746 research outputs found
Delay QoS Provisioning and Optimal Resource Allocation for Wireless Networks
Recent years have witnessed a significant growth in wireless communication and networking due to the exponential growth in mobile applications and smart devices, fueling unprecedented increase in both mobile data traffic and energy demand. Among such data traffic, real-time data transmissions in wireless systems require certain quality of service (QoS) constraints e.g., in terms of delay, buffer overflow or packet drop/loss probabilities, so that acceptable performance levels can be guaranteed for the end-users, especially in delay sensitive scenarios, such as live video transmission, interactive video (e.g., teleconferencing), and mobile online gaming. With this motivation, statistical queuing constraints are considered in this thesis, imposed as limitations on the decay rate of buffer overflow probabilities. In particular, the throughput and energy efficiency of different types of wireless network models are analyzed under QoS constraints, and optimal resource allocation algorithms are proposed to maximize the throughput or minimize the delay.
In the first part of the thesis, the throughput and energy efficiency analysis for hybrid automatic repeat request (HARQ) protocols are conducted under QoS constraints. Approximations are employed for small QoS exponent values in order to obtain closed-form expressions for the throughput and energy efficiency metrics. Also, the impact of random arrivals, deadline constraints, outage probability and QoS constraints are studied. For the same system setting, the throughput of HARQ system is also analyzed using a recurrence approach, which provides more accurate results for any value of the QoS exponent. Similarly, random arrival models and deadline constraints are considered, and these results are further extended to the finite-blocklength coding regime.
Next, cooperative relay networks are considered under QoS constraints. Specifically, the throughput performance in the two-hop relay channel, two-way relay channel, and multi-source multi-destination relay networks is analyzed. Finite-blocklength codes are considered for the two-hop relay channel, and optimization over the error probabilities is investigated. For the multi-source multi-destination relay network model, the throughput for both cases of with and without CSI at the transmitter sides is studied. When there is perfect CSI at the transmitter, transmission rates can be varied according to instantaneous channel conditions. When CSI is not available at the transmitter side, transmissions are performed at fixed rates, and decoding failures lead to retransmission requests via an ARQ protocol.
Following the analysis of cooperative networks, the performance of both half-duplex and full-duplex operations is studied for the two-way multiple input multiple output (MIMO) system under QoS constraints. In full-duplex mode, the self-interference inflicted on the reception of a user due to simultaneous transmissions from the same user is taken into account. In this setting, the system throughput
is formulated by considering the sum of the effective capacities of the users in both half-duplex and full-duplex modes. The low signal to noise ratio (SNR) regime is considered and the optimal transmission/power-allocation strategies are characterized by identifying the optimal input covariance matrices.
Next, mode selection and resource allocation for device-to-device (D2D) cellular networks are studied. As the starting point, ransmission mode selection and resource allocation are analyzed for a time-division multiplexed (TDM) cellular network with one cellular user, one base station, and a pair of D2D users under rate and QoS constraints. For a more complicated setting with multiple cellular and D2D users, two joint mode selection and resource allocation algorithms are proposed. In the first algorithm, the channel allocation problem is formulated as a maximum-weight matching problem, which can be solved by employing the Hungarian algorithm. In the second algorithm, the problem is divided into three subproblems, namely user partition, power allocation and channel assignment, and a novel three-step method is proposed by combining the algorithms designed for the three subproblems.
In the final part of the thesis, resource allocation algorithms are investigated for content delivery over wireless networks. Three different systems are considered. Initially, a caching algorithm is designed, which minimizes the average delay of a single-cell network. The proposed algorithm is applicable in settings with very general popularity models, with no assumptions on how file popularity varies among different users, and this algorithm is further extended to a more general setting, in which the system parameters and the distributions of channel fading change over time. Next, for D2D cellular networks operating under deadline constraints, a scheduling algorithm is designed, which manages mode selection, channel allocation and power maximization with acceptable complexity. This proposed scheduling algorithm is designed based on the convex delay cost method for a D2D cellular network with deadline constraints in an OFDMA setting. Power optimization algorithms are proposed for all possible modes, based on our utility definition. Finally, a two-step intercell interference (ICI)-aware scheduling algorithm is proposed for cloud radio access networks (C-RANs), which performs user grouping and resource allocation with the goal of minimizing delay violation probability. A novel user grouping algorithm is developed for the user grouping step, which controls the interference among the users in the same group, and the channel assignment problem is formulated as a maximum-weight matching problem in the second step, which can be solved using standard algorithms in graph theory
Bio-Inspired Resource Allocation for Relay-Aided Device-to-Device Communications
The Device-to-Device (D2D) communication principle is a key enabler of direct
localized communication between mobile nodes and is expected to propel a
plethora of novel multimedia services. However, even though it offers a wide
set of capabilities mainly due to the proximity and resource reuse gains,
interference must be carefully controlled to maximize the achievable rate for
coexisting cellular and D2D users. The scope of this work is to provide an
interference-aware real-time resource allocation (RA) framework for relay-aided
D2D communications that underlay cellular networks. The main objective is to
maximize the overall network throughput by guaranteeing a minimum rate
threshold for cellular and D2D links. To this direction, genetic algorithms
(GAs) are proven to be powerful and versatile methodologies that account for
not only enhanced performance but also reduced computational complexity in
emerging wireless networks. Numerical investigations highlight the performance
gains compared to baseline RA methods and especially in highly dense scenarios
which will be the case in future 5G networks.Comment: 6 pages, 6 figure
Spectral Efficient and Energy Aware Clustering in Cellular Networks
The current and envisaged increase of cellular traffic poses new challenges
to Mobile Network Operators (MNO), who must densify their Radio Access Networks
(RAN) while maintaining low Capital Expenditure and Operational Expenditure to
ensure long-term sustainability. In this context, this paper analyses optimal
clustering solutions based on Device-to-Device (D2D) communications to mitigate
partially or completely the need for MNOs to carry out extremely dense RAN
deployments. Specifically, a low complexity algorithm that enables the creation
of spectral efficient clusters among users from different cells, denoted as
enhanced Clustering Optimization for Resources' Efficiency (eCORE) is
presented. Due to the imbalance between uplink and downlink traffic, a
complementary algorithm, known as Clustering algorithm for Load Balancing
(CaLB), is also proposed to create non-spectral efficient clusters when they
result in a capacity increase. Finally, in order to alleviate the energy
overconsumption suffered by cluster heads, the Clustering Energy Efficient
algorithm (CEEa) is also designed to manage the trade-off between the capacity
enhancement and the early battery drain of some users. Results show that the
proposed algorithms increase the network capacity and outperform existing
solutions, while, at the same time, CEEa is able to handle the cluster heads
energy overconsumption
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Game-Theoretic based Power Allocation for a Full Duplex D2D Network
International audienceThis paper tackles the power allocation optimization problem of a Full duplex(FD) D2D underlaying cellular network. In particular, we aim at providing a distributed power allocation algorithm for this type of network. Towards this end, first, we formulate the PA problem as a non-cooperative game in which each user decides how much power to transmit over its allocated channel to maximize its link's energy-efficiency (EE). Next, we show that this game admits a unique Nash equilibrium (NE) point which can be obtained through an iterative process. After that, we show that this iterative algorithm can be implemented in a fully distributed manner. Finally, we compare our proposed distributed algorithm with the conventional centralized algorithms and simulation results show the importance of the proposed solution
Resource Allocation for Device-to-Device Communications Underlaying Heterogeneous Cellular Networks Using Coalitional Games
Heterogeneous cellular networks (HCNs) with millimeter wave (mmWave)
communications included are emerging as a promising candidate for the fifth
generation mobile network. With highly directional antenna arrays, mmWave links
are able to provide several-Gbps transmission rate. However, mmWave links are
easily blocked without line of sight. On the other hand, D2D communications
have been proposed to support many content based applications, and need to
share resources with users in HCNs to improve spectral reuse and enhance system
capacity. Consequently, an efficient resource allocation scheme for D2D pairs
among both mmWave and the cellular carrier band is needed. In this paper, we
first formulate the problem of the resource allocation among mmWave and the
cellular band for multiple D2D pairs from the view point of game theory. Then,
with the characteristics of cellular and mmWave communications considered, we
propose a coalition formation game to maximize the system sum rate in
statistical average sense. We also theoretically prove that our proposed game
converges to a Nash-stable equilibrium and further reaches the near-optimal
solution with fast convergence rate. Through extensive simulations under
various system parameters, we demonstrate the superior performance of our
scheme in terms of the system sum rate compared with several other practical
schemes.Comment: 13 pages, 12 figure
Resource Allocation for Device-to-Device Communications in Multi-Cell Multi-Band Heterogeneous Cellular Networks
Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave)
communications are considered as a promising technology for the fifth
generation mobile networks. Mm-wave has the potential to provide multiple
gigabit data rate due to the broad spectrum. Unfortunately, additional free
space path loss is also caused by the high carrier frequency. On the other
hand, mm-wave signals are sensitive to obstacles and more vulnerable to
blocking effects. To address this issue, highly directional narrow beams are
utilized in mm-wave networks. Additionally, device-to-device (D2D) users make
full use of their proximity and share uplink spectrum resources in HCNs to
increase the spectrum efficiency and network capacity. Towards the caused
complex interferences, the combination of D2D-enabled HCNs with small cells
densely deployed and mm-wave communications poses a big challenge to the
resource allocation problems. In this paper, we formulate the optimization
problem of D2D communication spectrum resource allocation among multiple
micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the
totally different propagation conditions on the two bands, a heuristic
algorithm is proposed to maximize the system transmission rate and approximate
the solutions with sufficient accuracies. Compared with other practical
schemes, we carry out extensive simulations with different system parameters,
and demonstrate the superior performance of the proposed scheme. In addition,
the optimality and complexity are simulated to further verify effectiveness and
efficiency.Comment: 13 pages, 11 figures, IEEE Transactions on Vehicular Technolog
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