1,330 research outputs found
Synchronous wearable wireless body sensor network composed of autonomous textile nodes
A novel, fully-autonomous, wearable, wireless sensor network is presented, where each flexible textile node performs cooperative synchronous acquisition and distributed event detection. Computationally efficient situational-awareness algorithms are implemented on the low-power microcontroller present on each flexible node. The detected events are wirelessly transmitted to a base station, directly, as well as forwarded by other on-body nodes. For each node, a dual-polarized textile patch antenna serves as a platform for the flexible electronic circuitry. Therefore, the system is particularly suitable for comfortable and unobtrusive integration into garments. In the meantime, polarization diversity can be exploited to improve the reliability and energy-efficiency of the wireless transmission. Extensive experiments in realistic conditions have demonstrated that this new autonomous, body-centric, textile-antenna, wireless sensor network is able to correctly detect different operating conditions of a firefighter during an intervention. By relying on four network nodes integrated into the protective garment, this functionality is implemented locally, on the body, and in real time. In addition, the received sensor data are reliably transferred to a central access point at the command post, for more detailed and more comprehensive real-time visualization. This information provides coordinators and commanders with situational awareness of the entire rescue operation. A statistical analysis of measured on-body node-to-node, as well as off-body person-to-person channels is included, confirming the reliability of the communication system
Sparse Array Beamformer Design via ADMM
In this paper, we devise a sparse array design algorithm for adaptive
beamforming. Our strategy is based on finding a sparse beamformer weight to
maximize the output signal-to-interference-plus-noise ratio (SINR). The
proposed method utilizes the alternating direction method of multipliers
(ADMM), and admits closed-form solutions at each ADMM iteration. The algorithm
convergence properties are analyzed by showing the monotonicity and boundedness
of the augmented Lagrangian function. In addition, we prove that the proposed
algorithm converges to the set of Karush-Kuhn-Tucker stationary points.
Numerical results exhibit its excellent performance, which is comparable to
that of the exhaustive search approach, slightly better than those of the
state-of-the-art solvers, including the semidefinite relaxation (SDR), its
variant (SDR-V), and the successive convex approximation (SCA) approaches, and
significantly outperforms several other sparse array design strategies, in
terms of output SINR. Moreover, the proposed ADMM algorithm outperforms the
SDR, SDR-V, and SCA methods, in terms of computational complexity.Comment: Accepted by IEEE Transactions on Signal Processin
Adaptive Sparse Array Beamformer Design by Regularized Complementary Antenna Switching
In this work, we propose a novel strategy of adaptive sparse array beamformer
design, referred to as regularized complementary antenna switching (RCAS), to
swiftly adapt both array configuration and excitation weights in accordance to
the dynamic environment for enhancing interference suppression. In order to
achieve an implementable design of array reconfiguration, the RCAS is conducted
in the framework of regularized antenna switching, whereby the full array
aperture is collectively divided into separate groups and only one antenna in
each group is switched on to connect with the processing channel. A set of
deterministic complementary sparse arrays with good quiescent beampatterns is
first designed by RCAS and full array data is collected by switching among them
while maintaining resilient interference suppression. Subsequently, adaptive
sparse array tailored for the specific environment is calculated and
reconfigured based on the information extracted from the full array data. The
RCAS is devised as an exclusive cardinality-constrained optimization, which is
reformulated by introducing an auxiliary variable combined with a piece-wise
linear function to approximate the -norm function. A regularization
formulation is proposed to solve the problem iteratively and eliminate the
requirement of feasible initial search point. A rigorous theoretical analysis
is conducted, which proves that the proposed algorithm is essentially an
equivalent transformation of the original cardinality-constrained optimization.
Simulation results validate the effectiveness of the proposed RCAS strategy
Joint signal detection and channel estimation in rank-deficient MIMO systems
L'évolution de la prospère famille des standards 802.11 a encouragé le développement des technologies appliquées aux réseaux locaux sans fil (WLANs). Pour faire face à la toujours croissante nécessité de rendre possible les communications à très haut débit, les systèmes à antennes multiples (MIMO) sont une solution viable. Ils ont l'avantage d'accroître le débit de transmission sans avoir recours à plus de puissance ou de largeur de bande. Cependant, l'industrie hésite encore à augmenter le nombre d'antennes des portables et des accésoires sans fil. De plus, à l'intérieur des bâtiments, la déficience de rang de la matrice de canal peut se produire dû à la nature de la dispersion des parcours de propagation, ce phénomène est aussi occasionné à l'extérieur par de longues distances de transmission. Ce projet est motivé par les raisons décrites antérieurement, il se veut un étude sur la viabilité des transcepteurs sans fil à large bande capables de régulariser la déficience de rang du canal sans fil. On vise le développement des techniques capables de séparer M signaux co-canal, même avec une seule antenne et à faire une estimation précise du canal. Les solutions décrites dans ce document cherchent à surmonter les difficultés posées par le medium aux transcepteurs sans fil à large bande. Le résultat de cette étude est un algorithme transcepteur approprié aux systèmes MIMO à rang déficient
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