Showing papers by "Pin-Han Ho published in 2019"

UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks

Abstract: Fifth generation wireless networks are expected to provide advanced capabilities and create new markets. Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of unmanned aerial vehicles (UAVs) to collect data in dense wireless sensor networks using projection-based compressive data gathering (CDG) as a novel solution methodology. CDG is utilized to aggregate data en-route from a large set of sensor nodes to selected projection nodes acting as cluster heads (CHs) in order to reduce the number of needed transmissions leading to notable energy savings and extended network lifetime. The UAV transfers the gathered data from the CHs to a remote sink node, e.g., a 5G cellular base station, which avoids the need for long range transmissions or multihop communications among the sensors. Our problem definition aims at clustering the sensors, constructing an optimized forwarding tree per cluster, and gathering the data from selected CH nodes based on projection-based CDG with minimized UAV trajectory distance. We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. We demonstrate the superiority of the proposed approach and the designed algorithms via detailed performance results with analysis, comparisons, and insights.

Energy-efficient radio-over-fiber system for next-generation cloud radio access networks

Abstract: The paper proposes a novel adaptive radio-over-fiber (RoF) system for next-generation cloud radio access network (C-RAN), aiming to optimize the operation cost in terms of power consumption while maintaining required data rate. By jointly considering the nonlinear distortion from Mach-Zehnder modulator (MZM) and high power amplifier (HPA) due to high peak-to-average-power ratio (PAPR) in the electronic domain, we first provide a 2×2 multiple-input mulitple-output orthogonal frequency division multiplexing (MIMO-OFDM) baseband model on electrical SNR (ESNR) for a single RoF transmission line. To take the modulation levels into consideration, we provide the optical signal to noise ratio (OSNR) analysis that jointly considers the electrical SNR (ESNR) model and the non-linear effect of the optical transmission. This optical SNR (OSNR) analysis result is further used in the subsequent power consumption model for both the downlink and uplink of the considered RoF transmission system. Case studies via simulation and numerical experiments are conducted to verify that the proposed RoF system not only can reach the lowest power and spectrum consumptions at same time, but also consumes considerably less power than current RoF system.

A Benchmark for Joint Channel Allocation and User Scheduling in Flexible Heterogeneous Networks

Abstract: Flexible duplexing is a promising technique to improve the spectral efficiency of future cellular networks, which has been proposed mainly to provision asymmetric uplink (UL) and downlink (DL) traffic scenarios, through flexible channel allocations. However, this flexibility in the channel allocation process, which is responsible for allocating the underlying channel to different base stations in a heterogeneous network (HetNet), has brought new technical challenges due to the introduction of complex UL-to-DL and DL-to-UL interference scenarios. This paper analyzes the joint channel allocation (CA) and user scheduling (US) process for orthogonal frequency-division multiple access-based flexible HetNets, while considering exact inter-cell/intra-cell interferences. The resulting joint problem is a large-scale mixed-integer nonlinear programming problem that is computationally intractable, therefore, it has been re-formulated into a convex upper bound problem to find benchmark solutions for CA in flexible HetNets. Since, no new CA scheme has been proposed yet for the HetNets employing flexible duplexing techniques, we discuss the efficacy of existing schemes under various UL and DL traffic scenarios.

Statistical Properties of Energy Detection for Spectrum Sensing by Using Estimated Noise Variance

Abstract: In energy detection for cognitive radio spectrum sensing, the noise variance is usually assumed given, by which a threshold is set to guarantee a desired constant false alarm rate (CFAR) or a constant detection rate (CDR). However, in practical situations, the exact information of noise variance is generally unavailable to a certain extent due to the fact that the total noise consists of time-varying thermal noise, receiver noise, and environmental noise, etc. Hence, setting the thresholds by using an estimated noise variance may result in different false alarm probabilities from the desired ones. In this paper, we analyze the basic statistical properties of the false alarm probability by using estimated noise variance, and propose a method to obtain more suitable CFAR thresholds for energy detection. Specifically, we first come up with explicit descriptions on the expectations of the resultant probability, and then analyze the upper bounds of their variance. Based on these theoretical preparations, a new method for precisely obtaining the CFAR thresholds is proposed in order to assure that the expected false alarm probability can be as close to the predetermined as possible. All analytical results derived in this paper are testified by corresponding numerical experiments.

Joint User Scheduling and RRU Association for ODFMA-Based Networks With Inter-BBU Coordination

Abstract: This paper investigates the joint user scheduling (US) and user association (UA) problem for OFDMA-based networks under the centralized radio access network (C-RAN) architecture. We first formulate the joint optimization problem for US and UA, which is intractable in its exact form, and therefore, we propose a corresponding upper bound problem, with much lower computational complexity, with the help of a novel continuous rate function. We show that the upper bound problem can be further converted into an equivalent convex optimization problem via geometric programming (GP) that can be solved with inter-baseband unit coordination, which is viable in the C-RAN architecture. Furthermore, we show that the solutions of the convex upper bound problem can be mapped into the solution space of the original joint US and UA problem with a small gap. As a practically implementable solution to the original problem, a heuristic-based scheduler has been developed to obtain quasi-optimal UA and US solutions for the uplink (UL) as well as the downlink (DL) transmissions. Through extensive numerical simulations, we verify that the performance of the proposed heuristic-based scheduler is quasi-optimal on both UL and DL.