Ssajjabbi Muwonge Bernard, Pei Tingrui, Sansa Otim Julianne, Mayambala Fred
School of Computer Science, Xiangtan University, Xiangtan 411105, China.
Key Laboratory of Hunan Province for Internet of Things and Information Security, Xiangtan 411105, China.
Sensors (Basel). 2020 Aug 31;20(17):4907. doi: 10.3390/s20174907.
To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate.
为了在节省可用的有限电力和能源资源的同时，最大化主要用户与认知物联网（IoT）用户之间的有限频谱，有必要优化网络资源。然而，单独研究传输速率、传输功率或传输延迟的影响相当复杂，而除了信道选择变量之外，同时考虑这三个变量会使复杂性进一步加剧，因为这会产生一个非凸问题。我们的目标是在误码率（BER）、干扰和其他信道限制的约束下，联合优化三个主要变量：传输功率、速率和延迟。我们分析了总功率、速率和延迟如何随数据包大小、网络大小、BER和干扰而变化。使用分支切割多面体方法解决由此产生的问题。为了模拟结果，我们使用MATLAB以及最先进的BARON软件。可以观察到，数据包大小的增加通常会导致总速率、总功率和总传输延迟的增加。还可以观察到，增加信道上的次要用户数量通常会导致功率、延迟和速率的增加。
