Small-sized packet error rate reduction using coded parity packet approach

2012

J Wireless Com Network

Self Cite

A successive interference cancelation (SIC) method is developed in this article to improve the performance of the downlink transmission throughput for the current high speed downlink packet access (HSDPA) system. The multicode code division multiplexing spreading sequences are orthogonal at the HSDPA downlink transmitter. However, the spreading sequences loose their orthogonality following transmission through frequency selective multipath channels. The SIC method uses a minimum-mean-square-error (MMSE) equalizer at the receiver to despread multicode signals to restore the orthogonality of the receiver signature sequences. The SIC scheme is also used as part of the resource allocation schemes at the transmitter and for the purpose of interference and inter-symbolinterference cancelation at the receiver. The article proposes a novel system value based optimization criterion to provide a computationally efficient energy allocation method at the transmitter, when using the SIC interference cancelation and MMSE equalizer methods at the receiver. The performance of the proposed MMSE equalizer based on the SIC receiver is significantly improved compared with the existing schemes tested and is very close to the theoretical upper bound which may be achieved under laboratory conditions.

Section: System Value Simplifications Using the Sic Conceptmentioning

confidence: 99%

The interference-reduced energy loading for multi-code HSDPA systems

Gurcan

2012

J Wireless Com Network

Self Cite

“…represents a symbol, which is regenerated using the CPP scheme [11], received in the p-th symbol period. This coding scheme has been demonstrated in [11] to reduce the gap value achieved by the Turbo coding scheme, especially at small-sized packets.…”

Section: And the Receiver Structurementioning

confidence: 99%

“…This coding scheme has been demonstrated in [11] to reduce the gap value achieved by the Turbo coding scheme, especially at small-sized packets. Furthermore, the improved packet-based decoding technique provides an improved detection process and prevents the error propagation problem, if any, during the successive interference cancellation and decoding processes.…”

Section: And the Receiver Structurementioning

confidence: 99%

“…In this paper, a different SIC-based energy allocation scheme [10], which requires a relatively low computational load without matrix inversions to mitigate lSI and MAl components and enhance the total transmission bit rate, is proposed and in tegrated with the two-group resource allocation scheme [2]. A packet-based detection scheme known as the coded parity packet (CPP) coding scheme [11] is also combined with this proposed loading scheme to provide correctly detected previous and next symbols from the packet received in the currently detected channel for the SIC and detection operations on the packet in the next channel. This modified two-group loading technique, which requires no matrix inversions, is suitable for femtocells implementation as its computational complexity is significantly reduced whilst maintaining the improvement in the transmission bit rate.…”

Section: Introductionmentioning

confidence: 99%

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Successive interference cancellation for two-group resource allocation

Gurcan

2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications

2011

An energy allocation scheme is developed for multi code code division mUltiple access (CDMA) systems to allocate the total energy to two-groups of code channels whilst considering successive interference cancellation to minimize the allocated energy. With a simplified energy calculation formulation, the required computational complexity to improve the transmission data rates is relatively reduced. This proposed scheme is also combined with a packet-based channel coding scheme, which provides regenerated symbols to be removed during the interfer ence cancellation process.

“…Fourier Transform is first introduced by Jean Baptiste Joseph Fourier [1] to solve the computational complexity in wide varities of fields including earth and science, chemistry, communications, and signal processing [2][3][4][5]. In signal processing, Fourier Transform [6][7][8][9][10][11] has long been established as an instrumental tool applied in electrical signal spectrum and filter analysis, sampling and series, antenna, television image convolution as well as radio broadcasting [1].…”

Section: Introductionmentioning

confidence: 99%

A review on sparse fast fourier transform applications in image processing

Malek

Azmi

et al. 2020

IJECE

Fast Fourier Transform has long been established as an essential tool in signal processing. To address the computational issues while helping the analysis work for multi-dimensional signals in image processing, sparse Fast Fourier Transform model is reviewed here when applied in different applications such as lithography optimization, cancer detection, evolutionary arts and wasterwater treatment. As the demand for higher dimensional signals in various applications especially multimedia appplications, the need for sparse Fast Fourier Transform grows higher.