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Channel ranking algorithm and ranking error bounds: A two channel case

机译:渠道排名算法和排名误差范围:两个渠道的情况

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In this paper, we establish a channel ranking strategy for wireless sensor networks (WSN) in the presence of WLAN interference. The packet delivery ratio (PDR) of a sensor link is the performance metric used for channel ranking. The PDR is defined as a function of the signal-to-interference-and-noise-ratio (SINR) at the sensor and the time domain transmission characteristics of the interferer that is, the activity factor and the traffic pattern. The PDR is estimated at the sensor by using spectrum measurements. When the channel bandwidth of the interferer is large and the measurement time is also limited, the traffic pattern cannot be satisfactorily predicted for each measured channel. Because of that it is proposed to utilize Poisson and periodic traffic patterns to obtain bounds on the performance of channel ranking. Given the channel measurement time upper and lower bounds on the ranking error probability are calculated by using Poisson and periodic traffic patterns respectively. Even though the traffic pattern of WLAN interference is usually modeled with phase-type (PH) distributions, the periodic and the Poisson traffic patterns allow us to bypass the traffic pattern estimation process and relatively rank the channels based on their SINR and activity factor estimates.
机译:在本文中,我们建立了存在WLAN干扰的无线传感器网络(WSN)的信道排名策略。传感器链路的数据包传输率(PDR)是用于信道排名的性能指标。将PDR定义为传感器处的信号干扰噪声比(SINR)和干扰源的时域传输特性(即活动因子和流量模式)的函数。通过使用频谱测量在传感器处估计PDR。当干扰源的信道带宽很大并且测量时间也受到限制时,无法为每个测量的信道令人满意地预测流量模式。因此,提出利用泊松和周期性话务量模式来获得信道排序性能的界限。在给定信道测量时间的情况下,分别通过使用泊松和周期性业务量模式来计算排序错误概率的上限和下限。尽管通常使用相位类型(PH)分布对WLAN干扰的流量模式进行建模,但周期性流量和泊松流量模式仍使我们能够绕过流量模式估计过程,并根据其SINR和活动因子估计值对信道进行相对排名。

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