Bio-Inspired Resource Allocation for Relay-Aided Device-to-Device Communications

The Device-to-Device (D2D) communication principle is a key enabler of direct localized communication between mobile nodes and is expected to propel a plethora of novel multimedia services. However, even though it offers a wide set of capabilities mainly due to the proximity and resource reuse gains, interference must be carefully controlled to maximize the achievable rate for coexisting cellular and D2D users. The scope of this work is to provide an interference-aware real-time resource allocation (RA) framework for relay-aided D2D communications that underlay cellular networks. The main objective is to maximize the overall network throughput by guaranteeing a minimum rate threshold for cellular and D2D links. To this direction, genetic algorithms (GAs) are proven to be powerful and versatile methodologies that account for not only enhanced performance but also reduced computational complexity in emerging wireless networks. Numerical investigations highlight the performance gains compared to baseline RA methods and especially in highly dense scenarios which will be the case in future 5G networks.Comment: 6 pages, 6 figure

A DYNAMIC SPECTRUM ACCESS OPTIMIZATION MODEL FOR COGNITIVE RADIO WIRELESS SENSOR NETWORK

The availability of low cost and tiny sensor devices have resulted in increased adoption of wireless sensor network (WSN) in various industries and organization. The WSN is expected to play a significant role in future internet based application services. WSN has been adopted in healthcare, disaster management, environment monitoring and so on. The low-cost availability of smart devices has led to increased use of wireless devices such as Bluetooth, Wi-Fi etc. Therefore, cognitive radio network plays a significant role in handling spectrum efficiently. The emerging internet access technology such as 4G and 5G network which is expected to come in near future is going to make cognitive spectrum access more challenging. The existing cognitive radio based WSN is not efficient in utilizing spectrum. They induce high collision due to interference and improper channel state information. To address, this work present an efficient distributed opportunistic spectrum access for wireless sensor network. The channel availability of likelihood distribution is computed using continuous-time Markov chain considering primary transmitting users temporal channel usage channel pattern and spatial distribution. The simulation outcome shows the proposed model achieves significant performance improvement over existing model. The proposed model improves the overall spectrum efficiency of cognitive radio wireless sensor network in terms of throughput, packet transmission and collision