A simple example of audio signal processing on TMS320VC5416 USB DSK board. Main source is contained in tone.c file, memory configuration - tonecfg.cmd. Folder docs/ contains useful docmentation on board, its components and libraries. The example's configuration is based on example "tone" from Code Composer Studio's 3.1 example for 5416 DSK.
The 4.0 kbit/s speech codec described in this paper is based on a
Frequency Domain Interpolative (FDI) coding technique, which
belongs to the class of prototype waveform Interpolation (PWI)
coding techniques. The codec also has an integrated voice
activity detector (VAD) and a noise reduction capability. The
input signal is subjected to LPC analysis and the prediction
residual is separated into a slowly evolving waveform (SEW) and
a rapidly evolving waveform (REW) components. The SEW
magnitude component is quantized using a hierarchical
predictive vector quantization approach. The REW magnitude is
quantized using a gain and a sub-band based shape. SEW and
REW phases are derived at the decoder using a phase model,
based on a transmitted measure of voice periodicity. The spectral
(LSP) parameters are quantized using a combination of scalar
and vector quantizers. The 4.0 kbits/s coder has an algorithmic
delay of 60 ms and an estimated floating point complexity of
21.5 MIPS. The performance of this coder has been evaluated
using in-house MOS tests under various conditions such as
background noise. channel errors, self-tandem. and DTX mode
of operation, and has been shown to be statistically equivalent to
ITU-T (3.729 8 kbps codec across all conditions tested.
The SP2526A device is a dual +3.0V to +5.5V USB Supervisory Power Control Switch ideal
for self-powered and bus-powered Universal Serial Bus (USB) applications. Each switch has
low on-resistance (110mΩ typical) and can supply 500mA minimum. The fault currents are
limited to 1.0A typical and the flag output pin for each switch is available to indicate fault
conditions to the USB controller. The thermal shutdown feature will prevent damage to the
device when subjected to excessive current loads. The undervoltage lockout feature will
ensure that the device will remain off unless there is a valid input voltage present.
The recent developments in full duplex (FD) commu-
nication promise doubling the capacity of cellular networks using
self interference cancellation (SIC) techniques. FD small cells
with device-to-device (D2D) communication links could achieve
the expected capacity of the future cellular networks (5G). In
this work, we consider joint scheduling and dynamic power
algorithm (DPA) for a single cell FD small cell network with
D2D links (D2DLs). We formulate the optimal user selection and
power control as a non-linear programming (NLP) optimization
problem to get the optimal user scheduling and transmission
power in a given TTI. Our numerical results show that using
DPA gives better overall throughput performance than full power
transmission algorithm (FPA). Also, simultaneous transmissions
(combination of uplink (UL), downlink (DL), and D2D occur
80% of the time thereby increasing the spectral efficiency and
network capacity
Mobilenetworkoperatorswillmeetmanychallengesinthecomingyears.Itisexpectedthatthe
numberofpeopleconnected,wirelineandwireless,willreachfivebillionby2015.Atthesame
time, people use more wireless services and they expect similar user experience to what they
can now get from fixed networks. Because of that we will see a hundred-fold increase in
network traffic in the near future. At the same time markets are saturating and the revenue per
bit is dropping.
This book is intended for the graduate or advanced undergraduate
engineer. The primary motivation for developing the text was to present a
complete tutorial of phase-locked loops with a consistent notation. I believe
this is critical for the practicing engineer who uses the text as a self-study
guide.
I love telecommunications. It is powerful and it empowers, with
far-reaching consequences. It has demonstrated the potential to transform
society and business, and the revolution has only just begun. With the invention
of the telephone, human communications and commerce were forever changed: Time
and distance began to melt away as a barrier to doing business, keeping in touch
with loved ones, and being able to immediately respond to major world events.
Through the use of computers and telecommunications networks, humans have been
able to extend their powers of thinking, influence, and productivity, just as
those in the Industrial Age were able to extend the power of their muscles, or
physical self, through use of heavy machinery.
Wireless Mesh Networks (WMN) are believed to be a highly promising
technology and will play an increasingly important role in future
generation wireless mobile networks. WMN is characterized by
dynamic self-organization, self-configuration and self-healing to
enable quick deployment, easy maintenance, low cost, high scalability
and reliable services, as well as enhancing network capacity, connect-
ivity and resilience.
In writing this text my intention was to collect together in a single place
practical predictive modeling techniques, ideas and strategies that have been
proven to work but which are rarely taught in business schools, data science
courses or contained in any other single text.
