384 research outputs found
Concave Switching in Single and Multihop Networks
Switched queueing networks model wireless networks, input queued switches and
numerous other networked communications systems. For single-hop networks, we
consider a {()-switch policy} which combines the MaxWeight policies
with bandwidth sharing networks -- a further well studied model of Internet
congestion. We prove the maximum stability property for this class of
randomized policies. Thus these policies have the same first order behavior as
the MaxWeight policies. However, for multihop networks some of these
generalized polices address a number of critical weakness of the
MaxWeight/BackPressure policies.
For multihop networks with fixed routing, we consider the Proportional
Scheduler (or (1,log)-policy). In this setting, the BackPressure policy is
maximum stable, but must maintain a queue for every route-destination, which
typically grows rapidly with a network's size. However, this proportionally
fair policy only needs to maintain a queue for each outgoing link, which is
typically bounded in number. As is common with Internet routing, by maintaining
per-link queueing each node only needs to know the next hop for each packet and
not its entire route. Further, in contrast to BackPressure, the Proportional
Scheduler does not compare downstream queue lengths to determine weights, only
local link information is required. This leads to greater potential for
decomposed implementations of the policy. Through a reduction argument and an
entropy argument, we demonstrate that, whilst maintaining substantially less
queueing overhead, the Proportional Scheduler achieves maximum throughput
stability.Comment: 28 page
Distributive Network Utility Maximization (NUM) over Time-Varying Fading Channels
Distributed network utility maximization (NUM) has received an increasing
intensity of interest over the past few years. Distributed solutions (e.g., the
primal-dual gradient method) have been intensively investigated under fading
channels. As such distributed solutions involve iterative updating and explicit
message passing, it is unrealistic to assume that the wireless channel remains
unchanged during the iterations. Unfortunately, the behavior of those
distributed solutions under time-varying channels is in general unknown. In
this paper, we shall investigate the convergence behavior and tracking errors
of the iterative primal-dual scaled gradient algorithm (PDSGA) with dynamic
scaling matrices (DSC) for solving distributive NUM problems under time-varying
fading channels. We shall also study a specific application example, namely the
multi-commodity flow control and multi-carrier power allocation problem in
multi-hop ad hoc networks. Our analysis shows that the PDSGA converges to a
limit region rather than a single point under the finite state Markov chain
(FSMC) fading channels. We also show that the order of growth of the tracking
errors is given by O(T/N), where T and N are the update interval and the
average sojourn time of the FSMC, respectively. Based on this analysis, we
derive a low complexity distributive adaptation algorithm for determining the
adaptive scaling matrices, which can be implemented distributively at each
transmitter. The numerical results show the superior performance of the
proposed dynamic scaling matrix algorithm over several baseline schemes, such
as the regular primal-dual gradient algorithm
Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying
We study the problem of channel pairing and power allocation in a
multichannel multihop relay network to enhance the end-to-end data rate. Both
amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are
considered. Given fixed power allocation to the channels, we show that channel
pairing over multiple hops can be decomposed into independent pairing problems
at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal,
where each relay pairs its incoming and outgoing channels by their SNR order.
For the joint optimization of channel pairing and power allocation under both
total and individual power constraints, we show that the problem can be
decoupled into two subproblems solved separately. This separation principle is
established by observing the equivalence between sorting SNRs and sorting
channel gains in the jointly optimal solution. It significantly reduces the
computational complexity in finding the jointly optimal solution. It follows
that the channel pairing problem in joint optimization can be again decomposed
into independent pairing problems at each relay based on sorted channel gains.
The solution for optimizing power allocation for DF relaying is also provided,
as well as an asymptotically optimal solution for AF relaying. Numerical
results are provided to demonstrate substantial performance gain of the jointly
optimal solution over some suboptimal alternatives. It is also observed that
more gain is obtained from optimal channel pairing than optimal power
allocation through judiciously exploiting the variation among multiple
channels. Impact of the variation of channel gain, the number of channels, and
the number of hops on the performance gain is also studied through numerical
examples.Comment: 15 pages. IEEE Transactions on Signal Processin
Jointly Optimal Channel Pairing and Power Allocation for Multichannel Multihop Relaying
We study the problem of channel pairing and power allocation in a
multichannel multihop relay network to enhance the end-to-end data rate. Both
amplify-and-forward (AF) and decode-and-forward (DF) relaying strategies are
considered. Given fixed power allocation to the channels, we show that channel
pairing over multiple hops can be decomposed into independent pairing problems
at each relay, and a sorted-SNR channel pairing strategy is sum-rate optimal,
where each relay pairs its incoming and outgoing channels by their SNR order.
For the joint optimization of channel pairing and power allocation under both
total and individual power constraints, we show that the problem can be
decoupled into two subproblems solved separately. This separation principle is
established by observing the equivalence between sorting SNRs and sorting
channel gains in the jointly optimal solution. It significantly reduces the
computational complexity in finding the jointly optimal solution. It follows
that the channel pairing problem in joint optimization can be again decomposed
into independent pairing problems at each relay based on sorted channel gains.
The solution for optimizing power allocation for DF relaying is also provided,
as well as an asymptotically optimal solution for AF relaying. Numerical
results are provided to demonstrate substantial performance gain of the jointly
optimal solution over some suboptimal alternatives. It is also observed that
more gain is obtained from optimal channel pairing than optimal power
allocation through judiciously exploiting the variation among multiple
channels. Impact of the variation of channel gain, the number of channels, and
the number of hops on the performance gain is also studied through numerical
examples.Comment: 15 pages. IEEE Transactions on Signal Processin
Decentralized Dynamic Hop Selection and Power Control in Cognitive Multi-hop Relay Systems
In this paper, we consider a cognitive multi-hop relay secondary user (SU)
system sharing the spectrum with some primary users (PU). The transmit power as
well as the hop selection of the cognitive relays can be dynamically adapted
according to the local (and causal) knowledge of the instantaneous channel
state information (CSI) in the multi-hop SU system. We shall determine a low
complexity, decentralized algorithm to maximize the average end-to-end
throughput of the SU system with dynamic spatial reuse. The problem is
challenging due to the decentralized requirement as well as the causality
constraint on the knowledge of CSI. Furthermore, the problem belongs to the
class of stochastic Network Utility Maximization (NUM) problems which is quite
challenging. We exploit the time-scale difference between the PU activity and
the CSI fluctuations and decompose the problem into a master problem and
subproblems. We derive an asymptotically optimal low complexity solution using
divide-and-conquer and illustrate that significant performance gain can be
obtained through dynamic hop selection and power control. The worst case
complexity and memory requirement of the proposed algorithm is O(M^2) and
O(M^3) respectively, where is the number of SUs
Stability conditions for a decentralised medium access algorithm: single- and multi-hop networks
We consider a decentralised multi-access algorithm, motivated primarily by
the control of transmissions in a wireless network. For a finite single-hop
network with arbitrary interference constraints we prove stochastic stability
under the natural conditions. For infinite and finite single-hop networks, we
obtain broad rate-stability conditions. We also consider symmetric finite
multi-hop networks and show that the natural condition is sufficient for
stochastic stability
Dynamic Time-domain Duplexing for Self-backhauled Millimeter Wave Cellular Networks
Millimeter wave (mmW) bands between 30 and 300 GHz have attracted
considerable attention for next-generation cellular networks due to vast
quantities of available spectrum and the possibility of very high-dimensional
antenna ar-rays. However, a key issue in these systems is range: mmW signals
are extremely vulnerable to shadowing and poor high-frequency propagation.
Multi-hop relaying is therefore a natural technology for such systems to
improve cell range and cell edge rates without the addition of wired access
points. This paper studies the problem of scheduling for a simple
infrastructure cellular relay system where communication between wired base
stations and User Equipment follow a hierarchical tree structure through fixed
relay nodes. Such a systems builds naturally on existing cellular mmW backhaul
by adding mmW in the access links. A key feature of the proposed system is that
TDD duplexing selections can be made on a link-by-link basis due to directional
isolation from other links. We devise an efficient, greedy algorithm for
centralized scheduling that maximizes network utility by jointly optimizing the
duplexing schedule and resources allocation for dense, relay-enhanced OFDMA/TDD
mmW networks. The proposed algorithm can dynamically adapt to loading, channel
conditions and traffic demands. Significant throughput gains and improved
resource utilization offered by our algorithm over the static,
globally-synchronized TDD patterns are demonstrated through simulations based
on empirically-derived channel models at 28 GHz.Comment: IEEE Workshop on Next Generation Backhaul/Fronthaul Networks -
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Outage Performance of Two-Hop OFDM Systems with Spatially Random Decode-and-Forward Relays
In this paper, we analyze the outage performance of different multicarrier
relay selection schemes for two-hop orthogonal frequency-division multiplexing
(OFDM) systems in a Poisson field of relays. In particular, special emphasis is
placed on decode-and-forward (DF) relay systems, equipped with bulk and
per-subcarrier selection schemes, respectively. The exact expressions for
outage probability are derived in integrals for general cases. In addition,
asymptotic expressions for outage probability in the high signal-to-noise ratio
(SNR) region in the finite circle relay distribution region are determined in
closed forms for both relay selection schemes. Also, the outage probabilities
for free space in the infinite relay distribution region are derived in closed
forms. Meanwhile, a series of important properties related to cooperative
systems in random networks are investigated, including diversity, outage
probability ratio of two selection schemes and optimization of the number of
subcarriers in terms of system throughput. All analysis is numerically verified
by simulations. Finally, a framework for analyzing the outage performance of
OFDM systems with spatially random relays is constructed, which can be easily
modified to analyze other similar cases with different forwarding protocols,
location distributions and/or channel conditions
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