1,971 research outputs found
On the Throughput of Large-but-Finite MIMO Networks using Schedulers
This paper studies the sum throughput of the {multi-user}
multiple-input-single-output (MISO) networks in the cases with large but finite
number of transmit antennas and users. Considering continuous and bursty
communication scenarios with different users' data request probabilities, we
derive quasi-closed-form expressions for the maximum achievable throughput of
the networks using optimal schedulers. The results are obtained in various
cases with different levels of interference cancellation. Also, we develop an
efficient scheduling scheme using genetic algorithms (GAs), and evaluate the
effect of different parameters, such as channel/precoding models, number of
antennas/users, scheduling costs and power amplifiers' efficiency, on the
system performance. Finally, we use the recent results on the achievable rates
of finite block-length codes to analyze the system performance in the cases
with short packets. As demonstrated, the proposed GA-based scheduler reaches
(almost) the same throughput as in the exhaustive search-based optimal
scheduler, with substantially less implementation complexity. Moreover, the
power amplifiers' inefficiency and the scheduling delay affect the performance
of the scheduling-based systems significantly
To Stay Or To Switch: Multiuser Dynamic Channel Access
In this paper we study opportunistic spectrum access (OSA) policies in a
multiuser multichannel random access cognitive radio network, where users
perform channel probing and switching in order to obtain better channel
condition or higher instantaneous transmission quality. However, unlikely many
prior works in this area, including those on channel probing and switching
policies for a single user to exploit spectral diversity, and on probing and
access policies for multiple users over a single channel to exploit temporal
and multiuser diversity, in this study we consider the collective switching of
multiple users over multiple channels. In addition, we consider finite
arrivals, i.e., users are not assumed to always have data to send and demand
for channel follow a certain arrival process. Under such a scenario, the users'
ability to opportunistically exploit temporal diversity (the temporal variation
in channel quality over a single channel) and spectral diversity (quality
variation across multiple channels at a given time) is greatly affected by the
level of congestion in the system. We investigate the optimal decision process
in this case, and evaluate the extent to which congestion affects potential
gains from opportunistic dynamic channel switching
Opportunistic Relaying in Wireless Networks
Relay networks having source-to-destination pairs and half-duplex
relays, all operating in the same frequency band in the presence of block
fading, are analyzed. This setup has attracted significant attention and
several relaying protocols have been reported in the literature. However, most
of the proposed solutions require either centrally coordinated scheduling or
detailed channel state information (CSI) at the transmitter side. Here, an
opportunistic relaying scheme is proposed, which alleviates these limitations.
The scheme entails a two-hop communication protocol, in which sources
communicate with destinations only through half-duplex relays. The key idea is
to schedule at each hop only a subset of nodes that can benefit from
\emph{multiuser diversity}. To select the source and destination nodes for each
hop, it requires only CSI at receivers (relays for the first hop, and
destination nodes for the second hop) and an integer-value CSI feedback to the
transmitters. For the case when is large and is fixed, it is shown that
the proposed scheme achieves a system throughput of bits/s/Hz. In
contrast, the information-theoretic upper bound of bits/s/Hz
is achievable only with more demanding CSI assumptions and cooperation between
the relays. Furthermore, it is shown that, under the condition that the product
of block duration and system bandwidth scales faster than , the
achievable throughput of the proposed scheme scales as .
Notably, this is proven to be the optimal throughput scaling even if
centralized scheduling is allowed, thus proving the optimality of the proposed
scheme in the scaling law sense.Comment: 17 pages, 8 figures, To appear in IEEE Transactions on Information
Theor
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