86 research outputs found
Random Pilot and Data Access in Massive MIMO for Machine-type Communications
A massive MIMO system, represented by a base station with hundreds of
antennas, is capable of spatially multiplexing many devices and thus naturally
suited to serve dense crowds of wireless devices in emerging applications, such
as machine-type communications. Crowd scenarios pose new challenges in the
pilot-based acquisition of channel state information and call for pilot access
protocols that match the intermittent pattern of device activity. A joint pilot
assignment and data transmission protocol based on random access is proposed in
this paper for the uplink of a massive MIMO system. The protocol relies on the
averaging across multiple transmission slots of the pilot collision events that
result from the random access process. We derive new uplink sum rate
expressions that take pilot collisions, intermittent device activity, and
interference into account. Simplified bounds are obtained and used to optimize
the device activation probability and pilot length. A performance analysis
indicates how performance scales as a function of the number of antennas and
the transmission slot duration
Random Access for Massive MIMO Systems with Intra-Cell Pilot Contamination
Massive MIMO systems, where the base stations are equipped with hundreds of
antenna elements, are an attractive way to attain unprecedented spectral
efficiency in future wireless networks. In the "classical" massive MIMO
setting, the terminals are assumed fully loaded and a main impairment to the
performance comes from the inter-cell pilot contamination, i.e., interference
from terminals in neighboring cells using the same pilots as in the home cell.
However, when the terminals are active intermittently, it is viable to avoid
inter-cell contamination by pre-allocation of pilots, while same-cell terminals
use random access to select the allocated pilot sequences. This leads to the
problem of intra-cell pilot contamination. We propose a framework for random
access in massive MIMO networks and derive new uplink sum rate expressions that
take intra-cell pilot collisions, intermittent terminal activity, and
interference into account. We use these expressions to optimize the terminal
activation probability and pilot length
Grant-Free Massive MTC-Enabled Massive MIMO: A Compressive Sensing Approach
A key challenge of massive MTC (mMTC), is the joint detection of device
activity and decoding of data. The sparse characteristics of mMTC makes
compressed sensing (CS) approaches a promising solution to the device detection
problem. However, utilizing CS-based approaches for device detection along with
channel estimation, and using the acquired estimates for coherent data
transmission is suboptimal, especially when the goal is to convey only a few
bits of data.
First, we focus on the coherent transmission and demonstrate that it is
possible to obtain more accurate channel state information by combining
conventional estimators with CS-based techniques. Moreover, we illustrate that
even simple power control techniques can enhance the device detection
performance in mMTC setups.
Second, we devise a new non-coherent transmission scheme for mMTC and
specifically for grant-free random access. We design an algorithm that jointly
detects device activity along with embedded information bits. The approach
leverages elements from the approximate message passing (AMP) algorithm, and
exploits the structured sparsity introduced by the non-coherent transmission
scheme. Our analysis reveals that the proposed approach has superior
performance compared to application of the original AMP approach.Comment: Submitted to IEEE Transactions on Communication
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