基于博弈论的空时频谱共享：动态接入与惩罚策略

doi:10.11959/j.issn.1000-436x.2023218

摘要/Abstract

摘要：

为了解决时空域频谱资源利用不充分的问题，针对异构网络中多个次用户通过感知空时频谱机会动态接入的场景，提出一种基于博弈论的可靠频谱共享策略。首先，次用户通过信道采样感知主用户的活跃程度，并进一步寻找适合的空时频谱机会。其中，每个次用户旨在寻求更多的频谱资源，须避免对主用户的通信质量造成损害。为此，次用户与主用户之间需进行个人效用的协商，以达到混合纳什均衡状态。当次用户发射功率异常时，其行为将被视为违规。然后，结合违规次数和网络中活动节点数，对次用户采用退避时间补偿算法进行惩罚。最后，仿真结果验证了引入惩罚机制的空时频谱机会共享策略的有效性。

关键词: 认知无线电网络, 空时频谱机会, 混合纳什均衡, 退避时间补偿

Abstract:

To tackle the challenge of inefficient utilization of spatiotemporal spectrum resources in heterogeneous networks, a reliable spectrum sharing strategy based on game theory was proposed for scenarios where multiple secondary users dynamically access through sensing spatiotemporal spectrum opportunities.Firstly, secondary users sensed the activity state of primary users through channel sampling and subsequently seek suitable spatiotemporal spectrum opportunities.Each secondary user aimed to access more spectrum resources while preventing quality degradation between primary users.Consequently, a negotiation of individual utilities between secondary and primary users was needed, in order to reach a mixed Nash equilibrium.When the secondary user's transmission power was abnormal, its behavior would be regarded as a violation.Then, a backoff time compensation algorithm was presented to penalize the secondary users, according to the number of violations and active nodes in the network.Finally, simulation results validate the effectiveness of the spatiotemporal spectrum opportunities sharing strategy with the penalty mechanism.

Key words: cognitive radio network, spatiotemporal spectrum opportunity, mixed Nash equilibrium, backoff time compensation

中图分类号:

TN929.5

牛阳阳, 尉志青, 冯志勇. 基于博弈论的空时频谱共享：动态接入与惩罚策略[J]. 通信学报, 2023, 44(12): 28-38.

Yangyang NIU, Zhiqing WEI, Zhiyong FENG. Space-time spectrum sharing based on game theory:dynamic access and penalty strategy[J]. Journal on Communications, 2023, 44(12): 28-38.

图/表 10

图1

表1

黑区中PU与SU的效用函数"

效用函数	PU（捕获SU）	PU（未捕获SU）
SU（欺骗）	$- T M_{1} p_{0}, 0$	$K_{τ} (1 - p_{0}) \frac{\log (1 + \frac{\frac{P_{s}}{r^{α}}}{\frac{P_{0}}{l^{α}} + σ_{ω}^{2}})}{\log (1 + \frac{\frac{P_{s}}{r^{α}}}{σ_{ω}^{2}})} - T M_{1} p_{0}, - c_{p} M_{1}$
SU（未欺骗）	$- T M_{1} p_{0}, - c_{s}$	0，0

表1

表2

灰区中PU与SU的效用函数"

效用函数	PU（捕获SU）	PU（未捕获SU）
SU（欺骗）	$- T M_{2} p_{0}, 0$	$K_{τ} (1 - p_{0}) \frac{\log (1 + \frac{\frac{P_{s}}{r^{α_{1}}}}{\frac{P_{0}}{l^{α_{1}}} + σ_{ω}^{2}})}{\log (1 + \frac{\frac{P_{s}}{r^{α_{1}}}}{σ_{ω}^{2}})} - T M_{2} p_{0}, - c_{p} M_{2}$
SU（未欺骗）	$- T M_{2} p_{0}, 0$	0，0

表2

图2

表3

图3

图4

图5

图6

图7

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参数名称	参数值
主用户数M /个	4
次用户数N /个	10
信道数c /个	15
每个用户接入的带宽/MHz	30
基本惩罚时间T /符号时间	2
频谱检测时间τ/符号时间	1
采样点数K	1 000
小区半径/m	500
MATLAB仿真版本	R2023a