Shu-Ping Yeh

Capacity and coverage enhancement in heterogeneous networks

Disruptive innovations in mobile broadband system design are required to help network providers meet the exponential growth in mobile traffic demand with relatively flat revenues per bit. Heterogeneous network architecture is one of the most promising low-cost approaches to provide significant areal capacity gain and indoor coverage improvement. In this introductory article, we provide a brief overview of heterogeneous network architectures comprising hierarchical multitier multiple radio access technologies (RAT) deployments based on newer infrastructure elements. We begin with presenting possible deployment scenarios of heterogeneous networks to better illustrate the concepts of multitier and multi-RAT. We then focus on multitier deployments with single RAT and investigate the challenges associated with enabling single frequency reuse across tiers. Based on the spectrum usage, heterogeneous networks can be categorized into single carrier usage, where all devices within the network share the same spectrum, and distinct carrier usage, where different types of devices are allocated separate spectra. For single carrier usage, we show that interference management schemes are critical for reducing the resulting cross-tier interference, and present several techniques that provide significant capacity and coverage improvements. The article also describes industry trends, standardization efforts, and future research directions in this rich area of investigation.

Intelligent access network selection in converged multi-radio heterogeneous networks

Heterogeneous multi-radio networks are emerging network architectures that comprise hierarchical deployments of increasingly smaller cells. In these deployments, each user device may employ multiple radio access technologies to communicate with network infrastructure. With the growing numbers of such multi-radio consumer devices, mobile network operators seek to leverage spectrum across diverse radio technologies, thus boosting capacity and enhancing quality of service. In this article, we review major challenges in delivering uniform connectivity and service experience to converged multiradio heterogeneous deployments. We envision that multiple radios and associated device/infrastructure intelligence for their efficient use will become a fundamental characteristic of future 5G technologies, where the distributed unlicensed-band network (e.g., WiFi) may take advantage of the centralized control function residing in the cellular network (e.g., 3GPP LTE). Illustrating several available architectural choices for integrating WiFi and LTE networks, we specifically focus on interworking within the radio access network and detail feasible options for intelligent access network selection. Both network- and user-centric approaches are considered, wherein the control rests with the network or the user. In particular, our system-level simulation results indicate that load-aware usercentric schemes, which augment SNR measurements with additional information about network loading, could improve the performance of conventional WiFi-preferred solutions based on minimum SNR threshold. Comparison with more advanced network-controlled schemes has also been completed to confirm attractive practical benefits of distributed user-centric algorithms. Building on extensive system-wide simulation data, we also propose novel analytical space-time methodology for assisted network selection capturing user traffic dynamics together with spatial randomness of multi-radio heterogeneous networks.

Multi-radio heterogeneous networks: Architectures and performance

It is well-known that next generation (5G) wireless networks will need to provide orders of magnitude more capacity to address the predicted growth in mobile traffic demand, as well as support reliable connectivity for billions of diverse devices, which comprise the “Internet of Things.” While the industry is focused on a concerted effort to improve capacity of cellular networks, operators are increasingly using WiFi technology over un-licensed spectrum to relieve congestion in their networks. This paper argues that the trend towards integrated use of multiple radio access technologies (RATs) and networks, such as WiFi, will be essential for addressing the challenges faced by future 5G networks. In particular we expect that joint use of multiple RATs can yield beyond additive gains in user connectivity experience by exploiting the rich multi-dimensional diversity (e.g., spatial, temporal, frequency, load, etc.) available across multiple radio networks. We investigate such benefits through a case study on integrating WiFi with 3GPP heterogeneous networks. Our results show that intelligent integration of WiFi/3GPP radio networks can yield an additional 2-3x gains in system capacity and user quality of service, beyond what is achievable from independent use of both networks.

Cooperative Radio Resource Management in Heterogeneous Cloud Radio Access Networks

Responding to the unprecedented challenges imposed by the 5G communications ecosystem, emerging heterogeneous network architectures allow for improved integration between multiple radio access technologies. When combined with advanced cloud infrastructures, they bring to life a novel paradigm of heterogeneous cloud radio access network (H-CRAN). The novel H-CRAN architecture opens door to improved network-wide management, including coordinated cross-cell radio resource allocation. In this paper, emphasizing the lack of theoretical performance analysis, we specifically address the problem of cooperative radio resource management in H-CRAN by providing a comprehensive mathematical methodology for its real-time performance optimization. Our approach enables flexible balance between throughput and fairness metrics, as may be desired by the network operator, and demonstrates attractive benefits when compared against the state-of-the-art multiradio resource allocation strategies. The resulting algorithms are suitable for efficient online implementation, which principal feasibility is confirmed by our proof-of-concept prototype.

Capturing Spatial Randomness of Heterogeneous Cellular/WLAN Deployments With Dynamic Traffic

As fourth generation communications technology is already being deployed, research efforts are now being shifted to what comes beyond state-of-the-art wireless systems. Driven by the anticipated acceleration in mobile traffic demand, the wireless industry is specifically focused on improving capacity and coverage of current networks through aggressive reuse of the cellular spectrum. Together with deploying an increasingly dense overlay tier of smaller cells, mobile network operators are beginning to rely on unlicensed-band WLAN technologies to leverage additional spectrum and relieve congestion on their networks. Consequently, the emerging vision of heterogeneous networks exploits the potential of a diverse range of devices requiring connectivity at different scales to augment available system capacity and improve the user connectivity experience. In this paper, we seek to meet this important trend with our novel integrated methodology for assisted (managed) radio network selection capturing spatial randomness of converged cellular/WLAN deployments together with dynamic uplink traffic from their users. To this end, we employ tools coming from stochastic geometry to characterize performance of macro and pico cellular networks, as well as WLAN, mindful of user experience and targeting intelligent network selection/assignment. We complement our analysis with system-level simulations providing deeper insights into the behavior of future heterogeneous deployments.

Power control based interference mitigation in multi-tier networks

Significant areal capacity gains and improved cellular coverage can be achieved by hierarchical deployment of Femto Access Points (FAP) over an existing cellular network. However, the introduction of FAPs, which use the same spectrum as the cellular network, can cause severe interference to network and drive users into outage. In order to resolve this issue, advanced interference mitigation (IM) techniques should be applied in multi-tier networks. In this paper, we design and evaluate power control based IM algorithms in cellular systems with femtocell overlay. Simulation results show that FAP power back-off helps lower macro-user outage probability at the cost of femto-user rate reduction. For control channels with low data rate requirement, FAP power control can be a potential IM solution.

Characterizing performance of load-aware network selection in multi-radio (WiFi/LTE) heterogeneous networks

In this paper, we consider the problem of network selection between different radio access technologies (RATs) deployed as part of an operator managed multi-RAT heterogeneous network. An urban deployment scenario is studied where WiFi small cells are overlaid on top of the 3GPP LTE network. We assume limited cooperation across the multi-RAT network and emphasize user-centric network selection algorithms to minimize feedback overhead and to better account for user preferences. Specifically, we investigate schemes that rely on network loading information with suitable adaptation of hysteresis mechanisms and compare them with WiFi-preferred schemes that only account for signal strength measurements. We also benchmark the performance of load-aware schemes against conventional cell-range extension methods that use network-wide optimization to offload users to small cells. The results of our system-level performance evaluation show that load-aware user-centric schemes can provide improved performance compared to the WiFi-preferred schemes and may even outperform network-based cell-range extension schemes under some conditions.

Utility-based radio link assignment in multi-radio heterogeneous networks

Techniques for coordinated use of WiFi and LTE radio links are developed for operator-managed multi-radio heterogeneous networks. In particular, we consider deployments based on integrated small cells with co-located WiFi and LTE interfaces, which allow for tighter coordination between the two interfaces especially when used together with WiFi/LTE capable client devices. The paper develops a utility based framework which optimizes the partitioning of users between WiFi and LTE to improve the aggregate per-cell utility. The resulting link assignment framework is applied to take advantage of the orthogonal WiFi carrier to mitigate cross-tier LTE interference between macro-cells and small-cells. Results show that this technique not only improves system capacity and coverage beyond what is achievable with uncoordinated use of WiFi and LTE, but also preserves macro-cell throughput by reducing the need for macro-cells to mute their transmissions in order to avoid cross-tier interference. We also apply the utility-based assignment framework to improve the on-time throughput across users, which measures the average data rate delivered to a user before its delay deadline. This is an important metric to characterize the quality-of-service achievable for transmitting delay sensitive traffic, such as real-time voice and video. Our results show that accounting for delay sensitivity in the optimization can improve the number of users achieving target on-time throughput by up to 3x, when compared with un-coordinated use of WiFi and LTE interfaces.

Analysis of human-body blockage in urban millimeter-wave cellular communications

The use of extremely high frequency (EHF) or millimeter-wave (mmWave) band has attracted significant attention for the next generation wireless access networks. As demonstrated by recent measurements, mmWave frequencies render themselves quite sensitive to “blocking” caused by obstacles like foliage, humans, vehicles, etc. However, there is a dearth of analytical models for characterizing such blocking and the consequent effect on the signal reliability. In this paper, we propose a novel, general, and tractable model for characterizing the blocking caused by humans (assuming them to be randomly located in the environment) to mmWave propagation as a function of system parameters like transmitter-receiver locations and dimensions, as well as density and dimensions of humans. Moreover, the proposed model is validated using a ray-launcher tool. Utilizing the proposed model, the blockage probability is shown to increase with human density and separation between the transmitter-receiver pair. Furthermore, the developed analysis is shown to demonstrate the existence of a transmitter antenna height that maximizes the received signal strength, which in turn is a function of the transmitter-receiver distance and their dimensions.

Proportional Fair Traffic Splitting and Aggregation in Heterogeneous Wireless Networks

Traffic load balancing and resource allocation is set to play a crucial role in leveraging the dense and increasingly heterogeneous deployment of multiradio wireless networks. Traffic aggregation across different access points (APs)/radio access technologies (RATs) has become an important feature of recently introduced cellular standards on LTE dual connectivity and LTE-WLAN aggregation (LWA). Low complexity traffic splitting solutions for scenarios where the APs are not necessarily collocated are of great interest for operators. In this letter, we consider a scenario, where traffic for each user may be split across macrocell and an LTE or WiFi small cells connected by nonideal backhaul links, and develop a closed form solution for optimal aggregation accounting for the backhaul delay. The optimal solution lends itself to a “water-filling” based interpretation, where the fraction of users traffic sent over macrocell is proportional to ratio of users peak capacity on that macrocell and its throughput on the small cell. Using comprehensive system level simulations, the developed optimal solution is shown to provide substantial edge and median throughput gain over algorithms representative of current 3GPP-WLAN interworking solutions. The achievable performance benefits hold promise for operators expecting to introduce aggregation solutions with their existing WLAN deployments.