39,602 research outputs found
Mutual Successive Interference Cancellation Strategies in NOMA for Enhancing the Spectral Efficiency of CoMP Systems
International audienceThe densification of mobile networks should enable the fifth generation (5G) mobile networks to cope with the ever increasing demand for higher rate traffic, reduced latency, and improved reliability. The large scale deployment of small cells and distributed antenna systems in heterogeneous environments will require more elaborate interference mitigating techniques to increase spectral efficiency and to help unlock the expected performance leaps from the new network topologies. Coordinated multi-point (CoMP) is the most advanced framework for interference management enabling the cooperation between base stations to mitigate inter-cell interference and boost cell-edge user performance. In this paper, we study the combination of CoMP with mutual SIC, an interference cancellation technique based on power-domain non-orthogonal multiple access (NOMA) that enables multiplexed users to simultaneously cancel their corresponding interfering signals. A highly efficient inter-cell interference cancellation scheme is then devised, that can encompass several deployment configurations and coordination techniques. The obtained results prove the superiority of this approach compared to conventional NOMA-CoMP systems
Distributed space time block coding in asynchronous cooperative relay networks
The design and analysis of various distributed space time block coding
schemes for asynchronous cooperative relay networks is considered
in this thesis. Rayleigh frequency flat fading channels are assumed to
model the links in the networks, and interference suppression techniques
together with an orthogonal frequency division multiplexing type transmission
approach are employed to mitigate the synchronization errors
at the destination node induced by the different delays through the
relay nodes.
Closed-loop space time block coding is first considered in the context
of decode-and-forward (regenerative) networks. In particular, quasi orthogonal
and extended orthogonal coding techniques are employed for
transmission from four relay nodes and parallel interference cancellation
detection is exploited to mitigate synchronization errors. Availability
of a direct link between the source and destination nodes is studied,
and a new Alamouti space time block coding technique with parallel
interference cancellation detection which does not require such a direct
link connection and employs two relay nodes is proposed. Outer
coding is then added to gain further improvement in end-to-end performance
and amplify-and-forward (non regenerative) type networks
together with distributed space time coding are considered to reduce
relay node complexity.
Novel detection schemes are then proposed for decode-and-forward
networks with closed-loop extended orthogonal coding which reduce
the computational complexity of the parallel interference cancellation.
Both sub-optimum and near-optimum detectors are presented for relay
nodes with single or dual antennas. End-to-end bit error rate simulations
confirm the potential of the approaches and their ability to
mitigate synchronization errors. A relay selection approach is also formulated
which maximizes spatial diversity gain and attains robustness
to timing errors.
Finally, a new closed-loop distributed extended orthogonal space
time block coding solution for amplify-and-forward type networks which
minimizes the number of feedback bits by using a cyclic rotation phase
is presented. This approach utilizes an orthogonal frequency division
multiplexing type transmission structure with a cyclic prefix to mitigate
synchronization errors. End-to-end bit error performance evaluations
verify the efficacy of the scheme and its success in overcoming synchronization
errors
ALOHA Random Access that Operates as a Rateless Code
Various applications of wireless Machine-to-Machine (M2M) communications have
rekindled the research interest in random access protocols, suitable to support
a large number of connected devices. Slotted ALOHA and its derivatives
represent a simple solution for distributed random access in wireless networks.
Recently, a framed version of slotted ALOHA gained renewed interest due to the
incorporation of successive interference cancellation (SIC) in the scheme,
which resulted in substantially higher throughputs. Based on similar principles
and inspired by the rateless coding paradigm, a frameless approach for
distributed random access in slotted ALOHA framework is described in this
paper. The proposed approach shares an operational analogy with rateless
coding, expressed both through the user access strategy and the adaptive length
of the contention period, with the objective to end the contention when the
instantaneous throughput is maximized. The paper presents the related analysis,
providing heuristic criteria for terminating the contention period and showing
that very high throughputs can be achieved, even for a low number for
contending users. The demonstrated results potentially have more direct
practical implications compared to the approaches for coded random access that
lead to high throughputs only asymptotically.Comment: Revised version submitted to IEEE Transactions on Communication
Distributed space time block coding and application in cooperative cognitive relay networks
The design and analysis of various distributed space time block coding
schemes for cooperative relay networks is considered in this thesis.
Rayleigh frequency flat and selective fading channels are assumed to
model the links in the networks, and interference suppression techniques
together with an orthogonal frequency division multiplexing (OFDM)
type transmission approach are employed to mitigate synchronization
errors at the destination node induced by the different delays through
the relay nodes.
Closed-loop space time block coding is first considered in the context
of decode-and-forward (regenerative) networks. In particular, quasi orthogonal
and extended orthogonal coding techniques are employed for
transmission from four relay nodes and parallel interference cancellation
detection is exploited to mitigate synchronization errors. Availability
of a direct link between the source and destination nodes is studied.
Outer coding is then added to gain further improvement in end-to-end
performance and amplify-and-forward (non regenerative) type networks
together with distributed space time coding are considered to reduce
relay node complexity. A novel detection scheme is then proposed
for decode-and-forward and amplify-and-forward networks with closed-loop
extended orthogonal coding and closed-loop quasi-orthogonal coding
which reduce the computational complexity of the parallel interference cancellation. The near-optimum detector is presented for relay
nodes with single or dual antennas. End-to-end bit error rate simulations
confirm the potential of the approach and its ability to mitigate
synchronization errors
Effective Capacity in Broadcast Channels with Arbitrary Inputs
We consider a broadcast scenario where one transmitter communicates with two
receivers under quality-of-service constraints. The transmitter initially
employs superposition coding strategies with arbitrarily distributed signals
and sends data to both receivers. Regarding the channel state conditions, the
receivers perform successive interference cancellation to decode their own
data. We express the effective capacity region that provides the maximum
allowable sustainable data arrival rate region at the transmitter buffer or
buffers. Given an average transmission power limit, we provide a two-step
approach to obtain the optimal power allocation policies that maximize the
effective capacity region. Then, we characterize the optimal decoding regions
at the receivers in the space spanned by the channel fading power values. We
finally substantiate our results with numerical presentations.Comment: This paper will appear in 14th International Conference on
Wired&Wireless Internet Communications (WWIC
Integer-forcing in multiterminal coding: uplink-downlink duality and source-channel duality
Interference is considered to be a major obstacle to wireless communication. Popular approaches, such as the zero-forcing receiver in MIMO (multiple-input and multiple-output) multiple-access channel (MAC) and zero-forcing (ZF) beamforming in MIMO broadcast channel (BC), eliminate the interference first and decode each codeword separately using a conventional single-user decoder. Recently, a transceiver architecture called integer-forcing (IF) has been proposed in the context of the MIMO Gaussian multiple-access channel to exploit integer-linear combinations of the codewords. Instead of treating other codewords as interference, the integer-forcing approach decodes linear combinations of the codewords from different users and solves for desired codewords. Integer-forcing can closely approach the performance of the optimal joint maximum likelihood decoder. An advanced version called successive integer-forcing can achieve the sum capacity of the MIMO MAC channel. Several extensions of integer-forcing have been developed in various scenarios, such as integer-forcing for the Gaussian MIMO broadcast channel, integer-forcing for Gaussian distributed source coding and integer-forcing interference alignment for the Gaussian interference channel.
This dissertation demonstrates duality relationships for integer-forcing among three different channel models. We explore in detail two distinct duality types in this thesis: uplink-downlink duality and source-channel duality. Uplink-downlink duality is established for integer-forcing between the Gaussian MIMO multiple-access channel and its dual Gaussian MIMO broadcast channel. We show that under a total power constraint, integer-forcing can achieve the same sum rate in both cases. We further develop a dirty-paper integer-forcing scheme for the Gaussian MIMO BC and show an uplink-downlink duality with successive integer-forcing for the Gaussian MIMO MAC. The source-channel duality is established for integer-forcing between the Gaussian MIMO multiple-access channel and its dual Gaussian distributed source coding problem. We extend previous results for integer-forcing source coding to allow for successive cancellation. For integer-forcing without successive cancellation in both channel coding and source coding, we show the rates in two scenarios lie within a constant gap of one another. We further show that there exists a successive cancellation scheme such that both integer-forcing channel coding and integer-forcing source coding achieve the same rate tuple
Machine Learning Applications in Spacecraft State and Environment Estimation
There are some problems in spacecraft systems engineering with highly non-linear characteristics and noise where traditional nonlinear estimation techniques fail to yield accurate results. In this thesis, we consider approaching two such problems using kernel methods in machine learning. First, we present a novel formulation and solution to orbit determination of spacecraft and spacecraft groups which can be applied with very weakly observable and highly noisy scenarios. We present a ground station network architecture that can perform orbit determination using Doppler-only observations over the network. Second, we present a machine learning solution to the spacecraft magnetic field interference cancellation problem using distributed magnetometers paving the way for space magnetometry with boom-less CubeSats.
We present an approach to orbit determination under very broad conditions that are satisfied for n-body problems. We show that domain generalization and distribution regression techniques can learn to estimate orbits of a group of satellites and identify individual satellites especially with prior understanding of correlations between orbits and provide asymptotic convergence conditions. The approach presented requires only observability of the dynamical system and visibility of the spacecraft and is particularly useful for autonomous spacecraft operations using low-cost ground stations or sensors. With the absence of linear region constraints in the proposed method, we are able to identify orbits that are 800 km apart and reduce orbit uncertainty by 92.5% to under 60 km with noisy Doppler-only measurements.
We present an architecture for collaborative orbit determination using networked ground stations. We focus on clusters of satellites deployed in low Earth orbit and measurements of their Doppler-shifted transmissions made by low-gain antenna systems in a software-defined federated ground station network. We develop a network architecture enabling scheduling and tracking with uncertain orbit information. For the proposed network, we also present scheduling and coordinated tracking algorithms for tracking with the purpose of generating measurements for orbit determination. We validate our algorithms and architecture with its application to high fidelity simulations of different networked orbit determination scenarios. We demonstrate how these low-cost ground stations can be used to provide accurate and timely orbital tracking information for large satellite deployments, which is something that remains a challenge for current tracking systems.
Last, we present a novel approach and algorithm to the problem of magnetic field interference cancellation of time-varying interference using distributed magnetometers and spacecraft telemetry with particular emphasis on the computational and power requirements of CubeSats. The spacecraft magnetic field interference cancellation problem involves estimation of noise when the number of interfering sources far exceed the number of sensors required to decouple the noise from the signal. The proposed approach models this as a contextual bandit learning problem and the proposed algorithm learns to identify the optimal low-noise combination of distributed magnetometers based on indirect information gained on spacecraft currents through telemetry. Experimental results based on on-orbit spacecraft telemetry shows a 50% reduction in interference compared to the best magnetometer.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147688/1/srinag_1.pd
Distributed MIMO Interference Cancellation for Interfering Wireless Networks: Protocol and Initial Simulation
In this report, the problem of interference in dense wireless network deployments is addressed. Two example scenarios are: 1) overlapping basic service sets (OBSSes) in wireless LAN deployments, and 2) interference among close-by femtocells.
The proposed approach is to exploit the interference cancellation
and spatial multiplexing capabilities of multiple-input multiple-
output (MIMO) links to mitigate interference and improve the
performance of such networks. Both semi-distributed and fully
distributed protocols for 802.11-based wireless networks standard
are presented and evaluated. The philosophy of the approach is to
minimize modifications to existing protocols, particularly within
client-side devices. Thus, modifications are primarily made at
the access points (APs). The semi-distributed protocol was fully
implemented within the 802.11 package of ns-3 to evaluate the
approach. Simulation results with two APs, and with either one
client per AP or two clients per AP, show that within 5 seconds
of network operation, our protocol increases the goodput on the
downlink by about
50%, as compared against a standard 802.11n
implementation
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