Resource Allocation for Underlay Interfering D2D Networks With Multiantenna and Imperfect CSI

Elnourani, Mohamed; Deshmukh, Siddharth; Beferull-Lozano, Baltasar

doi:10.1109/tcomm.2022.3194193

Cited by 9 publications

(7 citation statements)

References 42 publications

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“…The work in [22] considered single and multiple antenna configurations for optimizing channel and power resources. The work in [23] considered two constraints, namely maximum power and a minimum rate, for optimizing energy efficiency for multicast D2D communication.…”

Section: A Literature Reviewmentioning

confidence: 99%

“…Objectives UpLink (UL)/DownLink (DL) Methodology Resource Sharing Model [13] D2D sum rate UL Two-stage resource sharing Many-to-many [14] D2D sum rate DL Matching theory One-to-one + one-to-many [15] D2D rate + system sum rate UL Stochastic optimization Multiple cellular environment [16] D2D sum rate UL Approximation + Stackelberg Many-to-many [17] D2D power UL Game theory One-to-many [18] D2D sum rate UL Joint subcarrier and power allocation Many-to-many [19] Network sum rate DL Matching theory One-to-many [20] Network throughput UL Weighted bipartite graph One-to-many [22] Network sum rate DL Joint channel and power allocation One-to-many [23] Energy efficiency UL Two-stage semi-distribution solution One-to-many [24] Network sum rate DL Joint channel and power allocation One-to-many [25] D2D sum rate UL Stochastic geometry One-to-many [27] Network throughput UL + DL Graph colouring Many-to-many [28] D2D cluster utility function UL Stackelberg One-to-one [29] System throughput UL Joint subcarrier and power allocation Many-to many [30] System power UL Joint channel and power allocation Many-to-many [31] System sum rate DL Heuristic algorithm Many-to-many [32] System sum rate DL Heuristic algorithm Many-to-many or natural disasters, is dependent on effective and efficient communication for public safety. However, as eNB can not differentiate between public safety and other communications and also due to heavy data traffic through the eNB, a dedicated service to public safety communication will be missed causing a communication delay for the first responders.…”

Section: Refmentioning

confidence: 99%

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An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach

Veedu,

Manjappa

2024

J. Commun. Netw.

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This study aims to give an edge to public safety applications over commercial applications in an underlay cellular-assisted device-to-device (D2D) communication. The proposed framework introduces two frameworks: Cluster-based many-to-many resource allocation and resource sharing framework (CMMRARS) and constant time power control algorithm (CTPCA). The RB assigned to a CUE can share with multiple DUE pairs, and the DUE pairs can also use RB assigned to multiple CUEs under the many-to-many strategy. The CMMRARS framework is responsible for resource allocation and resource sharing and accordingly, it is further divided into three sub-problems. The CTPCA framework is divided into two subproblems and used to find optimal power for cellular users and D2D transmitters to avoid cross-tier and co-tier interference. The K-means clustering algorithm is employed to form applicationspecific clusters, and it ensures that more cellular users fall into the public safety clusters so that the D2D users will get more resource-sharing options. Cellular users use a weighted bipartite graph to form a priority list of D2D users for resource sharing. The main objective of the proposed work is to enhance the system's sum rate by simultaneously reusing the same resource by multiple D2D pairs and safeguarding the Quality of Services provided to all kinds of network users. A theoretical justification is presented to ensure that the proposed frameworks terminate after a certain number of runs and congregate to a consistent matching. Simulation results show that the proposed method influences the overall system's sum rate and provides a preference for public safety applications over commercial applications.

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Section: A Literature Reviewmentioning

confidence: 99%

Section: Refmentioning

confidence: 99%

An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach

Veedu,

Manjappa

2024

J. Commun. Netw.

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“…Nevertheless, they offer manageable expressions that can be effectively handled and significantly expedite convergence. Authors in [37] have numerically demonstrated the negligible impact of this alteration on the feasibility region. Furthermore, exploiting the lower bound for the random SINR constraint (13), the respective probabilistic constraint can be further expressed as:…”

Section: And the Value Ofmentioning

confidence: 99%

Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

Zhao,

Yu,

Pan

et al. 2024

IEEE Access

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The densification of low-Earth orbit (LEO) constellations and the development of inter-satellite links enable the cooperative transmission of multiple satellites. This paper investigates a decentralized resource allocation strategy for multi-satellite cooperation networks under statistical channel state information (CSI). Our formulation aims at minimizing the total matching error between non-uniform traffic requests and achievable throughput by jointly optimizing transmit power and beam illumination pattern. The original problem is a stochastic mixed-integer quadratic programming with the long-term accumulation nature, whose stochastic objective is first addressed by incorporating the outage probability constraint. Then we decompose the deterministic problem into a series of single-timeslot subproblems on the greedy basis, each of which is further decomposed for each satellite following the decentralized decision principle with a limited number of inter-satellite interactions required to obtain the overall resource allocation. Finally, the optimization problem at each satellite is solved by sequential quadratic programming (SQP)-based alternating optimization algorithm that iterates between the transmit power allocation and beam illumination design. Numerical results show the effectiveness of the proposed decentralized algorithm in reducing the total matching error by at least 27% over other baseline approaches.

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“…D2D communication is low latency and highly reliable, which makes it perfect for vehicle-to-vehicle (V2V), UAV, and emergency communications [8][9][10][11][12][13]. Academic and industrial researchers are becoming increasingly interested in this topic, so much research has been done on mode selection, power control, and resource allocation [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation for D2D Communication Underlaying Cellular Networks: A Distance-Based Grouping Strategy

Gao

Meng

Yang

et al. 2023

Wireless Communications and Mobile Computing

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Device-to-device (D2D) communication with direct terminal connection is a promising candidate for 5G communication, which increases the capacity of cellular networks and spectral efficiency. Introducing D2D communication to cellular users (CUs) will increase system capacity, and CUs will provide reusable channel resources for D2D users (DUs). However, the sharing of channel resources between CUs and DUs will lead to cofrequency interference and affect the communication quality of user terminals. As a means of improving spectrum utilization and solving cofrequency interference problems, a one-to-many D2D communication system model is established in cellular networks. Through model analysis, the interference between CUs and DUs is correlated with their distance from one another. Considering the different interference of CUs to DUs at different distances, an algorithm for resource allocation based on distance grouping is proposed. With this algorithm, DUs will reuse channel resources of CUs within a reasonable distance in the group, and interference between DUs and CUs will be minimized. The improved particle swarm optimization algorithm is used to solve the optimal power, to achieve the maximum transmission rate of the system. Simulated results show that the algorithm will significantly improve system throughput and performance while also lowering the computational complexity of the algorithm, enabling the whole system to have better communication quality.

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Resource Allocation for Underlay Interfering D2D Networks With Multiantenna and Imperfect CSI

Cited by 9 publications

References 42 publications

An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach

An efficient application based many-to-many resource allocation and sharing with power optimization for D2D communication — A clustered approach

Dynamic Resource Allocation for Multi-Satellite Cooperation Networks: A Decentralized Scheme Under Statistical CSI

Resource Allocation for D2D Communication Underlaying Cellular Networks: A Distance-Based Grouping Strategy

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