343 research outputs found
Wireless Cellular Networks
When aiming for achieving high spectral efficiency in wireless cellular networks, cochannel interference (CCI) becomes the dominant performancelimiting factor. This article provides a survey of CCI mitigation techniques, where both active and passive approaches are discussed in the context of both open- and closed-loop designs.More explicitly, we considered both the family of flexible frequency-reuse (FFR)-aided and dynamic channel allocation (DCA)-aided interference avoidance techniques as well as smart antenna-aided interference mitigation techniques, which may be classified as active approach
A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
This paper addresses the problem of channel estimation in multi-cell
interference-limited cellular networks. We consider systems employing multiple
antennas and are interested in both the finite and large-scale antenna number
regimes (so-called "massive MIMO"). Such systems deal with the multi-cell
interference by way of per-cell beamforming applied at each base station.
Channel estimation in such networks, which is known to be hampered by the pilot
contamination effect, constitute a major bottleneck for overall performance. We
present a novel approach which tackles this problem by enabling a low-rate
coordination between cells during the channel estimation phase itself. The
coordination makes use of the additional second-order statistical information
about the user channels, which are shown to offer a powerful way of
discriminating across interfering users with even strongly correlated pilot
sequences. Importantly, we demonstrate analytically that in the
large-number-of-antennas regime, the pilot contamination effect is made to
vanish completely under certain conditions on the channel covariance. Gains
over the conventional channel estimation framework are confirmed by our
simulations for even small antenna array sizes.Comment: 10 pages, 6 figures, to appear in IEEE Journal on Selected Areas in
Communication
Coordinated Per-Antenna Power Minimization for Multicell Massive MIMO Systems with Low-Resolution Data Converters
A multicell-coordinated beamforming solution for massive multiple-input
multiple-output orthogonal frequency-division multiplexing (OFDM) systems is
presented when employing low-resolution data converters and per-antenna level
constraints. For a more realistic deployment, we aim to find the downlink (DL)
beamformer that minimizes the maximum power on transmit antenna array of each
basestation under received signal quality constraints while minimizing
per-antenna transmit power. We show that strong duality holds between the
primal DL formulation and its manageable Lagrangian dual problem which can be
interpreted as the virtual uplink (UL) problem with adjustable noise covariance
matrices. For a fixed set of noise covariance matrices, we claim that the
virtual UL solution is effectively used to compute the DL beamformer and noise
covariance matrices can be subsequently updated with an associated subgradient.
Our primary contributions are then (1) formulating the quantized DL OFDM
antenna power minimax problem and deriving its associated dual problem, (2)
showing strong duality and interpreting the dual as a virtual quantized UL OFDM
problem, and (3) developing an iterative minimax algorithm based on the dual
problem. Simulations validate the proposed algorithm in terms of the maximum
antenna transmit power and peak-to-average-power ratio.Comment: submitted for possible IEEE journal publicatio
Optimal Linear Precoding in Multi-User MIMO Systems: A Large System Analysis
We consider the downlink of a single-cell multi-user MIMO system in which the
base station makes use of antennas to communicate with single-antenna
user equipments (UEs) randomly positioned in the coverage area. In particular,
we focus on the problem of designing the optimal linear precoding for
minimizing the total power consumption while satisfying a set of target
signal-to-interference-plus-noise ratios (SINRs). To gain insights into the
structure of the optimal solution and reduce the computational complexity for
its evaluation, we analyze the asymptotic regime where and grow large
with a given ratio and make use of recent results from large system analysis to
compute the asymptotic solution. Then, we concentrate on the asymptotically
design of heuristic linear precoding techniques. Interestingly, it turns out
that the regularized zero-forcing (RZF) precoder is equivalent to the optimal
one when the ratio between the SINR requirement and the average channel
attenuation is the same for all UEs. If this condition does not hold true but
only the same SINR constraint is imposed for all UEs, then the RZF can be
modified to still achieve optimality if statistical information of the UE
positions is available at the BS. Numerical results are used to evaluate the
performance gap in the finite system regime and to make comparisons among the
precoding techniques.Comment: 6 pages, 2 figures, IEEE Global Communications Conference (GLOBECOM),
Austin, Texas, Dec. 2014. An extended version of this work is available at
http://arxiv.org/abs/1406.598
Cooperative Precoding with Limited Feedback for MIMO Interference Channels
Multi-antenna precoding effectively mitigates the interference in wireless
networks. However, the resultant performance gains can be significantly
compromised in practice if the precoder design fails to account for the
inaccuracy in the channel state information (CSI) feedback. This paper
addresses this issue by considering finite-rate CSI feedback from receivers to
their interfering transmitters in the two-user multiple-input-multiple-output
(MIMO) interference channel, called cooperative feedback, and proposing a
systematic method for designing transceivers comprising linear precoders and
equalizers. Specifically, each precoder/equalizer is decomposed into inner and
outer components for nulling the cross-link interference and achieving array
gain, respectively. The inner precoders/equalizers are further optimized to
suppress the residual interference resulting from finite-rate cooperative
feedback. Further- more, the residual interference is regulated by additional
scalar cooperative feedback signals that are designed to control transmission
power using different criteria including fixed interference margin and maximum
sum throughput. Finally, the required number of cooperative precoder feedback
bits is derived for limiting the throughput loss due to precoder quantization.Comment: 23 pages; 5 figures; this work was presented in part at Asilomar 2011
and will appear in IEEE Trans. on Wireless Com
Distributed optimisation techniques for wireless networks
Alongside the ever increasing traffic demand, the fifth generation (5G) cellular network architecture is being proposed to provide better quality of service, increased data rate, decreased latency, and increased capacity. Without any doubt, the 5G cellular network will comprise of ultra-dense networks and multiple input multiple output technologies. This will make the current centralised solutions impractical due to increased complexity. Moreover, the amount of coordination information that needs to be transported over the backhaul links will be increased. Distributed or decentralised solutions are promising to provide better alternatives.
This thesis proposes new distributed algorithms for wireless networks which aim to reduce the amount of system overheads in the backhaul links and the system complexity. The analysis of conflicts amongst transmitters, and resource allocation are conducted via the use of game theory, convex optimisation, and auction theory.
Firstly, game-theoretic model is used to analyse a mixed quality of service (QoS) strategic non-cooperative game (SNG), for a two-user multiple-input single-output (MISO) interference channel. The players are considered to have different objectives. Following this, the mixed QoS SNG is extended to a multicell multiuser network in terms of signal-to-interference-and-noise ratio (SINR) requirement. In the multicell multiuser setting, each transmitter is assumed to be serving real time users (RTUs) and non-real time users (NRTUs), simultaneously. A novel mixed QoS SNG algorithm is proposed, with its operating point identified as the Nash equilibrium-mixed QoS (NE-mixed QoS). Nash, Kalai-Smorodinsky, and Egalitarian bargain solutions are then proposed to improve the performance of the NE-mixed QoS. The performance of the bargain solutions are observed to be comparable to the centralised solutions.
Secondly, user offloading and user association problems are addressed for small cells using auction theory. The main base station wishes to offload some of its users to privately owned small cell access points. A novel bid-wait-auction (BWA) algorithm, which allows single-item bidding at each auction round, is designed to decompose the combinatorial mathematical nature of the problem. An analysis on the existence and uniqueness of the dominant strategy equilibrium is conducted. The BWA is then used to form the forward BWA (FBWA) and the backward BWA (BBWA). It is observed that the BBWA allows more users to be admitted as compared to the FBWA.
Finally, simultaneous multiple-round ascending auction (SMRA), altered SMRA (ASMRA), sequential combinatorial auction with item bidding (SCAIB), and repetitive combinatorial auction with item bidding (RCAIB) algorithms are proposed to perform user offloading and user association for small cells. These algorithms are able to allow bundle bidding. It is then proven that, truthful bidding is individually rational and leads to Walrasian equilibrium. The performance of the proposed auction based algorithms is evaluated. It is observed that the proposed algorithms match the performance of the centralised solutions when the guest users have low target rates. The SCAIB algorithm is shown to be the most preferred as it provides high admission rate and competitive revenue to the bidders
Large System Analysis of Base Station Cooperation for Power Minimization
This work focuses on a large-scale multi-cell multi-user MIMO system in which
base stations (BSs) of antennas each communicate with
single-antenna user equipments. We consider the design of the linear precoder
that minimizes the total power consumption while ensuring target user rates.
Three configurations with different degrees of cooperation among BSs are
considered: the coordinated beamforming scheme (only channel state information
is shared among BSs), the coordinated multipoint MIMO processing technology or
network MIMO (channel state and data cooperation), and a single cell
beamforming scheme (only local channel state information is used for
beamforming while channel state cooperation is needed for power allocation).
The analysis is conducted assuming that and grow large with a non
trivial ratio and imperfect channel state information (modeled by the
generic Gauss-Markov formulation form) is available at the BSs. Tools of random
matrix theory are used to compute, in explicit form, deterministic
approximations for: (i) the parameters of the optimal precoder; (ii) the powers
needed to ensure target rates; and (iii) the total transmit power. These
results are instrumental to get further insight into the structure of the
optimal precoders and also to reduce the implementation complexity in
large-scale networks. Numerical results are used to validate the asymptotic
analysis in the finite system regime and to make comparisons among the
different configurations.Comment: 32 pages, 6 figures, to appear IEEE Trans. Wireless Commun. A
preliminary version of this paper was presented at the IEEE Global
Communication Conference, San Diego, USA, Dec. 201
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