the paper is concerned with the design of wavelet filters for discrete wavelet multitone (DWMT) systems. DWMT systems suffer from the two main problems of inter-symbol interference (ISI) and inter-carrier interference (ICI). ISI may be considerably reduced via channel equalization. The effect of ICI can be reduced using high order filters, but at the expense of increased system complexity. The analysis presented in the work have showed that the required wavelet filters to reduce the ICI should have autocorrelation function approaching an impulse. The resulting filters are orthogonal and consisting of only two nonzero components for any filter order. These filters are compared to Daubechies and Coiflets filters. The comparisons showed that when the designed filters are employed by a DWMT system, then it is much simpler and a much less number of interfering terms will appear at detection. Therefore, the designed filters seem to be more suitable to be used in DWMT systems compared to other types of wavelet filters.
Smart city has developed energy, environmental, and healthcare services. It is also continuously providing new services to all citizens. This paper is concerned with the design and implementation of smart meter system as the core for smart grid in smart city. A system is proposed where the electricity supply is monitored by measuring its related parameters (voltage, current, power, energy consumption, and consumption bill) and issuing Short Message Service (SMS) notification of the consumption. The designed system used PZEM-004T, Arduino Mega, Raspberry Pi and Node-Red platforms. The data related to the measured parameters are successfully transmitted to the datacenter using Message Queuing Telemetry Transport (MQTT) protocol, stored in MySQL database using core python program, and displayed on Node-Red platform. The test and verification of the system are performed using different scenarios showing that successful and accurate operation of the system components are achieved. Finally, the designed system can be extended to cover large geographical areas and can be modified to serve for pre-paid arrangement in an effort to assist in reducing the electricity consumption in Iraq with the continuing crises of electricity.
Channel coding is required to correct transmission errors that are caused by noise, interference and poor signal strength. 3G and 4G systems already used turbo code for error correction. 3GPP and other standardization bodies are currently debating whether to use Low Density Parity Check (LDPC) or polar code instead in 5G. In this paper we look into 5G requirements for channel coding and review candidate channel coding schemes for 5G. A comparative study is presented for possible channel coding candidates of 5G covering Convolutional, Turbo, LDPC, and Polar codes. It seems that polar code with Successive Cancellation List (SCL) decoding using small list length (such as 8) is a promising choice for short message lengths (≤ 128 bits) due to its error performance and relatively low complexity. Adopting non-binary LDPC can provide good performance on the expense of increased complexity but with better spectral efficiency. Considering the implementation, polar code with decoding algorithms based on SCL required small area and low power consumption when compared to LDPC codes. For larger message lengths (≥ 256 bits) turbo code can provide better performance at low coding rates (<1/2).
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