Physical Layer Parameters Research Articles

Feasibility Study of Power Line Communications for Backhauling Outdoor Small Cells

Small cells are low-power and low-range radio access nodes that can be used to increase network capacity in reduced areas with high traffic demand and to provide coverage to small isolated zones. As their number is expected to be very high, connecting them to the aggregation point in a cost-efficient manner is a key challenge, and there is consensus that none of the current technologies is valid for all scenarios. Since lamp-posts are one of the most convenient locations for outdoor small cells, this work analyzes the use of power line communications (PLC) over outdoor public lighting networks (OPLN) as a backhaul technology for outdoor small cell deployments. To this end, the characteristics of the PLC channels established in OPLN are firstly assessed. The analysis combines noise measurements performed in existing OPLN and channel responses obtained from a multiconductor transmission line (MTL) model. The attenuation, delay spread and spatial correlation of the multiple-input multiple-output (MIMO) channels are investigated and their influence in the physical layer parameters of PLC systems is discussed. Afterward, the performance achieved by state-of-the-art PLC systems is assessed. To this end, estimations obtained by means of simulations and measurements taken in actual networks are included. Data throughput achieved by PLC systems based on the ITU-T G.hn standard, as well as the expected improvements obtained by $3\times 3$ MIMO systems, are given. Results indicate that PLC can be an interesting technology for coverage-driven small cell deployments with backhaul length shorter than 150 m, offering throughput values similar to existing Sub-6 GHz wireless solutions in non-line-of-sight (NLOS) conditions and wired ones like G.fast.

Optimized Node Clustering based on Received Signal Strength with Particle Ordered-filter Routing Used in VANET

VANET is a critical and demanding mission. Numerous methods exist, but none profits in a distributed fashion from physical layer parameters. This paper describes a method that enables individual nodes to estimate node density, independent of beacon messages, and other infrastructure-based information, of their surrounding network. In this paper, a discrete simulator of events was proposed to estimate the average number of simultaneously transmitting nodes, a functional channel model for the VANETs system, and a method of estimating node density. Proposed based on some equations to allow individual nodes to estimate their surrounding node density in real-time Optimized Node Cluster Algorithm with Network Density in which the composition of a cluster is triggered adjacent, these traffic signals is the same and has been predicated mostly on the position a vehicle might well take after crossing. Additional Ordered Tracking with Particle -Filter Routing in which receives simultaneous signal intensity versus node transmission and node density transmission. Conduct multiple location-related analyzes to test the plausibility of the neighboring single-hop nodes on mobility data. The system is designed to operate in the most complex situations where nodes have little knowledge of network topology and the results, therefore, indicate that the system is fairly robust and accurate.

Experimental Link Quality Analysis for LoRa-Based Wireless Underground Sensor Networks

A variety of industrial applications are deployed in underground environments, such as soil condition assessment and pipeline monitoring (PM). Wireless underground sensor networks (WUSNs) are capable of continuously monitoring pipelines and promptly alerting any anomaly of entities. However, underground soils significantly influence the traditional WUSNs connectivity success. Long range (LoRa), being a leading low-power wide-area networks (LPWANs) technology, provides a new solution for underground industrial monitoring with its advantages in long-range capability and ultralow power consumption. Nevertheless, the LoRa-based link quality characteristics have not yet been quantitatively evaluated for WUSNs. In this article, the channel models of both the underground-to-aboveground (UG2AG) and aboveground-to-underground (AG2UG) communications are investigated. We experimentally analyze the impact of the propagation direction, burial depth and LoRa physical layer parameters on the in-situ LoRa propagation performance. The received signal strength indictor (RSSI), signal-to-noise ratio (SNR), and packet deliver ratio (PDR) are characterized for both communication channels in LoRa-based WUSNs. The semiempirical path-loss models are successfully verified by our field results, and we demonstrate that the communication range can be greater than 50 m at the burial depth of 0.4 m by adjusting the LoRa transmission/receiving settings. The combination of RSSI and SNR can be a better indicator of PDR than relying on either of them alone. Finally, the frame error rate (FER) is calculated to estimate the link performance with EM interferences. These results successfully demonstrate the advantages of LoRa for PM applications, which serve the first step toward the efficient protocol development of LoRa-based WUSNs.

Environmental Impacts on Hardware-Based Link Quality Estimators in Wireless Sensor Networks.

Hardware-based link quality estimators (LQEs) in wireless sensor networks generally use physical layer parameters to estimate packet reception ratio, which has advantages of high agility and low overhead. However, many existing studies didn’t consider the impacts of environmental changes on the applicability of these estimators. This paper compares the performance of typical hardware-based LQEs in different environments. Meanwhile, aiming at the problematic Signal-to-Noise Ratio (SNR) calculation used in existing studies, a more reasonable calculation method is proposed. The results show that it is not accurate to estimate the packet reception rate using the communication distance, and it may be useless when the environment changes. Meanwhile, the fluctuation range of the Received Signal Strength Indicator (RSSI) and SNR will be affected and that of Link Quality Indicator (LQI) is almost unchanged. The performance of RSSI based LQEs may degrade when the environment changes. Fortunately, this degradation is mainly caused by the change of background noise, which could be compensated conveniently. The best environmental adaptability is gained by LQI and SNR based LQEs, as they are almost unaffected when the environment changes. Moreover, LQI based LQEs are more accurate than SNR based ones in the transitional region. Nevertheless, compared with SNR, the fluctuation range of LQI is much larger, which needs a larger smoothing window to converge. In addition, the calculation of LQI is typically vendor-specific. Therefore, the tradeoff between accuracy, agility, and convenience should be considered in practice.

A study of the LoRa signal propagation in forest, urban, and suburban environments

Sensing is an activity of paramount importance for smart cities. The coverage of large areas based on reduced infrastructure and low energy consumption is desirable. In this context, Low Power Wide Area Network (LPWAN) plays an important role. In this paper, we investigate LoRa, a low-power technology offering large coverage, but low transmission rates. Radio range and data rate are tunable by using different spreading factors and coding rates, which are configuration parameters of the LoRa physical layer. LoRa can cover large areas but variations in the environment affect link quality. This work studies the propagation of LoRa signals in forest, urban, and suburban vehicular environments. Besides being environments with variable propagation conditions, we evaluate scenarios with node mobility. To characterize the communication link, we mainly use the Received Signal Strength Indicator (RSSI), Signal to Noise Ratio (SNR), and Packet Delivery Ratio (PDR). As for node mobility, speeds are chosen according to prospective applications. Our results show that the link reaches up to 250 m in the forest scenario, while in the vehicular scenario it reaches up to 2 km. In contrast, in scenarios with high-density buildings and human activity, the maximum range of the link reaches up to 200 m in the urban scenario.

HD video transmission of multi-rotor Unmanned Aerial Vehicle based on 5G cellular communication network

In UAV (Unmanned Aerial Vehicle) mission scenarios for aerial reconnaissance and aerial photography, wireless video backhaul is one of the essential functions. In recent years, with the rapid development of UAV in the military and civilian fields, mobile high-quality video backhaul has become a trend. This paper analyzes the hardware structure and software architecture of the UAV HD video wireless transmission model. The overall model is described from three levels of hardware, software, and link interface, and its software architecture is analyzed. Aiming at the high-frequency and large-bandwidth transmission system under 5G small cells, the influence of new channel characteristics on physical layer parameters is analyzed, and the frame structure design parameters such as subcarrier spacing and cyclic prefix are optimized. Considering the low throughput rate in multi-hop wireless networks, this paper innovatively proposes a slide mode based on frame rate adjustment. The simulation results show that the revised throughput prediction value has higher accuracy than the traditional method, and the bit rate adjustment is timely and can maintain a certain stability. Combining the advantages of the high and low bit rate schemes, the continuous video transmission is maintained while providing higher quality.

MUACLP Modeling Unified Architecture of Cross Layer Parameters Strategy of Handoff for Next Generation Wireless Network

The Quality of Service and Quality of experience is always a goal of future generation wireless systems. A suitably designed handoff plays an important role in achieving these goals. The traditional methods of handoff for wireless systems pose challenges in handling the smooth transition in the heterogeneous architecture of future generation architecture. This paper induces a model for synchronization of seamless handoff for a mobile user from a unified access point of a large cell to the small cell. The study is carried out considering a novel analytical model for facilitating a better form of vertical handoff mechanism in order to facilitate communication over 5G networks. The modeling is carried out considering the efficiency of channel capacity as well as considering near real-time constraint of latency and throughput. The typical design assumption for the unified architecture of the model for the handoff is for future generation wireless network that includes various physical layer parameters. For an effective analysis, the study considers that the receiving node will be identified on the basis of the non-erroneous node as the idea is to increase the proper utilization of the network resources. The core agenda of the study will be to ensure that irrespective of any form of traffic intensity as well as variable resource availability, the proposed scheme should be able to offer an extensive communication with the seamless performance during handoff operation. The study outcome exhibits that the proposed system offers better vertical handoff performance in contrast to the existing system on various test cases.

QoS Enhancement of AODV Routing for MBANs

Medical Body Area Networks or MBANs are gaining popularity in healthcare circles because of the convenience they provide to patients and caregivers and assist in chronic disease management. In order to provide prompt and efficient care to the patient, MBANs need to be designed in a way so that stringent QoS requirements are fulfilled. This is essential as MBANs carry vital sign data and any loss or delay in transmission can be fatal and life-threatening. Current research focus is to develop mechanisms and protocols that are focused to reduce delays, conserve energy and improve QoS parameters such as Reliability. An important aspect of MBANs is to give special attention to emergency traffic which is carried when a serious event is triggered such as heartbeat going above threshold or ECG status showing cardiac issues. Thus, the provision of QoS is a challenging task and must be addressed at various layers of the network. There are various techniques to cater to QoS requirements and one way of improving QoS is to reduce the packet loss so that transmission is reliable which is necessary for life-saving data. Research contributions have addressed this mostly at the MAC layer/network layer and through queuing techniques. However, none of these mechanisms do not consider the wireless channel dynamics and the impact of MAC layer and physical layer parameters together while focusing on Emergency data handling within an Intra-WBAN. In this paper, we have proposed a QoS aware Cross layered solution based on IEEE 802.15.6 that is adaptive, Relay based, multi metric and changes the routing scheme based on traffic type. We have selected AODV protocol over OLSR, DSR and other protocols because of its design simplicity. In this paper, we have reviewed the existing literature on WBAN Reliability enhancements’ techniques followed by a review of QoS aware enhancements for AODV. Our proposed protocol is designed and simulated for Intra-WBAN communication and is efficient in terms of end-to-end reliability.

Connectivity optimization in interference-limited random DSA networks

Network connectivity in dynamic spectrum access (DSA) networks has been well studied–most of which are under the unit disk model. However, the disk model does not capture the primary-secondary and secondary-secondary interference; hence signal to interference and noise ratio (SINR) based models are more appropriate. Moreover, in the SINR regime, there is no unique way to characterize connectivity and hence its maximization becomes even more challenging.In this paper, we develop the long eluding network connectivity objective function which we use to build three connectivity optimization techniques each of which targets a particular network setup. The proposed techniques are: i) Fittest deployment density, ii) Fittest receive-only ratio, and iii) Fittest TDMA slotting.To develop the aforementioned objective function, we start by addressing the lack of any relation between deployment density and network connectivity in interference-limited DSA networks. Next, percolation theory in conjunction with the Boolean model are utilized to develop such a relationship between the density of the percolation visible nodes and the network connectivity in interference limited environments. Finally, we use that relation to build the objective function for connectivity maximization along three optimization techniques. Theoretical findings are validated by simulating networks under various scenarios. Results provide a blueprint to establish and maximize connectivity using physical layer parameters (density, coverage radius, etc.) which can be used in conjunction with higher layer techniques. Also, tackling the connectivity problem at the physical layer relieves the other higher layers like the MAC layer from excess signaling and complex protocol designs.

Throughput enhancement of cognitive M2M networks based on NOMA for 5G communication systems

SummaryOne of the promising technologies for 5G cellular networks is machine‐to‐machine (M2M) communications. We propose a cognitive radio network (CR) that includes a primary cellular system and a secondary cognitive system. The primary cellular system has a primary client (PC) and the secondary cognitive system has M2M clients which are called secondary clients (SCs). In a conventional system of CR network based on orthogonal frequency division multiple access (CR‐OFDMA), when the primary client (PC) is absent, only one SC can obtain the idle spectrum. But, the SC must leave the spectrum when detecting the existence of the PC. So, the spectrum usage of this system is very low. This paper proposes a cooperative CR network based on nonorthogonal multiple access (CCR‐NOMA) for spectrum sensing using energy detection (ED) to allow multiple SCs to share the same frequency at the same time, but are differentiated according to the power domain or code domain, to improve spectrum efficiency of 5G communications and the transmission performance of CR network at the absence and presence of the PC. To evaluate the channel sensing performance of the ED technique in CCR‐NOMA, we derived a closed‐form expression between the achievable throughput and sensing time for the CCR‐NOMA system. The same analysis for the case of CR‐OFDMA is reproduced for the sake of comparison. The analysis showed that the CR‐NOMA system for M2M communication outperforms the CR‐OFDMA system for M2M communication for the same noncooperative and cooperative spectrum sensing and physical layer parameters.

Machine Learning Based Network Analysis Using Millimeter-Wave Narrow-Band Energy Traces

Next-generation wireless networks promise to provide extremely high data rates, especially exploiting the so-called millimeter-wave frequency range. Gaining information from spectrum usage is becoming important to provide smart adaptation capabilities to future network protocol stacks. Issues such as deafness, misaligned antennas, or blockage may severely impact network performance, and their identification is crucial. Despite the complexity of full analytical models, machine learning techniques are progressively being considered to improve spectrum usage at higher layers. In this paper, we design a signal processing technique that uses narrowband physical layer energy traces, obtained from one or multiple channel sniffers. The proposed technique utilizes a combination of template matching and an Explicit Duration Hidden Markov Model (EDHMM) to correctly classify frames, while coping with the non-stationarity of the traces. This leads to a protocol level monitor that does not need to decode the channel at the physical layer, but just infers the type of packets that are exchanged based on sub-sampled energy traces. The performance of this framework is evaluated using off-the-shelf mm-wave wireless devices, quantifying its detection performance in the presence of one or multiple sniffers, and assessing the impact of physical layer parameters such as noise power and signal levels.

Lightweight, Fluctuation Insensitive Multi-Parameter Fusion Link Quality Estimation for Wireless Sensor Networks

Accurate and agile link quality estimation is essential for wireless sensor networks. Using the mapping models between physical layer parameters and packet reception ratio, link quality can be estimated with advantages of high agility and low overhead. However, existing estimators based on physical layer parameters fail to utilize link quality information carried by different physical layer parameters efficiently and effectively and fail to effectively solve the problem that physical layer parameters fluctuate greatly, which makes them difficult to describe link conditions really. In this study, a lightweight, fluctuation insensitive multi-parameter fusion link quality estimator is proposed. Two physical layer parameters, Signal-to-Noise Ratio and Link Quality Indicator are preprocessed by exponential weighted Kalman filtering to get more stable estimation values. Then, these two parameters are fused using lightweight weighted Euclidean distance to fully utilize link quality information carried by them. On this basis, link quality is estimated quantitatively with the mapping model of the fused parameter and packet reception ratio, which is constructed by logistic regression. Experimental results show that the proposed estimator could reflect link quality more realistically. Compared with similar estimators, estimate error of the proposed one is reduced by 18.32% to 60.11% under moderate and bad links with large fluctuations, by 1.42% to 83.43% under sudden changed links, and by 16.64% to 65.61% under a long-time link. More importantly, computation overhead of the proposed estimator is equivalent to that of single-parameter estimators, but much less than other multi-parameter fusion estimators. Compared with the later, computation overhead is reduced by 72.36% to 95.61%.

Optimal Collaborative Spectrum Sharing for a Cognitive Multi-Antenna Relay With Full-Duplex Capability and Stability Constraint

Collaborative spectrum sharing (CSS) between primary and secondary users (PU and SU) is an effective way of utilizing limited radio spectrum. In CSS, cognitive SU acts as a relay for PU, which facilitates the PU to send its packet with a lower error probability by the help of the SU, and consequently, the SU has more chances to find a vacant spectrum. When SU is equipped with multiple antennas, it can further efficiently utilize the radio spectrum by adopting a growing self-interference cancellation technique for full-duplex (FD) transmission. In this paper, both an aggressive and a passive secondary usage of the spectrum are proposed, the operational principles of which are defined using spectrum-sharing probability φ in FD CSS environments. For the spectrum-sharing probability φ, SU for each of the methods sends its own signal and the PU's (relayed) signal together by using superposition transmission. For the remaining probability 1 - φ, the two methods work differently: SU sends its own signal only in the aggressive mode while it sends only the relaying signal for PU in the passive mode. We formulate an FD CSS problem with various physical-layer parameters and the proposed operating modes as a function of the spectrum-sharing probability. Our goal is to maximize the secondary stable throughput while keeping a primary traffic constraint. Closed-form optimal solutions on φ are provided in the paper, the value of which heavily depends on the primary traffic volume, the operating modes, the relative locations of the collaborative nodes and the transmit power budget at SU. The analytical results in the paper are verified with numerical investigation, and the performance enhancement by the proposed methods is evaluated in comparison with benchmark systems. The results show that the aggressive mode is promising if SU has a relatively small transmit power and the primary traffic load is low, while the passive mode is suitable when the primary traffic load is high.

Optimized Energy Consumption for Slotted Aloha and CSMA/CA Multihop Ad Hoc Networks

Ad hoc and wireless sensor networks are characterized by their ability to monitor phenomena in the most adverse scenarios. However, to perform well, these networks need to be self-adjusting and save energy. In general, these networks operate without human interference and require strategies to provide longer operating life. This paper investigates the energy consumption in a random multihop ad hoc network, comparing the slotted Aloha with the CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance) implemented in the IEEE 802.11 Distributed Coordination Function (DCF) as medium access control (MAC) protocols. We obtain the optimal transmission power as a function of physical and link layers parameters which results the optimized energy consumption per successfully transmitted bit. In this paper, we find that there are values of these parameters that can be used to extend the battery life of wireless communication devices comparing the Aloha and CSMA/CA performance.

Coalition Formation Games for Coordinated Service in Realistic Small Cell Propagation Topologies

The densification of modern wireless networks into a dense ecosystem of small cells imposes challenges for the reliable service and high quality of experience of its users as it can result into severe intercell interference, especially for users scattered on the cell edges. Joint Transmission Coordinated Multipoint (JT-CoMP) is a technique that can be deployed to form cooperating clusters of transmission points, enabling them to jointly transmit data to significantly mitigate this type of interference for these users. However, JT-CoMP stresses the backhaul links and radio resources are limited, meaning that, with incautious clustering, the data rates for cell edge users may not improve, while the data rates for the non-cell edge users may severely decrease. To tackle these drawbacks, a dynamic coalition formation algorithm is proposed to form the appropriate transmission point clusters to implement JT-CoMP. Furthermore, to ensure reliable service for all the network’s users, the case where JT-CoMP is enhanced with the capability to serve users based on their selected application is examined. The proposed scheme’s adaptability and capability to increase cell edge user throughput is then tested and compared to the non JT-CoMP case, a JT-CoMP scheme with static clustering and a JT-CoMP scheme with greedy clustering for a user mobility scenario. To obtain more reliable and accurate results of the JT-CoMP deployment, physical layer parameters retrieved from a fully deterministic physical layer radio planning tool (TruNET wireless) are imported for our simulations.

On Bayesian Fisher Information Maximization for Distributed Vector Estimation

In this paper, we consider the problem of bandwidth-constrained distributed estimation of a Gaussian vector with linear observation model. Each sensor makes a scalar noisy observation of the unknown vector, employs a multi-bit scalar quantizer to quantize its observation, and maps it to a digitally modulated symbol. Sensors transmit their symbols over orthogonal-power-constrained fading channels to a fusion center (FC). The FC is tasked with fusing the received signals from sensors and estimating the unknown vector. We derive the Bayesian Fisher Information Matrix (FIM) for three types of receivers: (i) coherent receiver; (ii) noncoherent receiver with known channel envelopes; and (iii) noncoherent receiver with known channel statistics only. We also derive the Weiss–Weinstein bound (WWB). We formulate two constrained optimization problems, namely maximizing trace and log-determinant of Bayesian FIM under network transmit power constraint, with sensors’ transmit powers being the optimization variables (we refer to as FIM-max schemes). We show that for coherent receiver, these problems are concave. However, for noncoherent receivers, they are not necessarily concave. The solution to the trace of Bayesian FIM maximization problem can be implemented in a distributed fashion, in the sense that each sensor calculates its own transmit power using its local parameters. On the other hand, the solution to the log-determinant of Bayesian FIM maximization problem cannot be implemented in a distributed fashion and the FC needs to find the powers (using parameters of all sensors) and inform the active sensors of their transmit powers. We numerically investigate how the FIM-max power allocation across sensors depends on the sensors observation qualities and physical layer parameters as well as the network transmit power constraint. Moreover, we evaluate the system performance in terms of mean square error (MSE) using the solutions of FIM-max schemes, and compare it with the solution obtained from minimizing the MSE of the LMMSE estimator (MSE-min scheme), and that of uniform power allocation. These comparisons illustrate that, although the WWB is tighter than the inverse of Bayesian FIM, it is still suitable to use FIM-max schemes, since the performance loss in terms of the MSE of the LMMSE estimator is not significant. Furthermore, comparing the performance of different receivers, our numerical results reveal that coherent receiver and noncoherent receiver with known channel statistics have the best and the worst performance, respectively.

A Reliable Channel Estimation Scheme Using Scattered Pilot Pattern for IEEE 802.22-Based Mobile Communication System

Current vehicular communication systems are disadvantageous in dealing with a full-range futuristic intelligent transportation system (ITS) with regard to coverage and cost. On the contrary, TV white-spaces have the potential to provide a wide-coverage, large-capacity, and cost-effective connectivity for ITS because of the excellent propagation properties, and there are increasing demands for applying IEEE 802.22 to mobile communication system capable of a wide coverage of 10–30 km. Meanwhile, since IEEE 802.22 was standardized as a fixed communication system, its scattered pilot pattern hinders accurate channel estimation in a highly mobile environment due to the Doppler shift and long-delay multipath fading. In this paper, we propose a reliable channel estimation scheme enabling an IEEE 802.22-based mobile communication system in rural areas without altering physical layer parameters. The proposed scheme effectively uses pilot symbols in adjacent subcarriers to extend interpolation range and shorten interpolation interval and offers high-accurate and stable channel estimation while maintaining flexibility in downstream/upstream ratio. As a simulation result, our proposed scheme sufficiently achieves a required bit error rate of $2\times 10^{-4}$ in a highly mobile long-delay multipath fading environment even in the presence of high carrier frequency offset.

Downlink Interference Control of LAA-LTE for Coexistence With Asymmetric Hidden Wi-Fi APs

To confront the increasing mobile traffic demand and the scarcity of the licensed band, 3GPP has standardized a new type of LTE, called License Assisted Access (LAA) LTE (LAA-LTE), which aggregates licensed bands with unlicensed bands. Since the conventional Wi-Fi devices employ −62 dBm clear channel assessment threshold to LAA-LTE's signals, the appearance of LAA-LTE in the unlicensed band leads to a new phenomenon, asymmetric hidden terminal problem , which severely degrades the throughput and delay performance of LAA-LTE as well as Wi-Fi. We propose a downlink interference control scheme for an LAA-LTE eNB to prevent the asymmetric hidden Wi-Fi APs nearby from recklessly transmitting and thereby interfering the eNB's transmission. Specifically, we analyze the distortion of Wi-Fi's signals received at LAA-LTE and LAA-LTE's signals received at Wi-Fi due to the difference of physical-layer parameters between LAA-LTE and Wi-Fi. Based on this analysis, we develop an AP suppression and power control technique to control incoming and outgoing interference of the LAA-LTE eNB. Extensive simulations confirm that the proposed scheme improves the throughput and delay performance of LAA-LTE while maintaining or even improving the performance of Wi-Fi.

Performance comparison between recirculating loop buffer-based optical packet switch architectures

Due to the high cabling complications and limited scalability, the Ethernet switching is not a well-suited technology for the next-generation data center systems (NGDCs). In designing of interconnects for NGDCs, the first step is to select an appropriate switching technology. The best solution to the problems faced by NGDCs is the use of optical switching technology in the core of data centers. In this paper, three recirculating loop buffer-based optical packet switches are discussed. The first two switch discussed in this paper were proposed in the recent past, and the third switch is proposed by the authors of this paper. In this paper, a performance comparison between the switches is performed by considering physical and network layer parameters. The obtained results presented in the paper show that the performance of our proposed switch is better in comparison with other switches.

Sensitivity of Planetary Boundary Layer Scheme in WRF-Chem Model for Predicting PM10 Concentration (Case study: Jakarta)

Weather Forecasting-Chemistry (WRF-Chem) is an air pollution model that combines meteorological factors and atmospheric chemistry simultaneously (online coupled). Many schemes selected on WRF-Chem according to boundary layer conditions of the study area. The objectives of this study were to evaluate WRF-Chem model and analyze the sensitivity of Yonsei University (YSU) scheme and Mellor Yamada Janjic (MYJ) scheme as physical boundary layer parameters, especially for Jakarta region. Particulate matter 10 micrometers or less in diameter (PM10) selected as the air pollutant parameter. The model outputs compared to observational data in five locations in Jakarta. The regression analysis between air temperature data shows that the values of R2 are 0.5 - 0.6 in February and 0.5 - 0.9 in August. Another result, the wind velocity from WRF-Chem overestimates but the hourly averages have a similar diurnal pattern with the observation. The PM10 concentration model output is underestimated which is caused by local emissions that are not accommodated in the model. The sensitivity analysis shows a higher sensitivity index for MYJ than YSU scheme, especially in August, so the model outcome of the MYJ scheme has a good response to the observations in Jakarta. It is seen that the extreme concentration of PM10 produced through the WRF-Chem with both schemes in February and August have the same time in morning. The model output of WRF-Chem through both schemes also demonstrate the minimum concentration of PM10 that follows during afternoon. The Planetary Boundary Layer (PBL) height analysis shows that in morning until noon, the PBL height with MYJ scheme is lower than YSU. It is different for other hours, that from the afternoon through the night until next morning, the height of PBL with MYJ scheme is thicker than YSU. At the point when the PBL is high, the pollutants assorted in a more volume so the estimation of the pollutant concentration estimated on the surface will be reduced.