Subband decomposition techniques for adaptive channel equalisation

In this contribution, the convergence behaviour of the adaptive linear equaliser based on subband decomposition technique is investigated. Two different subband-based linear equalisers are employed, with the aim of improving the equaliser's convergence performance. Simulation results over three channel models having different spectral characteristic are presented. Computer simulations indicate that subband-based equalisers outperform the conventional fullband linear equaliser when channel exhibit severe spectral dynamic. Convergence rate of subband equalisers are governed by the slowest subband, whereby different convergence behaviour in each individual subband is observed. Finally, the complexity of fullband and subband equalisers is discussed

Bit-error-rate Optimization for CDMA Ultra-wideband System Using Generalized Gaussian Approach

Ultra-wideband is a wireless technology arisen for future high speed multimedia applications. It can provide data rate in excess of Gigabits per second by transmitting impulse signal through the free space. However, the ultra-wideband indoor channel models proposed by the IEEE P802.15.3a suffer long multipath propagation. Due to this multipath effect, several studies have been done to improve the bit-error-rate performance of the ultra-wideband system in the existence of severe interference. Yet, most of the proposed algorithms were formulated based on the Gaussian distribution, which is not true in ultra-wideband. In this paper, we first analyze the statistical behavior of the CDMA-UWB signal by applying the Kullback-Leibler divergence index. Based on the analysis, a non-Gaussian equalizer is developed by deriving an enhanced bit-error-rate optimization algorithm using the Generalized Gaussian approach. The proposed equalizer has been shown to achieve a performance gain of at least 1.5dB to 2dB over the other equalizers simulated under IEEE P802.15.3a channel models

Performance modelling of adaptive VANET with enhanced priority scheme

In this paper, we present an analytical and simulated study on the performance of adaptive vehicular ad hoc networks (VANET) priority based on Transmission Distance Reliability Range (TDRR) and data type. VANET topology changes rapidly due to its inherent nature of high mobility nodes and unpredictable environments. Therefore, nodes in VANET must be able to adapt to the ever changing environment and optimize parameters to enhance performance. However, there is a lack of adaptability in the current VANET scheme. Existing VANET IEEE802.11p’s Enhanced Distributed Channel Access; EDCA assigns priority solely based on data type. In this paper, we propose a new priority scheme which utilizes Markov model to perform TDRR prediction and assign priorities based on the proposed Markov TDRR Prediction with Enhanced Priority VANET Scheme (MarPVS). Subsequently, we performed an analytical study on MarPVS performance modeling. In particular, considering five different priority levels defined in MarPVS, we derived the probability of successful transmission, the number of low priority messages in back off process and concurrent low priority transmission. Finally, the results are used to derive the average transmission delay for data types defined in MarPVS. Numerical results are provided along with simulation results which confirm the accuracy of the proposed analysis. Simulation results demonstrate that the proposed MarPVS results in lower transmission latency and higher packet success rate in comparison with the default IEEE802.11p scheme and greedy scheduler scheme

Cognitive radio network in vehicular ad hoc network (VANET): a survey

Cognitive radio network and vehicular ad hoc network (VANET) are recent emerging concepts in wireless networking. Cognitive radio network obtains knowledge of its operational geographical environment to manage sharing of spectrum between primary and secondary users, while VANET shares emergency safety messages among vehicles to ensure safety of users on the road. Cognitive radio network is employed in VANET to ensure the efficient use of spectrum, as well as to support VANET’s deployment. Random increase and decrease of spectrum users, unpredictable nature of VANET, high mobility, varying interference, security, packet scheduling, and priority assignment are the challenges encountered in a typical cognitive VANET environment. This paper provides survey and critical analysis on different challenges of cognitive radio VANET, with discussion on the open issues, challenges, and performance metrics for different cognitive radio VANET applications

Space-Time Frequency Block Codes in LTE-DSRC Hybrid Vehicular Networks

In vehicular communication systems, Dedicated Short Range Communication (DSRC) is said to provide fast communication and high security between vehicles. Simultaneously, Long-Term Evolution (LTE) is used due to its high bandwidth, low latency, and high spectrum efficiency. The DSRC and LTE hybrid model has gained much attention as it is feasible and simpler in design and deployment. In fact, multiple-input multiple-output (MIMO) systems have been widely used in modern wireless communication systems to enhance data throughput, reliability, and coverage. This paper proposes a MIMO LTE-DSRC hybrid system using space-time frequency block codes (STFBC). This paper focuses on the physical layer performance of the LTE-DSRC hybrid uplink structure. The DSRC Orthogonal Frequency Division Multiplexing (OFDM) transmitter and LTE Single Carrier Frequency Division Multiplexing (SCFDM) receiver are used for the uplink transmission. A study on bit error rate (BER), pairwise error probability (PEP), and channel-to-interference ratio (CIR) of the 2x2 MIMO LTE-DSRC system is conducted. The numerical results show that this proposed method improves the error rate performance with a gradual increase in signal-to-noise ratio (SNR) compared to the baseline systems

Recovery of lowland dipterocarp forests under the Malayan uniform system

Recovery assessment of the logged lowland dipterocarp forests based on phytosociological studies conducted in the state of Negeri Sembilan, Malaysia, showed that the recovery rate of the logged areas depends on the state and degree of harvesting carried out on the stands. The stands that were harvested from 1963 to 1973 under the Malayan Uniform System (MUS) have shown a relatively slow recovery rate. The sites have small average coverage by emergent (ST) trees, ranging from 8% to 14%, and only a few dipterocarps occupy this layer. On the other hand, the stands harvested in the 1950s have recovered towards their original state prior to harvest. The stands recorded an average ST-layer coverage of 24%, T1 layer (57%) and T2 layer (45%). The analysis of species composition recovery and species abundance showed similar trends, with F50 stands appearing similar to the primary forest. The study shows that it takes at least approximately 40 years for the logged-over stands under the MUS to recover to their original state

Prediction of patient admissions and bed requirement in inpatient department by using system dynamic simulation

Hospitals play a vital role in a nation’s healthcare system. As the custodian of primary healthcare providers, hospitals strive to provide continuous and comprehensive care to patients. The increase of patients annually sparked the requirement for the hospitals to reasonably plan and project their resources especially treatment beds with the goal to meet the uprising patient’s demand. A similar predicament is also encountered by one of the busiest public hospitals in Selangor, Malaysia. The spike in patients’ demand has reflected in the hospital’s struggle in embracing the rapid changes while providing the best quality health care. Therefore, this study focuses on the hospital’s inpatient department which requires accurate resource planning and precise allocation of treatment beds. Hence, the system dynamics simulation modelling is developed to enable the prediction of the number of inpatient admission and the total number of treatment beds required to meet the demand at the hospital for a period of ten years. The study’s findings revealed an increase in inpatient admission and roughly one bed is required to be added approximately every two years in pursuance to meet the demand. Conclusively, the surge in the inpatient’s admission will parallelly increase the use of treatment beds by the patients. The results formulated by this study will enable the hospital management’s decision making in terms of managing, planning and predicting of resources within their allocated budget while ensuring the betterment of service quality and enhancing the performance of the inpatient department

Assignment of spectrum demands by merits via analytic hierarchy process and integer programming

Demand for wireless services is ever increasing due to wireless technology advances, which directly relates to the increasing demand for spectrum bandwidths. Due to the high demand, thus spectrum has become scarce.As a result, spectrum bandwidths have become important and need to be efficiently assigned to potential and demanding service providers.Thus, this paper proposes an integrated approach to solve a spectrum assignment problem.The integrated model is developed to efficiently determine the optimal spectrum assignment for the purpose of satisfying the identified relevant requirements and constraints or criteria.The development of the model has also taken into consideration the situation when the spectrum regulator wishes to choose the best provider or licensee based on merits.For that purpose, suitable weights based on qualitative criteria were obtained via Analytic Hierarchy Process and subsequently used as coefficients in the respective Integer Programming formulation. The integrated optimization model is able to tackle a multi-criteria spectrum problem and then solve the assignment problem by way of maximizing the total efficiency. The results exhibits a more efficient alternative as compared to the existing qualitative approach, as it is able to combine subjective judgments computation with a mathematically formulated approach to produce a systematic and consistent results

Modeling of spectrum demands through hybrids of analytic hierarchy process and integer programming

As wireless technology advances, demand for spectrum bandwidth increases and thus, spectrum has become scarce. As a scarce resource, spectrum bandwidths need to be efficiently allocated to potential service providers. Hence, this paper first reviews current approaches on how spectrum bandwidths are being allocated to the service providers. Then we present an efficient integrated approach in allocating spectrum volumes, whereby the approaches of Analytic Hierarchy Process and Integer Programming are integrated and applied to produce systematic and consistent allocation results. The integrated approach is able to cater multi-criteria problems through determination of suitable weights and computations, which exhibits a more efficient alternative as compared to the existing approaches.The illustrations revealed that the integrated approach indeed has the potential to be implemented and gives an alternative to the current existing approaches