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Channel allocation schemes

About: Channel allocation schemes is a research topic. Over the lifetime, 10656 publications have been published within this topic receiving 182117 citations.


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Journal ArticleDOI
TL;DR: An efficient graph-theoretical approach is proposed to perform channel allocation, which offers flexibility with respect to allocation criteria (aggregate utility maximization, fairness, and quality-of-service (QoS) guarantee).
Abstract: The basic idea of device-to-device (D2D) communication is that pairs of suitably selected wireless devices reuse the cellular spectrum to establish direct communication links, provided that the adverse effects of D2D communication on cellular users are minimized and that cellular users are given higher priority in using limited wireless resources. Despite its great potential in terms of coverage and capacity performance, implementing this new concept poses some challenges, particularly with respect to radio resource management. The main challenges arise from a strong need for distributed D2D solutions that operate in the absence of precise channel and network knowledge. To address this challenge, this paper studies a resource allocation problem in a single-cell wireless network with multiple D2D users sharing the available radio frequency channels with cellular users. We consider a realistic scenario where the base station (BS) is provided with strictly limited channel knowledge, whereas D2D and cellular users have no information. We prove a lower bound for the cellular aggregate utility in the downlink with fixed BS power, which allows for decoupling the channel allocation and D2D power control problems. An efficient graph-theoretical approach is proposed to perform channel allocation, which offers flexibility with respect to allocation criteria (aggregate utility maximization, fairness, and quality-of-service (QoS) guarantee). We model the power control problem as a multiagent learning game. We show that the game is an exact potential game with noisy rewards, which is defined on a discrete strategy set, and characterize the set of Nash equilibria. Q-learning better-reply dynamics is then used to achieve equilibrium.

86 citations

Journal ArticleDOI
TL;DR: It is proved the existence of Walrasian equilibrium and proposed a cooperative mechanism to reach it and the performance and complexity of the proposed solutions are illustrated by numerical simulations.
Abstract: We consider a set of secondary transmitter-receiver pairs in a cognitive radio setting. Based on channel sensing and access performances, we consider the problem of assigning channels orthogonally to secondary users through distributed coordination and cooperation algorithms. Two economic models are applied for this purpose: matching markets and competitive markets. In the matching market model, secondary users and channels build two agent sets. We implement a stable matching algorithm in which each secondary user, based on his achievable rate, proposes to the coordinator to be matched with desirable channels. The coordinator accepts or rejects the proposals based on the channel preferences which depend on interference from the secondary user. The coordination algorithm is of low complexity and can adapt to network dynamics. In the competitive market model, channels are associated with prices and secondary users are endowed with monetary budget. Each secondary user, based on his utility function and current channel prices, demands a set of channels. A Walrasian equilibrium maximizes the sum utility and equates the channel demand to their supply. We prove the existence of Walrasian equilibrium and propose a cooperative mechanism to reach it. The performance and complexity of the proposed solutions are illustrated by numerical simulations.

86 citations

Journal ArticleDOI
TL;DR: By exploiting device-to-device (D2D) communication for enabling user collaboration and reducing the edge server’s load, this paper investigates the D2D-assisted and NOMA-based MEC system and proposes a scheduling-based joint computing resource, power, and channel allocations algorithm to achieve the joint optimization.
Abstract: Mobile edge computing (MEC) and non-orthogonal multiple access (NOMA) have been considered as the promising techniques to address the explosively growing computation-intensive applications and accomplish the requirement of massive connectivity in the fifth-generation networks. Moreover, since the computing resources of the edge server are limited, the computing load of the edge server needs to be effectively alleviated. In this paper, by exploiting device-to-device (D2D) communication for enabling user collaboration and reducing the edge server's load, we investigate the D2D-assisted and NOMA-based MEC system. In order to minimize the weighted sum of the energy consumption and delay of all users, we jointly optimize the computing resource, power, and channel allocations. Regarding the computing resource allocation, we propose an adaptive algorithm to find the optimal solution. Regarding the power allocation, we present a novel power allocation algorithm based on the particle swarm optimization (PSO) for the single NOMA group comprised of multiple cellular users. Then, for the matching group comprised of a NOMA group and D2D pairs, we theoretically derive the interval of optimal power allocation and propose a PSO-based algorithm to solve it. Regarding the channel allocation, we propose a one-to-one matching algorithm based on the Pareto improvement and swapping operations and extend the one-to-one matching algorithm to a many-to-one matching scenario. Finally, we propose a scheduling-based joint computing resource, power, and channel allocations algorithm to achieve the joint optimization. The simulation results show that the proposed solution can effectively reduce the weighted sum of the energy consumption and delay of all users.

85 citations

Journal ArticleDOI
TL;DR: This paper investigates the issue of fairness in IEEE 802.11-based multirate wireless local area networks and demonstrates that under time-based fairness, the throughput that a tagged node achieves in a multirates WLAN with nodes is identical to what it would achieve in a single-rate W LAN with nodes all at the same data rate.
Abstract: This paper investigates the issue of fairness in IEEE 802.11-based multirate wireless local area networks (WLANs). Distributed coordination function, which is the medium-access control (MAC) protocol used in 802.11 WLANs, provides equal long-term channel access probability to competing stations, irrespective of the time required in sending a frame. When equal-sized frames are used and channel conditions are similar, each station, regardless of its data rate, achieves the same throughput. Furthermore, the aggregate throughput is reduced to a level much closer to what one gets when all stations are of lower rate. This anomaly in the performance is a result of unfair channel time allocation for stations when they use multiple data rates. We consider provisioning of time-based fairness in which each station receives an equal share of the wireless channel occupancy time. We demonstrate that under time-based fairness, the throughput that a tagged node achieves in a multirate WLAN with nodes is identical to what it would achieve in a single-rate WLAN with nodes all at the same data rate as the tagged node. Furthermore, we show that under time-based fairness scheme, the ratio of throughputs per station corresponding to two different bit rates is directly proportional to the ratio of their bit rates. We analyze different mechanisms in achieving time-based fairness by using an analytical model. Using Jain's fairness index, optimal MAC parameters required in achieving maximum fairness between slow and fast stations are obtained. The impacts of these mechanisms on throughput of slow and fast stations are explored. We also consider the notion of proportional fairness in a multirate scenario and prove that it is equivalent to fair channel time allocation. Last, our investigation of an alternative fairness criterion also leads us to propose that the IEEE 802.11 MAC protocol should be redesigned with temporal fairness as a design objective in avoiding inefficiencies related to the performance anomaly.

85 citations

Proceedings ArticleDOI
26 May 2008
TL;DR: This paper proposes the min-max coalition-proof Nash equilibrium (MMCPNE) channel allocation scheme in the game, which is aiming to max the achieved date rates of communication links, and proposes several algorithms that enable the selfish players to converge to MMCPNE.
Abstract: Channel allocation was extensively investigated in the framework of cellular networks, but it was rarely studied in the wireless ad-hoc networks, especially in the multi-hop ad-hoc networks. In this paper, we study the competitive multi-radio channel allocation problem in multi-hop wireless networks in detail. We model the channel allocation problem as a static cooperative game, in which some players collaborate to achieve high date rate. We propose the min-max coalition-proof Nash equilibrium (MMCPNE) channel allocation scheme in the game, which is aiming to max the achieved date rates of communication links. We study the existence of MMCPNE and prove the necessary conditions for MMCPNE. Furthermore, we propose several algorithms that enable the selfish players to converge to MMCPNE. Simulation results show that MMCPNE outperforms CPNE and NE schemes in terms of achieved data rates of the multi-hop links due to cooperation gain.

85 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202315
202259
2021181
2020268
2019293
2018292