Favorable Propagation Properties Research Articles

Favorable Propagation for Massive MIMO With Circular and Cylindrical Antenna Arrays

Massive MIMO systems with uniform circular and cylindrical antenna arrays are studied. Favorable propagation property is rigorously shown to hold asymptotically in LOS environment for a fixed antenna spacing and under some mild conditions. The analysis is based on a novel method using a Bessel function expansion, a new bounding technique and a simplified representation of inter-user interference for array geometries obeying Kronecker structure.

Online Trajectory and Radio Resource Optimization of Cache-Enabled UAV Wireless Networks With Content and Energy Recharging

Recently, unmanned aerial vehicle (UAV)-assisted wireless communication technology has been proposed to exploit the favorable propagation property and flexibility of air-to-ground channels to support content-centric caching and enhance wireless network capacity. In this article, we propose an online UAV-assisted wireless caching design via jointly optimizing UAV trajectory, transmission power and caching content scheduling. Specifically, we formulate the joint optimization of online UAV trajectory and caching content delivery as an infinite-horizon ergodic Markov Decision Process (MDP) problem to obtain a QoE-optimal solution based on the concept of request queues in wireless caching networks. By exploiting the fluid approximation approach, we first derive an optimal control policy from an approximated Bellman equation. Based on this, an actor-critic based online reinforcement learning algorithm is proposed to solve the problem. Finally, simulation results are provided to show that the proposed solution can achieve significant gain over the existing baselines.

Performance of a dense urban massive MIMO network from a simulated ray-based channel

Massive MIMO network deployments are expected to be a key feature of the upcoming 5G communication systems. Such networks are able to achieve a high level of channel quality and can simultaneously serve multiple users with the same resources. In this paper, realistic massive MIMO channels are evaluated both in single and multi-cell environments. The favorable propagation property is evaluated in the single-cell scenario and provides perspectives on the minimal criteria required to achieve such conditions. The dense multi-cell urban scenario provides a comparison between linear, planar, circular, and cylindrical arrays to evaluate a large-scale multi-cell massive MIMO network. The system-level performance is predicted using two different kinds of channel models. First, a ray-based deterministic tool is utilized in a real North American city environment. Second, an independent and identically distributed (i.i.d.) Rayleigh fading channel model is considered, as often used in previously published massive MIMO studies. The analysis is conducted in a 16-macro-cell network with both randomly distributed outdoor and indoor users. It is shown that the physical array properties like the shape and configuration have a large impact on the throughput statistics. Although the system-level performance with i.i.d. Rayleigh fading can be close to the deterministic prediction in some situations (e.g., with large linear arrays), significant differences are noticed when considering other types of arrays. The differences in the performance of the various arrays utilizing the exact same network parameters and the same number of total antenna elements provide insights into the selection of these physical parameters for upcoming 5G networks.

Overlapping User Grouping in IoT Oriented Massive MIMO Systems

This paper considers network capacity and user coverage improvement in Internet of Things (IoT)-oriented massive MIMO systems. In the literature, user grouping approaches have been used in massive MIMO to improve the network capacity, where users are generally divided into non-overlapping groups, and those users with less favorable channel conditions are dropped for capacity optimization. As a result, users may suffer from unpredicted interruptions and delays, even long time disconnection from the network. Moreover, non-overlapping user grouping also leads to unnecessary resource waste. As an effort to overcome these limitations, in this paper, we introduce the concept of overlapping user grouping by exploiting the favorable propagation property in massive MIMO. More specifically, we propose two new user grouping approaches. First, we present a greedy search-based user grouping method by allowing overlapping among the selected subgroups. Second, we introduce a new channel similarity measure, and develop a low complexity overlapping user grouping approach based on the spectral clustering algorithm in machine learning. Both the theoretical and numerical results demonstrate that: overlapping user grouping can achieve much higher network capacity, and can ensure that at any given time, each IoT device will be served in at least one subgroup.

Efficient transceiver design for large-scale antenna systems

We present linear transceiver design strategies for large-scale multiple-input multiple-output downlink systems when the user nodes have multiple receive antennas, and they receive multiple streams. First, we propose a matched-filtering-based optimal power allocation method using the sum-rate maximization criterion and utilizing the favorable propagation property of large-scale antenna systems. In uncorrelated transmit antennas, we observe that the effective channel can be represented by the receive antenna correlation matrix. Motivated by this observation, we also propose a suboptimal two-step power allocation method in which each user node is equipped with two receive antennas to reduce the computational complexity of the optimum power allocation method. Compared with the optimum power allocation method, the proposed two-step method reduces the dimensions of the bisection search space while achieving essentially the same level of sum rate.