151 research outputs found
Compressed Sensing Based Multi-User Millimeter Wave Systems: How Many Measurements Are Needed?
Millimeter wave (mmWave) systems will likely employ directional beamforming
with large antenna arrays at both the transmitters and receivers. Acquiring
channel knowledge to design these beamformers, however, is challenging due to
the large antenna arrays and small signal-to-noise ratio before beamforming. In
this paper, we propose and evaluate a downlink system operation for multi-user
mmWave systems based on compressed sensing channel estimation and conjugate
analog beamforming. Adopting the achievable sum-rate as a performance metric,
we show how many compressed sensing measurements are needed to approach the
perfect channel knowledge performance. The results illustrate that the proposed
algorithm requires an order of magnitude less training overhead compared with
traditional lower-frequency solutions, while employing mmWave-suitable
hardware. They also show that the number of measurements need to be optimized
to handle the trade-off between the channel estimate quality and the training
overhead.Comment: IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP) 201
Iterative Soft/Hard Thresholding with Homotopy Continuation for Sparse Recovery
In this note, we analyze an iterative soft / hard thresholding algorithm with
homotopy continuation for recovering a sparse signal from noisy data
of a noise level . Under suitable regularity and sparsity conditions,
we design a path along which the algorithm can find a solution which
admits a sharp reconstruction error with an iteration complexity , where and are problem dimensionality and
controls the length of the path. Numerical examples are given to illustrate its
performance.Comment: 5 pages, 4 figure
User Activity Detection in Massive Random Access: Compressed Sensing vs. Coded Slotted ALOHA
Machine-type communication services in mobile cel- lular systems are
currently evolving with an aim to efficiently address a massive-scale user
access to the system. One of the key problems in this respect is to efficiently
identify active users in order to allocate them resources for the subsequent
transmissions. In this paper, we examine two recently suggested approaches for
user activity detection: compressed-sensing (CS) and coded slotted ALOHA (CSA),
and provide their comparison in terms of performance vs resource utilization.
Our preliminary results show that CS-based approach is able to provide the
target user activity detection performance with less overall system resource
utilization. However, this comes at a price of lower energy- efficiency per
user, as compared to CSA-based approach.Comment: Accepted for presentation at IEEE SPAWC 201
Coherence-Based Performance Guarantees of Orthogonal Matching Pursuit
In this paper, we present coherence-based performance guarantees of
Orthogonal Matching Pursuit (OMP) for both support recovery and signal
reconstruction of sparse signals when the measurements are corrupted by noise.
In particular, two variants of OMP either with known sparsity level or with a
stopping rule are analyzed. It is shown that if the measurement matrix
satisfies the strong coherence property, then with
, OMP will recover a -sparse signal with high
probability. In particular, the performance guarantees obtained here separate
the properties required of the measurement matrix from the properties required
of the signal, which depends critically on the minimum signal to noise ratio
rather than the power profiles of the signal. We also provide performance
guarantees for partial support recovery. Comparisons are given with other
performance guarantees for OMP using worst-case analysis and the sorted one
step thresholding algorithm.Comment: appeared at 2012 Allerton conferenc
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