Wideband Self-Adaptive RF Cancellation Circuit for Full-Duplex Radio: Operating Principle and Measurements

This paper presents a novel RF circuit architecture for self-interference cancellation in inband full-duplex radio transceivers. The developed canceller is able to provide wideband cancellation with waveform bandwidths in the order of 100 MHz or beyond and contains also self-adaptive or self-healing features enabling automatic tracking of time-varying self-interference channel characteristics. In addition to architecture and operating principle descriptions, we also provide actual RF measurements at 2.4 GHz ISM band demonstrating the achievable cancellation levels with different bandwidths and when operating in different antenna configurations and under low-cost highly nonlinear power amplifier. In a very challenging example with a 100 MHz waveform bandwidth, around 41 dB total cancellation is obtained while the corresponding cancellation figure is close to 60 dB with the more conventional 20 MHz carrier bandwidth. Also, efficient tracking in time-varying reflection scenarios is demonstrated.Comment: 7 pages, to be presented in 2015 IEEE 81st Vehicular Technology Conferenc

A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

Beam Based Stochastic Model of the Coverage Probability in 5G Millimeter Wave Systems

Communications using frequency bands in the millimeter-wave range can play a key role in future generations of mobile networks. By allowing large bandwidth allocations, high carrier frequencies will provide high data rates to support the ever-growing capacity demand. The prevailing challenge at high frequencies is the mitigation of large path loss and link blockage effects. Highly directional beams are expected to overcome this challenge. In this paper, we propose a stochastic model for characterizing beam coverage probability. The model takes into account both line-of-sight and first-order non-line-of-sight reflections. We model the scattering environment as a stochastic process and we derive an analytical expression of the coverage probability for any given beam. The results derived are validated numerically and compared with simulations to assess the accuracy of the model

Coverage prediction and optimization algorithms for indoor environments

A heuristic algorithm is developed for the prediction of indoor coverage. Measurements on one floor of an office building are performed to investigate propagation characteristics and validations with very limited additional tuning are performed on another floor of the same building and in three other buildings. The prediction method relies on the free-space loss model for every environment, this way intending to reduce the dependency of the model on the environment upon which the model is based, as is the case with many other models. The applicability of the algorithm to a wireless testbed network with fixed WiFi 802.11b/g nodes is discussed based on a site survey. The prediction algorithm can easily be implemented in network planning algorithms, as will be illustrated with a network reduction and a network optimization algorithm. We aim to provide an physically intuitive, yet accurate prediction of the path loss for different building types

Insights and approaches for low-complexity 5G small-cell base-station design for indoor dense networks

This paper investigates low-complexity approaches to small-cell base-station (SBS) design, suitable for future 5G millimeter-wave (mmWave) indoor deployments. Using large-scale antenna systems and high-bandwidth spectrum, such SBS can theoretically achieve the anticipated future data bandwidth demand of 10000 fold in the next 20 years. We look to exploit small cell distances to simplify SBS design, particularly considering dense indoor installations. We compare theoretical results, based on a link budget analysis, with the system simulation of a densely deployed indoor network using appropriate mmWave channel propagation conditions. The frequency diverse bands of 28 and 72 GHz of the mmWave spectrum are assumed in the analysis. We investigate the performance of low-complexity approaches using a minimal number of antennas at the base station and the user equipment. Using the appropriate power consumption models and the state-of-the-art sub-component power usage, we determine the total power consumption and the energy efficiency of such systems. With mmWave being typified nonline-of-sight communication, we further investigate and propose the use of direct sequence spread spectrum as a means to overcome this, and discuss the use of multipath detection and combining as a suitable mechanism to maximize link reliability