2,300 research outputs found
Frequency-Selective PAPR Reduction for OFDM
We study the peak-to-average power ratio (PAPR) problem in orthogonal
frequency-division multiplexing (OFDM) systems. In conventional clipping and
filtering based PAPR reduction techniques, clipping noise is allowed to spread
over the whole active passband, thus degrading the transmit signal quality
similarly at all active subcarriers. However, since modern radio networks
support frequency-multiplexing of users and services with highly different
quality-of-service expectations, clipping noise from PAPR reduction should be
distributed unequally over the corresponding physical resource blocks (PRBs).
To facilitate this, we present an efficient PAPR reduction technique, where
clipping noise can be flexibly controlled and filtered inside the transmitter
passband, allowing to control the transmitted signal quality per PRB. Numerical
results are provided in 5G New Radio (NR) mobile network context, demonstrating
the flexibility and efficiency of the proposed method.Comment: Accepted for publication as a Correspondence in the IEEE Transactions
on Vehicular Technology in March 2019. This is the revised version of
original manuscript, and it is in press at the momen
Communication Subsystems for Emerging Wireless Technologies
The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels
On Out-of-Band Emissions of Quantized Precoding in Massive MU-MIMO-OFDM
We analyze out-of-band (OOB) emissions in the massive multi-user (MU)
multiple-input multiple-output (MIMO) downlink. We focus on systems in which
the base station (BS) is equipped with low-resolution digital-to-analog
converters (DACs) and orthogonal frequency-division multiplexing (OFDM) is used
to communicate to the user equipments (UEs) over frequency-selective channels.
We demonstrate that analog filtering in combination with simple
frequency-domain digital predistortion (DPD) at the BS enables a significant
reduction of OOB emissions, but degrades the
signal-to-interference-noise-and-distortion ratio (SINDR) at the UEs and
increases the peak-to-average power ratio (PAR) at the BS. We use Bussgang's
theorem to characterize the tradeoffs between OOB emissions, SINDR, and PAR,
and to study the impact of analog filters and DPD on the error-rate performance
of the massive MU-MIMO-OFDM downlink. Our results show that by carefully tuning
the parameters of the analog filters, one can achieve a significant reduction
in OOB emissions with only a moderate degradation of error-rate performance and
PAR.Comment: Presented at the 2017 Asilomar Conference on Signals, Systems, and
Computers, 6 page
NOVEL OFDM SYSTEM BASED ON DUAL-TREE COMPLEX WAVELET TRANSFORM
The demand for higher and higher capacity in wireless networks, such as cellular,
mobile and local area network etc, is driving the development of new signaling
techniques with improved spectral and power efficiencies. At all stages of a
transceiver, from the bandwidth efficiency of the modulation schemes through highly
nonlinear power amplifier of the transmitters to the channel sharing between different
users, the problems relating to power usage and spectrum are aplenty. In the coming
future, orthogonal frequency division multiplexing (OFDM) technology promises to
be a ready solution to achieving the high data capacity and better spectral efficiency in
wireless communication systems by virtue of its well-known and desirable
characteristics.
Towards these ends, this dissertation investigates a novel OFDM system based on
dual-tree complex wavelet transform (D
Peak-to-Average Power Ratio Reduction of DOCSIS 3.1 Downstream Signals
Tone reservation (TR) is an attractive and widely used method for peak-to-average power ratio (PAPR) reduction of orthogonal frequency division multiplexing (OFDM) signals, where both transmitter and receiver agree upon a number of subcarriers or tones to be reserved to generate a peak canceling signal that can reduce the peak power of the transmitted signals. The tones are selected to be mutually exclusive with the tones used for data transmission, which allows the receiver to extract the data symbols without distortions.
This thesis presents two novel PAPR reduction algorithms for OFDM signals based on the TR principle, which do not distort the transmitted signals. The first proposed algorithm is performed in the time domain, whereas the second algorithm is a new clipping-and-filtering method. Both algorithms consist of two stages. The first stage, which is done off-line, creates a set of canceling signals based on the settings of the OFDM system. In particular, these signals are constructed to cancel signals at different levels of maximum instantaneous power that are above a predefined threshold. The second stage, which is online and iterative, reduces the signal peaks by using the canceling signals constructed in the first stage. The precalculated canceling signals can be updated when different tone sets are selected for data transmission, accommodating many practical applications. Simulation results show that the proposed algorithms achieve slightly better PAPR reduction performance than the conventional algorithms. Moreover, such performance is achieved with much lower computational complexity in terms of numbers of multiplications and additions per iteration. Among the two proposed algorithms, the time-domain algorithm gives the best peak reduction performance but the clipping-and-filtering algorithm requires considerably less number of multiplications per iteration and can be efficiently implemented using the fast Fourier transform (FFT)/inverse fast Fourier transform (IFFT) structure
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