Wireless Information and Power Transfer in Full-Duplex Systems with Massive Antenna Arrays

We consider a multiuser wireless system with a full-duplex hybrid access point (HAP) that transmits to a set of users in the downlink channel, while receiving data from a set of energy-constrained sensors in the uplink channel. We assume that the HAP is equipped with a massive antenna array, while all users and sensor nodes have a single antenna. We adopt a time-switching protocol where in the first phase, sensors are powered through wireless energy transfer from HAP and HAP estimates the downlink channel of the users. In the second phase, sensors use the harvested energy to transmit to the HAP. The downlink-uplink sum-rate region is obtained by solving downlink sum-rate maximization problem under a constraint on uplink sum-rate. Moreover, assuming perfect and imperfect channel state information, we derive expressions for the achievable uplink and downlink rates in the large-antenna limit and approximate results that hold for any finite number of antennas. Based on these analytical results, we obtain the power-scaling law and analyze the effect of the number of antennas on the cancellation of intra-user interference and the self-interference.Comment: Accepted for the IEEE International Conference on Communications (ICC 2017

Survey on encode biometric data for transmission in wireless communication networks

The aim of this research survey is to review an enhanced model supported by artificial intelligence to encode biometric data for transmission in wireless communication networks can be tricky as performance decreases with increasing size due to interference, especially if channels and network topology are not selected carefully beforehand. Additionally, network dissociations may occur easily if crucial links fail as redundancy is neglected for signal transmission. Therefore, we present several algorithms and its implementation which addresses this problem by finding a network topology and channel assignment that minimizes interference and thus allows a deployment to increase its throughput performance by utilizing more bandwidth in the local spectrum by reducing coverage as well as connectivity issues in multiple AI-based techniques. Our evaluation survey shows an increase in throughput performance of up to multiple times or more compared to a baseline scenario where an optimization has not taken place and only one channel for the whole network is used with AI-based techniques. Furthermore, our solution also provides a robust signal transmission which tackles the issue of network partition for coverage and for single link failures by using airborne wireless network. The highest end-to-end connectivity stands at 10 Mbps data rate with a maximum propagation distance of several kilometers. The transmission in wireless network coverage depicted with several signal transmission data rate with 10 Mbps as it has lowest coverage issue with moderate range of propagation distance using enhanced model to encode biometric data for transmission in wireless communication

Joint Power and Time Allocation in Full-Duplex Wireless Powered Communication Networks

We consider a full-duplex wireless powered communication network (WPCN) with one hybrid access point (H-AP) and a set of distributed users, where downlink wireless energy broadcasting is employed at H-AP and at the same time, uplink wireless information transmission takes place at users in a time-division multiple access manner. We extend proportional fair scheduler to this category of network when dealing with "doubly near-far problem," where users far away from H-AP achieve low throughput but suffer from both low harvested energy and high data transmission power consumption. We jointly optimize power and time allocation for each user to achieve proportional fairness while controlling the energy consumption offset for network to a low level. By using optimization techniques, the optimal transmit power and transmission time for users are obtained via proposed algorithm. Simulation results confirm the positive effect on improving the fairness metric and reducing energy consumption offset for network