732 research outputs found
Low-complexity medium access control protocols for QoS support in third-generation radio access networks
One approach to maximizing the efficiency of
medium access control (MAC) on the uplink in a future wideband
code-division multiple-access (WCDMA)-based third-generation
radio access network, and hence maximize spectral efficiency,
is to employ a low-complexity distributed scheduling control
approach. The maximization of spectral efficiency in third-generation
radio access networks is complicated by the need to
provide bandwidth-on-demand to diverse services characterized
by diverse quality of service (QoS) requirements in an interference
limited environment. However, the ability to exploit the full
potential of resource allocation algorithms in third-generation
radio access networks has been limited by the absence of a metric
that captures the two-dimensional radio resource requirement,
in terms of power and bandwidth, in the third-generation radio
access network environment, where different users may have
different signal-to-interference ratio requirements. This paper
presents a novel resource metric as a solution to this fundamental
problem. Also, a novel deadline-driven backoff procedure has
been presented as the backoff scheme of the proposed distributed
scheduling MAC protocols to enable the efficient support of
services with QoS imposed delay constraints without the need
for centralized scheduling. The main conclusion is that low-complexity
distributed scheduling control strategies using overload
avoidance/overload detection can be designed using the proposed
resource metric to give near optimal performance and thus maintain
a high spectral efficiency in third-generation radio access
networks and that importantly overload detection is superior to
overload avoidance
An Analytical Framework for Heterogeneous Partial Feedback Design in Heterogeneous Multicell OFDMA Networks
The inherent heterogeneous structure resulting from user densities and large
scale channel effects motivates heterogeneous partial feedback design in
heterogeneous networks. In such emerging networks, a distributed scheduling
policy which enjoys multiuser diversity as well as maintains fairness among
users is favored for individual user rate enhancement and guarantees. For a
system employing the cumulative distribution function based scheduling, which
satisfies the two above mentioned desired features, we develop an analytical
framework to investigate heterogeneous partial feedback in a general
OFDMA-based heterogeneous multicell employing the best-M partial feedback
strategy. Exact sum rate analysis is first carried out and closed form
expressions are obtained by a novel decomposition of the probability density
function of the selected user's signal-to-interference-plus-noise ratio. To
draw further insight, we perform asymptotic analysis using extreme value theory
to examine the effect of partial feedback on the randomness of multiuser
diversity, show the asymptotic optimality of best-1 feedback, and derive an
asymptotic approximation for the sum rate in order to determine the minimum
required partial feedback.Comment: To appear in IEEE Trans. on Signal Processin
Joint Resource Optimization for Multicell Networks with Wireless Energy Harvesting Relays
This paper first considers a multicell network deployment where the base
station (BS) of each cell communicates with its cell-edge user with the
assistance of an amplify-and-forward (AF) relay node. Equipped with a power
splitter and a wireless energy harvester, the self-sustaining relay scavenges
radio frequency (RF) energy from the received signals to process and forward
the information. Our aim is to develop a resource allocation scheme that
jointly optimizes (i) BS transmit powers, (ii) received power splitting factors
for energy harvesting and information processing at the relays, and (iii) relay
transmit powers. In the face of strong intercell interference and limited radio
resources, we formulate three highly-nonconvex problems with the objectives of
sum-rate maximization, max-min throughput fairness and sum-power minimization.
To solve such challenging problems, we propose to apply the successive convex
approximation (SCA) approach and devise iterative algorithms based on geometric
programming and difference-of-convex-functions programming. The proposed
algorithms transform the nonconvex problems into a sequence of convex problems,
each of which is solved very efficiently by the interior-point method. We prove
that our algorithms converge to the locally optimal solutions that satisfy the
Karush-Kuhn-Tucker conditions of the original nonconvex problems. We then
extend our results to the case of decode-and-forward (DF) relaying with
variable timeslot durations. We show that our resource allocation solutions in
this case offer better throughput than that of the AF counterpart with equal
timeslot durations, albeit at a higher computational complexity. Numerical
results confirm that the proposed joint optimization solutions substantially
improve the network performance, compared with cases where the radio resource
parameters are individually optimized
Analysis of Multi-Cell Downlink Cooperation with a Constrained Spatial Model
Multi-cell cooperation (MCC) mitigates intercell interference and improves
throughput at the cell edge. This paper considers a cooperative downlink,
whereby cell-edge mobiles are served by multiple cooperative base stations. The
cooperating base stations transmit identical signals over paths with
non-identical path losses, and the receiving mobile performs diversity
combining. The analysis in this paper is driven by a new expression for the
conditional outage probability when signals arriving over different paths are
combined in the presence of noise and interference, where the conditioning is
with respect to the network topology and shadowing. The channel model accounts
for path loss, shadowing, and Nakagami fading, and the Nakagami fading
parameters do not need to be identical for all paths. To study performance over
a wide class of network topologies, a random spatial model is adopted, and
performance is found by statistically characterizing the rates provided on the
downlinks. To model realistic networks, the model requires a minimum separation
among base stations. Having adopted a realistic model and an accurate analysis,
the paper proceeds to determine performance under several resource-allocation
policies and provides insight regarding how the cell edge should be defined.Comment: 6 pages, 3 figures, IEEE Global Telecommun. Conf. (GLOBECOM), 2013,
to appear. arXiv admin note: text overlap with arXiv:1210.366
Coalitional Games with Overlapping Coalitions for Interference Management in Small Cell Networks
In this paper, we study the problem of cooperative interference management in
an OFDMA two-tier small cell network. In particular, we propose a novel
approach for allowing the small cells to cooperate, so as to optimize their
sum-rate, while cooperatively satisfying their maximum transmit power
constraints. Unlike existing work which assumes that only disjoint groups of
cooperative small cells can emerge, we formulate the small cells' cooperation
problem as a coalition formation game with overlapping coalitions. In this
game, each small cell base station can choose to participate in one or more
cooperative groups (or coalitions) simultaneously, so as to optimize the
tradeoff between the benefits and costs associated with cooperation. We study
the properties of the proposed overlapping coalition formation game and we show
that it exhibits negative externalities due to interference. Then, we propose a
novel decentralized algorithm that allows the small cell base stations to
interact and self-organize into a stable overlapping coalitional structure.
Simulation results show that the proposed algorithm results in a notable
performance advantage in terms of the total system sum-rate, relative to the
noncooperative case and the classical algorithms for coalitional games with
non-overlapping coalitions
Cognition-inspired 5G cellular networks: a review and the road ahead
Despite the evolution of cellular networks, spectrum scarcity and the lack of intelligent and autonomous capabilities remain a cause for concern. These problems have resulted in low network capacity, high signaling overhead, inefficient data forwarding, and low scalability, which are expected to persist as the stumbling blocks to deploy, support and scale next-generation applications, including smart city and virtual reality. Fifth-generation (5G) cellular networking, along with its salient operational characteristics - including the cognitive and cooperative capabilities, network virtualization, and traffic offload - can address these limitations to cater to future scenarios characterized by highly heterogeneous, ultra-dense, and highly variable environments. Cognitive radio (CR) and cognition cycle (CC) are key enabling technologies for 5G. CR enables nodes to explore and use underutilized licensed channels; while CC has been embedded in CR nodes to learn new knowledge and adapt to network dynamics. CR and CC have brought advantages to a cognition-inspired 5G cellular network, including addressing the spectrum scarcity problem, promoting interoperation among heterogeneous entities, and providing intelligence and autonomous capabilities to support 5G core operations, such as smart beamforming. In this paper, we present the attributes of 5G and existing state of the art focusing on how CR and CC have been adopted in 5G to provide spectral efficiency, energy efficiency, improved quality of service and experience, and cost efficiency. This main contribution of this paper is to complement recent work by focusing on the networking aspect of CR and CC applied to 5G due to the urgent need to investigate, as well as to further enhance, CR and CC as core mechanisms to support 5G. This paper is aspired to establish a foundation and to spark new research interest in this topic. Open research opportunities and platform implementation are also presented to stimulate new research initiatives in this exciting area
Dynamic Almost Blank Subframe Scheme for Enhanced Intercell Interference Coordination in LTE-A Heterogeneous Networks
In LTE-A heterogeneous network, traffic load may be distributed unequally because the transmission power of macro eNodeB (eNB) is higher than pico eNB. To address the coverage problems resulting from nodes with different transmission powers, cell range expansion (CRE) technique has been proposed as a cell selection technique. However, in this case, the intercell interference (ICI) problem can occur on both data and control channels when users connect to pico eNB. To mitigate ICI problem, a new dynamic almost blank subframe (ABS) scheme is proposed in this paper. In this scheme, a fuzzy logic system is deployed to monitor the system performance and then obtain the required number of ABSs. Simulation results show that the cell throughput and user throughput can be improved using the proposed dynamic ABS scheme
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