335 research outputs found
Multiuser Scheduling in a Markov-modeled Downlink using Randomly Delayed ARQ Feedback
We focus on the downlink of a cellular system, which corresponds to the bulk
of the data transfer in such wireless systems. We address the problem of
opportunistic multiuser scheduling under imperfect channel state information,
by exploiting the memory inherent in the channel. In our setting, the channel
between the base station and each user is modeled by a two-state Markov chain
and the scheduled user sends back an ARQ feedback signal that arrives at the
scheduler with a random delay that is i.i.d across users and time. The
scheduler indirectly estimates the channel via accumulated delayed-ARQ feedback
and uses this information to make scheduling decisions. We formulate a
throughput maximization problem as a partially observable Markov decision
process (POMDP). For the case of two users in the system, we show that a greedy
policy is sum throughput optimal for any distribution on the ARQ feedback
delay. For the case of more than two users, we prove that the greedy policy is
suboptimal and demonstrate, via numerical studies, that it has near optimal
performance. We show that the greedy policy can be implemented by a simple
algorithm that does not require the statistics of the underlying Markov channel
or the ARQ feedback delay, thus making it robust against errors in system
parameter estimation. Establishing an equivalence between the two-user system
and a genie-aided system, we obtain a simple closed form expression for the sum
capacity of the Markov-modeled downlink. We further derive inner and outer
bounds on the capacity region of the Markov-modeled downlink and tighten these
bounds for special cases of the system parameters.Comment: Contains 22 pages, 6 figures and 8 tables; revised version including
additional analytical and numerical results; work submitted, Feb 2010, to
IEEE Transactions on Information Theory, revised April 2011; authors can be
reached at [email protected]/[email protected]/[email protected]
Information Exchange Limits in Cooperative MIMO Networks
Concurrent presence of inter-cell and intra-cell interferences constitutes a
major impediment to reliable downlink transmission in multi-cell multiuser
networks. Harnessing such interferences largely hinges on two levels of
information exchange in the network: one from the users to the base-stations
(feedback) and the other one among the base-stations (cooperation). We
demonstrate that exchanging a finite number of bits across the network, in the
form of feedback and cooperation, is adequate for achieving the optimal
capacity scaling. We also show that the average level of information exchange
is independent of the number of users in the network. This level of information
exchange is considerably less than that required by the existing coordination
strategies which necessitate exchanging infinite bits across the network for
achieving the optimal sum-rate capacity scaling. The results provided rely on a
constructive proof.Comment: 35 pages, 5 figur
Multiuser MAC Schemes for High-Throughput IEEE 802.11n/ac WLANs
In the last decade, the Wireless Local Area Network (WLAN) market has been experiencing
an impressive growth that began with the broad acceptance of the IEEE 802.11 standard [1].
Given the widespread deployment of WLANs and the increasing requirements of multimedia
applications, the need for high capacity and enhanced reliability has become imperative.
Multiple-Input Multiple-Output (MIMO) technology and its single receiving antenna version,
MISO (Multiple-Input Single-Output (MISO), promise a signi¿cant performance boost and
have been incorporated in the emerging IEEE 802.11n standard.Peer ReviewedPostprint (published version
Multiuser Diversity Gain in Cognitive Networks
Dynamic allocation of resources to the \emph{best} link in large multiuser
networks offers considerable improvement in spectral efficiency. This gain,
often referred to as \emph{multiuser diversity gain}, can be cast as
double-logarithmic growth of the network throughput with the number of users.
In this paper we consider large cognitive networks granted concurrent spectrum
access with license-holding users. The primary network affords to share its
under-utilized spectrum bands with the secondary users. We assess the optimal
multiuser diversity gain in the cognitive networks by quantifying how the
sum-rate throughput of the network scales with the number of secondary users.
For this purpose we look at the optimal pairing of spectrum bands and secondary
users, which is supervised by a central entity fully aware of the instantaneous
channel conditions, and show that the throughput of the cognitive network
scales double-logarithmically with the number of secondary users () and
linearly with the number of available spectrum bands (), i.e., . We then propose a \emph{distributed} spectrum allocation scheme, which does
not necessitate a central controller or any information exchange between
different secondary users and still obeys the optimal throughput scaling law.
This scheme requires that \emph{some} secondary transmitter-receiver pairs
exchange information bits among themselves. We also show that the
aggregate amount of information exchange between secondary transmitter-receiver
pairs is {\em asymptotically} equal to . Finally, we show that our
distributed scheme guarantees fairness among the secondary users, meaning that
they are equally likely to get access to an available spectrum band.Comment: 32 pages, 3 figures, to appear in the IEEE/ACM Transactions on
Networkin
Performance Analysis of Heterogeneous Feedback Design in an OFDMA Downlink with Partial and Imperfect Feedback
Current OFDMA systems group resource blocks into subband to form the basic
feedback unit. Homogeneous feedback design with a common subband size is not
aware of the heterogeneous channel statistics among users. Under a general
correlated channel model, we demonstrate the gain of matching the subband size
to the underlying channel statistics motivating heterogeneous feedback design
with different subband sizes and feedback resources across clusters of users.
Employing the best-M partial feedback strategy, users with smaller subband size
would convey more partial feedback to match the frequency selectivity. In order
to develop an analytical framework to investigate the impact of partial
feedback and potential imperfections, we leverage the multi-cluster subband
fading model. The perfect feedback scenario is thoroughly analyzed, and the
closed form expression for the average sum rate is derived for the
heterogeneous partial feedback system. We proceed to examine the effect of
imperfections due to channel estimation error and feedback delay, which leads
to additional consideration of system outage. Two transmission strategies: the
fix rate and the variable rate, are considered for the outage analysis. We also
investigate how to adapt to the imperfections in order to maximize the average
goodput under heterogeneous partial feedback.Comment: To appear in IEEE Trans. on Signal Processin
Can One Achieve Multiuser Diversity in Uplink Multi-Cell Networks?
We introduce a distributed opportunistic scheduling (DOS) strategy, based on
two pre-determined thresholds, for uplink -cell networks with time-invariant
channel coefficients. Each base station (BS) opportunistically selects a mobile
station (MS) who has a large signal strength of the desired channel link among
a set of MSs generating a sufficiently small interference to other BSs. Then,
performance on the achievable throughput scaling law is analyzed. As our main
result, it is shown that the achievable sum-rate scales as
in a high signal-to-noise ratio (SNR) regime, if the
total number of users in a cell, , scales faster than
for a constant . This
result indicates that the proposed scheme achieves the multiuser diversity gain
as well as the degrees-of-freedom gain even under multi-cell environments.
Simulation results show that the DOS provides a better sum-rate throughput over
conventional schemes.Comment: 11 pages, 3 figures, 2 tables, to appear in IEEE Transactions on
Communication
Downlink SDMA with Limited Feedback in Interference-Limited Wireless Networks
The tremendous capacity gains promised by space division multiple access
(SDMA) depend critically on the accuracy of the transmit channel state
information. In the broadcast channel, even without any network interference,
it is known that such gains collapse due to interstream interference if the
feedback is delayed or low rate. In this paper, we investigate SDMA in the
presence of interference from many other simultaneously active transmitters
distributed randomly over the network. In particular we consider zero-forcing
beamforming in a decentralized (ad hoc) network where each receiver provides
feedback to its respective transmitter. We derive closed-form expressions for
the outage probability, network throughput, transmission capacity, and average
achievable rate and go on to quantify the degradation in network performance
due to residual self-interference as a function of key system parameters. One
particular finding is that as in the classical broadcast channel, the per-user
feedback rate must increase linearly with the number of transmit antennas and
SINR (in dB) for the full multiplexing gains to be preserved with limited
feedback. We derive the throughput-maximizing number of streams, establishing
that single-stream transmission is optimal in most practically relevant
settings. In short, SDMA does not appear to be a prudent design choice for
interference-limited wireless networks.Comment: Submitted to IEEE Transactions on Wireless Communication
- …