111 research outputs found
Delay Constrained Throughput Analysis of a Correlated MIMO Wireless Channel
The maximum traffic arrival rate at the network for a given delay guarantee
(delay constrained throughput) has been well studied for wired channels.
However, few results are available for wireless channels, especially when
multiple antennas are employed at the transmitter and receiver. In this work,
we analyze the network delay constrained throughput of a multiple input
multiple output (MIMO) wireless channel with time-varying spatial correlation.
The MIMO channel is modeled via its virtual representation, where the
individual spatial paths between the antenna pairs are Gilbert-Elliot channels.
The whole system is then described by a K-State Markov chain, where K depends
upon the degree of freedom (DOF) of the channel. We prove that the DOF based
modeling is indeed accurate. Furthermore, we study the impact of the delay
requirements at the network layer, violation probability and the number of
antennas on the throughput under different fading speeds and signal strength.Comment: Submitted to ICCCN 2011, 8 pages, 5 figure
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On distributed scheduling for wireless networks with time-varying channels
textWireless scheduling is a fundamental problem in wireless networks that involves scheduling transmissions of multiple users in order to support data flows with as high rates as possible. This problem was first addressed by Tassuilas and Ephremides, resulting in the celebrated Back-Pressure network scheduling algorithm. This algorithm schedules network links to maximize throughput in an opportunistic fashion using instantaneous network state information (NSI), i.e., queue and channel state knowledge across the entire network. However, the Back-Pressure (BP) algorithm suffers from various drawbacks - (a) it requires knowledge of instantaneous NSI from the whole network, i.e. feedback about time-varying channel and queue states from all links of the network, (b) the algorithm requires solving a global optimization problem at each time to determine the schedule, making it highly centralized. Further, Back-pressure algorithm was originally designed for wireless networks where interference is modeled using protocol interference model. As recent break-throughs in full-duplex communications and interference cancelation techniques provide greatly increased capacity and scheduling flexibility, it is not clear how BP algorithm can be modified to improve the data rates and reduce the delay. In this thesis, we address the drawbacks of Back-Pressure algorithm to some extent. In particular, our first work provides a new scheduling algorithm (similar to BP) that allows users to make individual decisions (distributed) based on heterogeneously delayed network state information (NSI). Regarding the complexity issue, in our second work, we analyze the performance of the greedy version of BP algorithm, known as Greedy Maximal Scheduling (GMS) and understand the effect of channel variations on the performance of GMS. In particular, we characterize the efficiency ratio of GMS in wireless networks with fading. In our third and fourth work, we propose and analyze new scheduling algorithms that can benefit from new advancements in interference cancelation techniques.Electrical and Computer Engineerin
Studies on Trade-off Between Throughput and Reliability in Wireless Systems
In the first part of the thesis, we study the trade-off between the transmission reliability and data
rate in high signal-to-noise ratio regime in ad-hoc wireless
networks. Bandwidth allocation plays a significant role in this
trade-off, since dividing bandwidth reduces the number of users on
each band and consequently decreases the interference level, however
it also decreases the data rate. Noting that the interference power
is substantially influenced by the network density, this trade-off
introduces a measure for appropriate bandwidth allocation among
users considering the network density. The diversity-multiplexing trade-off
is derived for a one-dimensional regular ad-hoc
network.
In the second part of the thesis, we study the performance of point-to-point and broadcast systems
with partial channel state information at the transmitter in a time-varying environment.
First, the capacity of time-varying channels with
periodic feedback at the transmitter is evaluated. It is assumed that the
channel state information is perfectly known at the receiver
and is fed back to the transmitter at the regular time-intervals. The system capacity is investigated in two cases: i) finite state Markov channel, and
ii) additive white Gaussian noise channel with time-correlated fading. In a multiuser scenario, we consider a downlink system in which a single-antenna base
station communicates with single antenna users, over a
time-correlated fading channel. It is assumed that
channel state information is perfectly known at each receiver, while
the rate of channel variations and the fading
gain at the beginning of each frame are known to the transmitter. The asymptotic throughput of the
scheduling that transmits to the user with the maximum signal to
noise ratio is examined applying variable code rate and/or variable
codeword length signaling. It is shown that by selecting a fixed codeword
length for all users, the order of the maximum possible throughput (corresponding to quasi-static fading) is achieved
Scheduling and Codeword Length Optimization in Time Varying Wireless Networks
In this paper, a downlink scenario in which a single-antenna base station
communicates with K single antenna users, over a time-correlated fading
channel, is considered. It is assumed that channel state information is
perfectly known at each receiver, while the statistical characteristics of the
fading process and the fading gain at the beginning of each frame are known to
the transmitter. By evaluating the random coding error exponent of the
time-correlated fading channel, it is shown that there is an optimal codeword
length which maximizes the throughput. The throughput of the conventional
scheduling that transmits to the user with the maximum signal to noise ratio is
examined using both fixed length codewords and variable length codewords.
Although optimizing the codeword length improves the performance, it is shown
that using the conventional scheduling, the gap between the achievable
throughput and the maximum possible throughput of the system tends to infinity
as K goes to infinity. A simple scheduling that considers both the signal to
noise ratio and the channel time variation is proposed. It is shown that by
using this scheduling, the gap between the achievable throughput and the
maximum throughput of the system approaches zero
Effects of Mobility on User Energy Consumption and Total Throughput in a Massive MIMO System
Macroscopic mobility of wireless users is important to determine the
performance and energy effciency of a wireless network, because of the temporal
correlations it introduces in the consumed power and throughput. In this work
we introduce a methodology that obtains the long time statistics of such
metrics in a network. After describing the general approach, we present a
specific example of the uplink channel of a mobile user in the vicinity of a
massive MIMO base-station antenna array. To guarantee a fixed SINR and rate,
the user inverts the path-loss channel power, while moving around in the cell.
To calculate the long time distribution of the consumed energy of the user, we
assume his movement follows a Brownian motion, and then map the problem to the
solution of the minimum eigenvalue of a partial differential equation, which
can be solved either analytically, or numerically very fast. We also treat the
throughput of a single user. We then discuss the results and how they can be
generalized if the mobility is assumed to be a Levy random walk. We also
provide a roadmap to use this technique when one considers multiple users and
base stations.Comment: Submitted to ITW 201
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