Chung Ha Koh

Bio: Chung Ha Koh is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Channel state information & Queueing theory. The author has an hindex of 3, co-authored 3 publications receiving 94 citations.

A 25 Gb/s(/km 2 ) urban wireless network beyond IMT-advanced

Abstract: In this article we present a survey on the technical challenges of future radio access networks beyond LTE-Advanced, which could offer very high average area throughput to support a huge demand for data traffic and high user density with energy-efficient operation. We highlight various potential enabling technologies and architectures to support the aggressive goal of average area throughput 25 Gb/s/km2 in beyond IMT-Advanced systems. Specifically, we discuss the challenges and solutions from the controlling/ processing perspective, the radio resource management perspective, and the physical layer perspective for dense urban cell deployment. Using various advanced technologies such as interference mitigation techniques, MIMO, and cooperative communications as well as cross-layer self-organizing networks, we show that future urban wireless networks could potentially offer high-quality mobile services and offer an experience similar to the wired Internet.

Tradeoff analysis of delay-power-CSIT quality of generalized dynamic backpressure algorithm for energy efficient OFDM systems

Abstract: In this paper, we analyze the fundamental power-delay tradeoff in point-to-point OFDM systems under imperfect channel state information quality and non-ideal circuit power. We consider a family of generalized dynamic backpressure (GDBP) algorithms parameterized by α which determines the relative importance of the system delay. The transmitter determines the rate and power control actions based on the instantaneous channel state information (CSIT) and the queue state information (QSI). We exploit a general fluid queue dynamics using a continuous time dynamic equation. Using the sample-path approach and renewal theory, we decompose the average delay in terms of multiple unfinished works along a sample path, and derive an upper bound on the average delay under the GDBP power control, which is asymptotically accurate at small delay regime. We show that despite imperfect CSIT quality and non-ideal circuit power, the average power (P) of the GDBP policy scales with delay (D) as P = O(Dexp(1/D)) at small delay regime. The impact of CSIT quality and circuit power appears as the coefficients of the scaling law.

Delay-power tradeoff of max queue-weighted (MWQ) power control for wireless systems with limited renewable energy storage

Abstract: In this paper, we analyze the fundamental power-delay tradeoff in point-to-point wireless communication systems with renewable energy source. We consider the max queue-weighted (MWQ) algorithm, where the transmitter determines the rate and power control actions based on the instantaneous channel state information (CSI), the data queue state information (DQSI) and renewable energy storage information (RESI). We exploit a general fluid dynamics of the data queue and renewable energy storage buffer using continuous time dynamic equations. Using the sample-path approach and renewal theory, we decompose the average delay in terms of multiple unfinished works along a sample path, and obtain bounds for the average delay and AC power consumption under the MWQ algorithm, which are asymptotically tight at small delay regime. We show that despite the randomness of the renewable energy arrival and energy buffer size, the average AC power (P) of the MWQ policy is given by P = O(D exp(1/D)) at small delay D regime. We also quantify the impacts of the renewable energy storage size in the scaling coefficient.

Joint Precoding and Multivariate Backhaul Compression for the Downlink of Cloud Radio Access Networks

Abstract: This work studies the joint design of precoding and backhaul compression strategies for the downlink of cloud radio access networks. In these systems, a central encoder is connected to multiple multi-antenna base stations (BSs) via finite-capacity backhaul links. At the central encoder, precoding is followed by compression in order to produce the rate-limited bit streams delivered to each BS over the corresponding backhaul link. In current state-of-the-art approaches, the signals intended for different BSs are compressed independently. In contrast, this work proposes to leverage joint compression, also referred to as multivariate compression, of the signals of different BSs in order to better control the effect of the additive quantization noises at the mobile stations (MSs). The problem of maximizing the weighted sum-rate with respect to both the precoding matrix and the joint correlation matrix of the quantization noises is formulated subject to power and backhaul capacity constraints. An iterative algorithm is proposed that achieves a stationary point of the problem. Moreover, in order to enable the practical implementation of multivariate compression across BSs, a novel architecture is proposed based on successive steps of minimum mean-squared error (MMSE) estimation and per-BS compression. Robust design with respect to imperfect channel state information is also discussed. From numerical results, it is confirmed that the proposed joint precoding and compression strategy outperforms conventional approaches based on the separate design of precoding and compression or independent compression across the BSs.

Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks

Abstract: With years of tremendous traffic and energy consumption growth, green radio has been valued not only for theoretical research interests but also for the operational expenditure reduction and the sustainable development of wireless communications. Fundamental green tradeoffs, served as an important framework for analysis, include four basic relationships: 1) spectrum efficiency versus energy efficiency; 2) deployment efficiency versus energy efficiency; 3) delay versus power; and 4) bandwidth versus power. In this paper, we first provide a comprehensive overview on the extensive on-going research efforts and categorize them based on the fundamental green tradeoffs. We will then focus on research progresses of 4G and 5G communications, such as orthogonal frequency division multiplexing and non-orthogonal aggregation, multiple input multiple output, and heterogeneous networks. We will also discuss potential challenges and impacts of fundamental green tradeoffs, to shed some light on the energy efficient research and design for future wireless networks.

Method and apparatus for distributing content in a communication network

Abstract: Aspects of the subject disclosure may include, for example, a system for receiving decoded satellite signals, obtaining media channels from the decoded satellite signals, selecting a portion of the media channels for distribution to a plurality of media processors, encoding the portion of the media channels selected according to a satellite distribution protocol, such as a protocol that facilitates satellite switching, to generate satellite encoded content, formatting the satellite encoded content according to a transport protocol to generate formatted content, and providing the formatted content for distribution to the plurality of media processors via a communication network, such as a single wire communication network or other network. Other embodiments are disclosed.

Robust and Efficient Distributed Compression for Cloud Radio Access Networks

Abstract: This paper studies distributed compression for the uplink of a cloud radio access network where multiple multiantenna base stations (BSs) are connected to a central unit, which is also referred to as a cloud decoder, via capacity-constrained backhaul links. Since the signals received at different BSs are correlated, distributed source coding strategies are potentially beneficial. However, they require each BS to have information about the joint statistics of the received signals across the BSs, and they are generally sensitive to uncertainties regarding such information. Motivated by this observation, a robust compression method is proposed to cope with uncertainties on the correlation of the received signals. The problem is formulated using a deterministic worst case approach, and an algorithm is proposed that achieves a stationary point for the problem. Then, BS selection is addressed with the aim of reducing the number of active BSs, thus enhancing the energy efficiency of the network. An optimization problem is formulated in which compression and BS selection are performed jointly by introducing a sparsity-inducing term into the objective function. An iterative algorithm is proposed that is shown to converge to a locally optimal point. From numerical results, it is observed that the proposed robust compression scheme compensates for a large fraction of the performance loss induced by the imperfect statistical information. Moreover, the proposed BS selection algorithm is seen to perform close to the more complex exhaustive search solution.

Control-Data Separation Architecture for Cellular Radio Access Networks: A Survey and Outlook

Abstract: Conventional cellular systems are designed to ensure ubiquitous coverage with an always present wireless channel irrespective of the spatial and temporal demand of service. This approach raises several problems due to the tight coupling between network and data access points, as well as the paradigm shift towards data-oriented services, heterogeneous deployments and network densification. A logical separation between control and data planes is seen as a promising solution that could overcome these issues, by providing data services under the umbrella of a coverage layer. This article presents a holistic survey of existing literature on the control-data separation architecture (CDSA) for cellular radio access networks. As a starting point, we discuss the fundamentals, concepts, and general structure of the CDSA. Then, we point out limitations of the conventional architecture in futuristic deployment scenarios. In addition, we present and critically discuss the work that has been done to investigate potential benefits of the CDSA, as well as its technical challenges and enabling technologies. Finally, an overview of standardisation proposals related to this research vision is provided.