Downlink massive full dimension-multiple input multiple output downlink beamforming analysis at 3.5 GHz using coordinated ON-OFF switching

The long-term evolution and advancement (LTE-A) of the 5G wireless network depends critically on energy consumption. Many existing solutions focus on limiting power constraints and consequently system coverage. So, improving the antenna array elements of the base station (BS) can solve this issue. In this paper, introduce a coordinated ON-OFF switching method in the massive full dimensional multiple input multiple output (massive-FD-MIMO) system. It enhances the radiation pattern of the antenna array element by adjusting the angular power spectra at the BS. By the way, it allows to select the minimum number of antennas for effective beamforming toward specific user equipment’s (UEs). In this context, part of antenna element should be active mode and remining should be sleep mode at the time of signal beamforming. The multipath spatial profiles are decided the beamforming frequency band with minimize energy consumption. As part of the method, we used a conjugated beamforming with power optimization scheme to determine the individual antenna potential and fading channel condition, power optimization is performed. This method quality of service, reliability, energy consumption and data rate can all be evaluated by experimenting with different-sized antenna arrays such as 16×16, 32×32, 64×64 and 128×128

Heterogeneous cyber-physical network coexistence through interference contribution rate and uplink power control algorithm (ICR-UPCA) in 6G edge cells

Optimizing power control for interference mitigation at the network cell edge is pivotal in enhancing capacity within a heterogeneous cyber-physical infrastructure, such as smart cities, manufacturing, healthcare, energy grids, transportation, and agriculture, among others. In this paper, we consider the intricate dynamics of Internet of Things (IoT) 5/6G edge users, with a particular focus on the Interference Contribution Rate (ICR), where macro and femtocells are critical network infrastructures. Existing approaches has drawbacks such as computational complexity, overhead, and co-channel interference, among others. However, to fully address interference challenges from the coexistence of diverse network hierarchies, preserving the Quality of Service for femtocell users is prioritized. The paper concurrently enhances the handoff mechanism of cell edge users in the macro cell network. A two-tier heterogeneous network (HetNet) is utilized to initially assess the contribution of edge user equipment (UE) to interference levels during its active state while quantifying it as ICR. Game theory is used to formulate a cohesive model for the coexistence of macro cell (MUE) and femtocell users (FUE). ICR-based uplink power control and reference signal received quality (RSRQ)-based handoff algorithms are deployed to regulate interference levels and enhance the Signal-to-Interference-Noise Ratio (SINR) of the MUE at the cell edge. This is achieved through coordinated transmit power adjustments by both user types. Results indicate a 6.67 % channel capacity loss (interference tolerance) by the FUE, leading to a 12.5 % improvement, translating to approximately 4 Mbps and 1 Mbps channel enhancements, respectively. The MUE and FUE can effectively coordinate power control with minimal overhead, accepting compromises in network channel quality. This approach facilitates improved MUE data access rates while ensuring the preservation of FUE. We show that interference is successfully mitigated through power control in heterogeneous networks with lower computational complexity