1,651 research outputs found
A Review of Audio Features and Statistical Models Exploited for Voice Pattern Design
Audio fingerprinting, also named as audio hashing, has been well-known as a
powerful technique to perform audio identification and synchronization. It
basically involves two major steps: fingerprint (voice pattern) design and
matching search. While the first step concerns the derivation of a robust and
compact audio signature, the second step usually requires knowledge about
database and quick-search algorithms. Though this technique offers a wide range
of real-world applications, to the best of the authors' knowledge, a
comprehensive survey of existing algorithms appeared more than eight years ago.
Thus, in this paper, we present a more up-to-date review and, for emphasizing
on the audio signal processing aspect, we focus our state-of-the-art survey on
the fingerprint design step for which various audio features and their
tractable statistical models are discussed.Comment: http://www.iaria.org/conferences2015/PATTERNS15.html ; Seventh
International Conferences on Pervasive Patterns and Applications (PATTERNS
2015), Mar 2015, Nice, Franc
Optimal Beamforming for Physical Layer Security in MISO Wireless Networks
A wireless network of multiple transmitter-user pairs overheard by an
eavesdropper, where the transmitters are equipped with multiple antennas while
the users and eavesdropper are equipped with a single antenna, is considered.
At different levels of wireless channel knowledge, the problem of interest is
beamforming to optimize the users' quality-of-service (QoS) in terms of their
secrecy throughputs or maximize the network's energy efficiency under users'
QoS. All these problems are seen as very difficult optimization problems with
many nonconvex constraints and nonlinear equality constraints in beamforming
vectors. The paper develops path-following computational procedures of
low-complexity and rapid convergence for the optimal beamforming solution.
Their practicability is demonstrated through numerical examples
Real-time Optimal Resource Allocation for Embedded UAV Communication Systems
We consider device-to-device (D2D) wireless information and power transfer
systems using an unmanned aerial vehicle (UAV) as a relay-assisted node. As the
energy capacity and flight time of UAVs is limited, a significant issue in
deploying UAV is to manage energy consumption in real-time application, which
is proportional to the UAV transmit power. To tackle this important issue, we
develop a real-time resource allocation algorithm for maximizing the energy
efficiency by jointly optimizing the energy-harvesting time and power control
for the considered (D2D) communication embedded with UAV. We demonstrate the
effectiveness of the proposed algorithms as running time for solving them can
be conducted in milliseconds.Comment: 11 pages, 5 figures, 1 table. This paper is accepted for publication
on IEEE Wireless Communications Letter
Chain: A Dynamic Double Auction Framework for Matching Patient Agents
In this paper we present and evaluate a general framework for the design of
truthful auctions for matching agents in a dynamic, two-sided market. A single
commodity, such as a resource or a task, is bought and sold by multiple buyers
and sellers that arrive and depart over time. Our algorithm, Chain, provides
the first framework that allows a truthful dynamic double auction (DA) to be
constructed from a truthful, single-period (i.e. static) double-auction rule.
The pricing and matching method of the Chain construction is unique amongst
dynamic-auction rules that adopt the same building block. We examine
experimentally the allocative efficiency of Chain when instantiated on various
single-period rules, including the canonical McAfee double-auction rule. For a
baseline we also consider non-truthful double auctions populated with
zero-intelligence plus"-style learning agents. Chain-based auctions perform
well in comparison with other schemes, especially as arrival intensity falls
and agent valuations become more volatile
Joint Fractional Time Allocation and Beamforming for Downlink Multiuser MISO Systems
It is well-known that the traditional transmit beamforming at a base station
(BS) to manage interference in serving multiple users is effective only when
the number of users is less than the number of transmit antennas at the BS.
Non-orthogonal multiple access (NOMA) can improve the throughput of users with
poorer channel conditions by compromising their own privacy because other users
with better channel conditions can decode the information of users in poorer
channel state. NOMA still prefers that the number of users is less than the
number of antennas at the BS transmitter. This paper resolves such issues by
allocating separate fractional time slots for serving the users with similar
channel conditions. This enables the BS to serve more users within the time
unit while the privacy of each user is preserved. The fractional times and
beamforming vectors are jointly optimized to maximize the system's throughput.
An efficient path-following algorithm, which invokes a simple convex quadratic
program at each iteration, is proposed for the solution of this challenging
optimization problem. Numerical results confirm its versatility.Comment: IEEE Communications Letters (To Appear
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