Unique word-orthogonal frequency division multiplexing (UW-OFDM) provides several performance benefits over conventional cyclic prefix (CP) based OFDM, such as excellent spectral sidelobe suppression properties and an...
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ISBN:
(数字)9781728154787
ISBN:
(纸本)9781728154794
Unique word-orthogonal frequency division multiplexing (UW-OFDM) provides several performance benefits over conventional cyclic prefix (CP) based OFDM, such as excellent spectral sidelobe suppression properties and an outstanding bit error ratio performance. Aside from idealized assumptions, each comm.nication system faces challenges in conducting various system parameter estimation tasks. This work extends the current UW-OFDM signaling scheme by optimally including pilots tones in the frequency domain. Pilot tone based estimation of a carrier frequency offset (CFO) is conducted as a practical estimation example. Simulation results in a multipath environment demonstrate a significantly increased estimation accuracy in UW-OFDM over CP-OFDM, a result predicated on the inherent redundancy present in an UW-OFDM signal. The difference in estimation quality gets even more dominant with increasing CFO.
In our previous paper, we proposed a sound source separation method using the two-dimensional fast Fourier transform (2D FFT) of a spatio-temporal sound pressure distribution (STSPD) image that is composed from the ou...
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In our previous paper, we proposed a sound source separation method using the two-dimensional fast Fourier transform (2D FFT) of a spatio-temporal sound pressure distribution (STSPD) image that is composed from the ou...
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ISBN:
(数字)9781728152561
ISBN:
(纸本)9781728152578
In our previous paper, we proposed a sound source separation method using the two-dimensional fast Fourier transform (2D FFT) of a spatio-temporal sound pressure distribution (STSPD) image that is composed from the outputs of a microphone array. In an STSPD image, vertical stripes are created for a target sound arriving from the perpendicular direction to the array; therefore, its spectral components are concentrated on the spatial direct current (DC) components in the 2D amplitude spectrum. In that study, we estimated the noise DC amplitudes using a deep neural network (DNN), then subtracted them from the observed spectrum to suppress the noise. However, the performance of noise suppression can be improved further. In this study, we estimate the noise DC components theoretically inst.ad of empirically using a DNN. We improved the performance successfully.
In this work, we give an overview on recent developments that have been made in the field of mm-wave systems which are integrated on chip or in package. Several aspects like waveforms and signal generation, multi-chan...
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In this work, we give an overview on recent developments that have been made in the field of mm-wave systems which are integrated on chip or in package. Several aspects like waveforms and signal generation, multi-channel systems for beamforming applications as well as integration of antennas into packages will be discussed. The focus of this work is put on approaches which are suitable for on-chip and in-package integration. The restrictions imposed by the integration into single devices are discussed and several prototype systems are presented.
As the feature size of MOSFETs becomes increasingly small, the super self-aligned process is extremely important for the progress of ULSIs. The improvement of carrier mobility in the channel region is also indispensab...
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In this paper, a novel algorithm for low-power image coding and decoding is presented and the various inherent trade-offs are described and investigated in detail. The algorithm reduces the memory requirements of vect...
In this paper, a novel algorithm for low-power image coding and decoding is presented and the various inherent trade-offs are described and investigated in detail. The algorithm reduces the memory requirements of vector quantization, i.e., the size of memory required for the codebook and the number of memory accesses by using small codebooks. This significantly reduces the memory-related power consumption, which is an important part of the total power budget. To compensate for the loss of quality introduced by the small codebook size, simple transformations are applied on the codewords during coding. Thus, small codebooks are extended through computations and the main coding task becomes computation-based rather than memory-based. Each image block is encoded by a codeword index and a set of transformation parameters. The algorithm leads to power savings of a factor of 10 in coding and of a factor of 3 in decoding, at least in comparison to classical full-search vector quantization. In terms of SNR, the image quality is better than or comparable to that corresponding to full-search vector quantization, depending on the size of the codebook that is used. The main disadvantage of the proposed algorithm is the decrease of the compression ratio in comparison to vector quantization. The trade-off between image quality and power consumption is dominant in this algorithm and is mainly determined by the size of the codebook.
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