82,598 research outputs found
A Game-Theoretic Approach to Energy-Efficient Resource Allocation in Device-to-Device Underlay Communications
Despite the numerous benefits brought by Device-to-Device (D2D)
communications, the introduction of D2D into cellular networks poses many new
challenges in the resource allocation design due to the co-channel interference
caused by spectrum reuse and limited battery life of User Equipments (UEs).
Most of the previous studies mainly focus on how to maximize the Spectral
Efficiency (SE) and ignore the energy consumption of UEs. In this paper, we
study how to maximize each UE's Energy Efficiency (EE) in an
interference-limited environment subject to its specific Quality of Service
(QoS) and maximum transmission power constraints. We model the resource
allocation problem as a noncooperative game, in which each player is
self-interested and wants to maximize its own EE. A distributed
interference-aware energy-efficient resource allocation algorithm is proposed
by exploiting the properties of the nonlinear fractional programming. We prove
that the optimum solution obtained by the proposed algorithm is the Nash
equilibrium of the noncooperative game. We also analyze the tradeoff between EE
and SE and derive closed-form expressions for EE and SE gaps.Comment: submitted to IET Communications. arXiv admin note: substantial text
overlap with arXiv:1405.1963, arXiv:1407.155
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
Decentralized Resource Allocation for Heterogeneous Cellular Networks
Heterogeneous Cellular Network (HetNet) is a promising technology for 5th generation mobile networks (5G) that can potentially improve spatial resource reuse and extend coverage, therefore allowing it to achieve significantly higher data rates than single tier networks. However, the performance of HetNet is limited by co-channel (inter-UE, inter-cell) interference. Hence, resource allocation is carefully done in this paper to ensure that the likely loss in achievable data rate due to interference doesn't diminish the gain in the achievable data rate due to higher spatial reuse. The resources which we consider in this paper are the spatial resource (unit-beamformer) and the power resource. We formulate our distributed spatial resource allocation problem as a quadratic optimization problem with non-convex quadratic constraints and solved it by exploiting stationarity karush-Kuhn-Tucker (KKT) conditions. While our proposed power resource allocation scheme is formulated as a convex optimization problem and is solved by exploiting karush-Kuhn-Tucker (KKT) conditions. Simulation results of our proposed method, when compared with other existing methods show significant improvement
A Tutorial on Cross-layer Optimization Wireless Network System Using TOPSIS Method
Each other, leading to issues such as interference, limited bandwidth, and varying channel conditions. These challenges require specialized optimization techniques tailored to the wireless environment. In wireless communication networks is to maximize the overall system throughput while ensuring fairness among users and maintaining quality of service requirements. This objective can be achieved through resource allocation optimization, where the available network resources such as bandwidth, power, and time slots are allocated to users in an optimal manner. Optimization-based approaches in wireless resource allocation typically involve formulating the resource allocation problem as an optimization problem with certain constraints.. These techniques provide practical solutions with reduced computational complexity, although they may not guarantee optimality. In summary, optimization-based approaches have been instrumental in studying resource allocation problems in communication networks, including the wireless domain. While techniques from the Internet setting have influenced the understanding of congestion control and protocol design, specific challenges in wireless networks necessitate tailored optimization techniques that account for interference, limited bandwidth, and varying channel conditions. power allocation problem in wireless ad hoc networks Cross-layer optimization refers to the process of jointly optimizing the allocation of resources across different layers of wireless networks, the interactions between different layers become more complex due to the shared medium and time-varying channel conditions. Nash equilibrium, where no user can unilaterally improve its own performance by changing its strategy. Game theory can capture the distributed nature of wireless networks and provide insights into the behavior of users in resource allocation scenarios Additionally, heuristics and approximation algorithms are often employed in wireless resource allocation due to the complexity of the optimization problems involved. In traditional cellular systems, each user is allocated a fixed time slot for transmission, regardless of their channel conditions. However, in opportunistic scheduling. Alternative parameters for “Data rate Ž kbps, Geographic coverage , Service requirements , cost ” Evaluation parameter for “Circuit-switched cell, CDPD, WLAN, Paging, Satellite.” “the first ranking training is obtained with the lowest quality of compensation.
Joint Optimization of Signal Design and Resource Allocation in Wireless D2D Edge Computing
In this paper, we study the distributed computational capabilities of
device-to-device (D2D) networks. A key characteristic of D2D networks is that
their topologies are reconfigurable to cope with network demands. For
distributed computing, resource management is challenging due to limited
network and communication resources, leading to inter-channel interference. To
overcome this, recent research has addressed the problems of wireless
scheduling, subchannel allocation, power allocation, and multiple-input
multiple-output (MIMO) signal design, but has not considered them jointly. In
this paper, unlike previous mobile edge computing (MEC) approaches, we propose
a joint optimization of wireless MIMO signal design and network resource
allocation to maximize energy efficiency. Given that the resulting problem is a
non-convex mixed integer program (MIP) which is prohibitive to solve at scale,
we decompose its solution into two parts: (i) a resource allocation subproblem,
which optimizes the link selection and subchannel allocations, and (ii) MIMO
signal design subproblem, which optimizes the transmit beamformer, transmit
power, and receive combiner. Simulation results using wireless edge topologies
show that our method yields substantial improvements in energy efficiency
compared with cases of no offloading and partially optimized methods and that
the efficiency scales well with the size of the network.Comment: 10 pages, 7 figures, Accepted by INFOCOM 202
Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks
This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium
Delay-Throughput Analysis in Distributed Wireless Networks
A primary challenge in wireless networks is to use available resources efficiently so
that the Quality of Service (QoS) is satisfied while maximizing the throughput of the
network. Among different resource allocation strategies, power and spectrum allocations
have long been regarded as efficient tools to mitigate interference and improve the
throughput of the network. Also, achieving a low transmission delay is an important
QoS requirement in buffer-limited networks, particularly for users with real-time
services. For these networks, too much delay results in dropping some packets. Therefore, the main challenge
in networks with real-time services is to utilize an efficient power allocation scheme
so that the delay is minimized while achieving a high throughput. This dissertation
deals with these problems in distributed wireless networks
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