Large mmWave Research Articles

Reliability Enhancement for VR Delivery in Mobile-Edge Empowered Dual-Connectivity Sub-6 GHz and mmWave HetNets

The reliability of current virtual reality (VR) delivery is low due to the limited resources on VR head-mounted displays (HMDs) and the transmission rate bottleneck of sub-6 GHz networks. In this paper, we propose a dual-connectivity sub-6 GHz and mmWave heterogeneous network architecture empowered by mobile edge capability. The core idea of the proposed architecture is to utilize the complementary advantages of sub-6 GHz links and mmWave links to conduct a collaborative edge resource design, which aims to improve the reliability of VR delivery. From the perspective of stochastic geometry, we analyze the reliability of VR delivery and theoretically demonstrate that sub-6 GHz links can be used to enhance the reliability of VR delivery despite the large mmWave bandwidth. Based on our analytical work, we formulate a joint caching and computing optimization problem with the goal to maximize the reliability of VR delivery. By analyzing the coupling caching and computing strategies at HMDs, sub-6 GHz and mmWave base stations (BSs), we further transform the problem into a multiple-choice multi-dimension knapsack problem. A best-first branch and bound algorithm and a difference of convex programming algorithm are proposed to obtain the optimal and sub-optimal solution, respectively. Numerical simulations demonstrate the performance improvement using the proposed algorithms, and reveal that caching more monocular videos at sub-6 GHz BSs and more stereoscopic videos at mmWave BSs can improve the VR delivery reliability efficiently.

Stability Analysis of Simple and Online User Association Policies for Millimeter Wave Networks

In a millimeter wave (mmWave) network, user association– the process of deciding as to which base station (BS) a given user should associate with– is a crucial process, which affects the throughput and delay performance seen by users in the network and the amount of load at each BS. In the existing research literature, the stability region of a user association policy, i.e. , the set of user arrival rates for which the user association policy stabilizes the network, has not been analytically characterized for any user association policy for mmWave networks. In this paper, we study the user association problem in mmWave networks and compare the performances of four user association policies: Signal to Noise Ratio (SNR) based, Throughput based, Load based and Mixed. All these policies are simple, easy to implement, distributed, and online. We use a Continuous Time Markov Chain (CTMC) model and Lyapunov function techniques to analytically characterize the stability region of each of the above four user association policies; our analysis provides several insights into the performances of the policies. We also evaluate the performances of the above four user association policies in a large mmWave network, in which link qualities fluctuate with time and users are mobile, via detailed simulations. Our results show that the Throughput based policy outperforms the other three user association policies in terms of stability region as well as average throughput, average delay, fairness and energy efficiency performance.

Architecture and Circuit Choices for 5G Millimeter-Wave Beamforming Transceivers

As 5G takes advantage of the vast amount of available spectrum in the mmWave bands, system and circuit designers face new challenges to create efficient, high-performance phased array transceivers. This article covers scaled CMOS circuit and system tradeoffs for large mmWave power consumers including the PA, LO generation, and LO distribution, in the context of mobile link requirements and beamforming system architectures. We survey a selection of published mmWave transceivers relevant to 5G communications and provide insight into tradeoffs made in practice. Finally, we discuss the application of these concepts toward E-band 71-76 GHz circuit blocks in the Intel 22FFL FinFET process with measurement results.

Training Beam Sequence Design for Millimeter-Wave MIMO Systems: A POMDP Framework

In this paper, adaptive training beam sequence design for efficient channel estimation in large millimeter-wave(mmWave) multiple-input multiple-output (MIMO) channels is considered. By exploiting the sparsity in large mmWave MIMO channels and imposing a Markovian random walk assumption on the movement of the receiver and reflection clusters, the adaptive training beam sequence design and channel estimation problem is formulated as a partially observableMarkov decision process (POMDP) problem that finds non-zero bins in a two-dimensional grid. Under the proposed POMDP framework, optimal and suboptimal adaptive training beam sequence design policies are derived. Furthermore, a very fast suboptimal greedy algorithm is developed based on a newly proposed reduced sufficient statistic to make the computational complexity of the proposed algorithm low to a level for practical implementation. Numerical results are provided to evaluate the performance of the proposed training beam design method. Numerical results show that the proposed training beam sequence design algorithms yield good performance.