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Joint Incentive and Resource Allocation Design for User Provided Network Under 5G Integrated Access and Backhaul Networks

机译:用户提供的联合激励和资源分配设计为5G集成访问和回程网络提供网络

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User provided network (UPN) allows a user with high channel quality to share the network access for users with poor channel quality. As a result, both the quality of experience and efficiency of network resource can be improved by UPN. However, the success of UPN relies heavily on the willingness of users to participate in sharing, so the design of incentive mechanisms is critical for UPN. In this paper, the UPN formed by D2D links under 5G integrated access and backhaul (IAB) networks is considered. In IAB networks, both access and backhaul links use wireless transmissions and dynamically share all the spectrum resources. Thus, the resource allocation for all the links also has a great impact on the UPN efficiency. To this end, a novel joint incentive and resource allocation design is explored. More specifically, considering the fairness between users, a Nash bargaining problem as a cooperative game is formulated by considering the user utility, the sensitivity of battery energy, the incentive compensation, and the limitation of network resources. To achieve the optimal Nash bargaining solution, a centralized algorithm is first designed, in which all the user information is collected by the operator for conducting centralized optimization. Thus, the centralized algorithm leads to a privacy problem. To this end, a distributed algorithm is developed to decompose the primal problem into subproblems for the operator and each user. By passing intermediate parameters between users and iterative execution of subproblems, the solution of the distributed algorithm is proved to converge to the optimal solution of the centralized algorithm. Extensive numerical results have been conducted to show that our design can effectively improve both the user experience and network throughput, i.e., operator's revenue.
机译:用户提供的网络(UPN)允许用户具有高通道质量的用户来共享具有较差信道质量的用户的网络访问。结果,通过UPN可以提高网络资源的经验质量和效率。然而,UPN的成功严重依赖于用户参与共享的意愿,因此激励机制的设计对于UPN至关重要。在本文中,考虑了由5G集成访问和回程(IAB)网络下的D2D链路形成的UPN。在IAB网络中,访问和回程链路都使用无线传输并动态共享所有频谱资源。因此,所有链路的资源分配也对UPN效率产生了很大的影响。为此,探讨了一种新的联合奖励和资源分配设计。更具体地,考虑用户之间的公平,通过考虑用户实用性,电池能量,激励补偿和网络资源限制来制定作为合作游戏的纳什议价问题。为了实现最佳的纳什讨价还价解决方案,首先设计一种集中式算法,其中由操作者收集所有用户信息以进行集中式优化。因此,集中算法导致隐私问题。为此,开发了一种分布式算法以将原始问题分解为运营商和每个用户的子问题。通过在用户之间传递中间参数和子问题的迭代执行,证明分布式算法的解融合到集中算法的最佳解决方案。已经进行了广泛的数值结果表明我们的设计可以有效地改善用户体验和网络吞吐量,即操作员的收入。

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