◽

Allocation Problem ◽

Model Parameters ◽

User Selection ◽

Wireless Links ◽

Model Compression

In this paper, the optimization of network performance to support the deployment of federated learning (FL) is investigated. In particular, in the considered model, each user owns a machine learning (ML) model by training through its own dataset, and then transmits its ML parameters to a base station (BS) which aggregates the ML parameters to obtain a global ML model and transmits it to each user. Due to limited radio frequency (RF) resources, the number of users that participate in FL is restricted. Meanwhile, each user uploading and downloading the FL parameters may increase communication costs thus reducing the number of participating users. To this end, we propose to introduce visible light communication (VLC) as a supplement to RF and use compression methods to reduce the resources needed to transmit FL parameters over wireless links so as to further improve the communication efficiency and simultaneously optimize wireless network through user selection and resource allocation. This user selection and bandwidth allocation problem is formulated as an optimization problem whose goal is to minimize the training loss of FL. We first use a model compression method to reduce the size of FL model parameters that are transmitted over wireless links. Then, the optimization problem is separated into two subproblems. The first subproblem is a user selection problem with a given bandwidth allocation, which is solved by a traversal algorithm. The second subproblem is a bandwidth allocation problem with a given user selection, which is solved by a numerical method. The ultimate user selection and bandwidth allocation are obtained by iteratively compressing the model and solving these two subproblems. Simulation results show that the proposed FL algorithm can improve the accuracy of object recognition by up to 16.7% and improve the number of selected users by up to 68.7%, compared to a conventional FL algorithm using only RF.

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Scalable user selection in FDD massive MIMO

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-02073-4 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Xing Zhang ◽

Ashutosh Sabharwal

Keyword(s):

Channel Estimation ◽

Massive Mimo ◽

Mimo Systems ◽

Base Station ◽

User Selection ◽

Selection Scheme ◽

Base Station Antennas ◽

Measurement Selection ◽

Weighted Sum Rate ◽

Experimental Findings

AbstractUser subset selection requires full downlink channel state information to realize effective multi-user beamforming in frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. However, the channel estimation overhead scales with the number of users in FDD systems. In this paper, we propose a novel propagation domain-based user selection scheme, labeled as zero-measurement selection, for FDD massive MIMO systems with the aim of reducing the channel estimation overhead that scales with the number of users. The key idea is to infer downlink user channel norm and inter-user channel correlation from uplink channel in the propagation domain. In zero-measurement selection, the base-station performs downlink user selection before any downlink channel estimation. As a result, the downlink channel estimation overhead for both user selection and beamforming is independent of the total number of users. Then, we evaluate zero-measurement selection with both measured and simulated channels. The results show that zero-measurement selection achieves up to 92.5% weighted sum rate of genie-aided user selection on the average and scales well with both the number of base-station antennas and the number of users. We also employ simulated channels for further performance validation, and the numerical results yield similar observations as the experimental findings.

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Fine structure of the rectal papillae of the oriental fruuit fly, Dacus dorsalis Hendel (Tephritidae, Diptera Insecta)

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100160042 ◽

1990 ◽

Vol 48 (3) ◽

pp. 498-499

Author(s):

Len Wen-Yung ◽

Mei-Jung Lin

Keyword(s):

Fine Structure ◽

Cell Membrane ◽

Intercellular Space ◽

Anterior Part ◽

Apical Cell ◽

Posterior Part ◽

Apical Cell Membrane ◽

Dacus Dorsalis ◽

Radial Cell ◽

Circular Base

Four cone-shaped rectal papillae locate at the anterior part of the rectum in Dacus dorsalis fly. The circular base of the papilla protrudes into the haemolymph (Fig. 1,2) and the rest cone-shaped tip (Fig. 2) inserts in the rectal lumen. The base is surrounded with the cuticle (Fig. 5). The internal structure of the rectal papilla (Fig. 3) comprises of the cortex with the columnar epithelial cells and a rod-shaped medulla. Between them, there is the infundibular space and many trabeculae connect each other. Several tracheae insert into the papilla through the top of the medulla, then run into the cortical epithelium and locate in the intercellular space. The intercellular sinuses distribute in the posterior part of the rectal papilla.The cortex of the base divides into about thirty segments. Between segments there is a radial cell (Fig. 4). Under the cuticle, the apical cell membrane of the cortical epithelium is folded into a regular border of leaflets (Fig. 5).

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A Survey on Hierarchical Cluster Based Secure Routing Protocols and Key Management Schemes in Wireless Sensor Networks

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit183810 ◽

2018 ◽

pp. 18-26

Author(s):

Yugashree Bhadane ◽

Pooja Kadam

Keyword(s):

Routing Protocol ◽

Routing Protocols ◽

Key Management ◽

Energy Efficient ◽

Base Station ◽

Secure Routing ◽

Sensor Nodes ◽

Wireless Sensor ◽

Management Schemes ◽

Cluster Based Routing

Now days, wireless technology is one of the center of attention for users and researchers. Wireless network is a network having large number of sensor nodes and hence called as “Wireless Sensor Network (WSN)”. WSN monitors and senses the environment of targeted area. The sensor nodes in WSN transmit data to the base station depending on the application. These sensor nodes communicate with each other and routing is selected on the basis of routing protocols which are application specific. Based on network structure, routing protocols in WSN can be divided into two categories: flat routing, hierarchical or cluster based routing, location based routing. Out of these, hierarchical or cluster based routing is becoming an active branch of routing technology in WSN. To allow base station to receive unaltered or original data, routing protocol should be energy-efficient and secure. To fulfill this, Hierarchical or Cluster base routing protocol for WSN is the most energy-efficient among other routing protocols. Hence, in this paper, we present a survey on different hierarchical clustered routing techniques for WSN. We also present the key management schemes to provide security in WSN. Further we study and compare secure hierarchical routing protocols based on various criteria.

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