129 research outputs found
Interference-Based Optimal Power-Efficient Access Scheme for Cognitive Radio Networks
In this paper, we propose a new optimization-based access strategy of
multipacket reception (MPR) channel for multiple secondary users (SUs)
accessing the primary user (PU) spectrum opportunistically. We devise an
analytical model that realizes the multipacket access strategy of SUs that
maximizes the throughput of individual backlogged SUs subject to queue
stability of the PU. All the network receiving nodes have MPR capability. We
aim at maximizing the throughput of the individual SUs such that the PU's queue
is maintained stable. Moreover, we are interested in providing an
energy-efficient cognitive scheme. Therefore, we include energy constraints on
the PU and SU average transmitted energy to the optimization problem. Each SU
accesses the medium with certain probability that depends on the PU's activity,
i.e., active or inactive. The numerical results show the advantage in terms of
SU throughput of the proposed scheme over the conventional access scheme, where
the SUs access the channel randomly with fixed power when the PU is sensed to
be idle
Energy efficiency in heterogeneous wireless access networks
In this article, we bring forward the important aspect of energy savings in wireless access networks. We specifically focus on the energy saving opportunities in the recently evolving heterogeneous networks (HetNets), both Single- RAT and Multi-RAT. Issues such as sleep/wakeup cycles and interference management are discussed for co-channel Single-RAT HetNets. In addition to that, a simulation based study for LTE macro-femto HetNets is presented, indicating the need for dynamic energy efficient resource management schemes. Multi-RAT HetNets also come with challenges such as network integration, combined resource management and network selection. Along with a discussion on these challenges, we also investigate the performance of the conventional WLAN-first network selection mechanism in terms of energy efficiency (EE) and suggest that EE can be improved by the application of intelligent call admission control policies
Utility Maximization for Uplink MU-MIMO: Combining Spectral-Energy Efficiency and Fairness
Driven by green communications, energy efficiency (EE) has become a new
important criterion for designing wireless communication systems. However, high
EE often leads to low spectral efficiency (SE), which spurs the research on
EE-SE tradeoff. In this paper, we focus on how to maximize the utility in
physical layer for an uplink multi-user multiple-input multipleoutput (MU-MIMO)
system, where we will not only consider EE-SE tradeoff in a unified way, but
also ensure user fairness. We first formulate the utility maximization problem,
but it turns out to be non-convex. By exploiting the structure of this problem,
we find a convexization procedure to convert the original nonconvex problem
into an equivalent convex problem, which has the same global optimum with the
original problem. Following the convexization procedure, we present a
centralized algorithm to solve the utility maximization problem, but it
requires the global information of all users. Thus we propose a primal-dual
distributed algorithm which does not need global information and just consumes
a small amount of overhead. Furthermore, we have proved that the distributed
algorithm can converge to the global optimum. Finally, the numerical results
show that our approach can both capture user diversity for EE-SE tradeoff and
ensure user fairness, and they also validate the effectiveness of our
primal-dual distributed algorithm
Green heterogeneous small-cell networks: toward reducing the CO2 emissions of mobile communications industry using uplink power adaptation
Heterogeneous small cell networks, or Het- SNets, are considered as a standard part of future mobile networks in which multiple lowpower low-cost user deployed base stations complement the existing macrocell infrastructure. This article proposes an energy-efficient deployment of the cells where the small cell base stations are arranged around the edge of the reference macrocell, and the deployment is referred to as cell-on-edge (COE) deployment. The proposed deployment ensures an increase in the network spectral and energy efficiency by facilitating cell edge mobile users with small cells. Moreover, COE deployment guarantees reduction of the carbon footprint of mobile operations by employing adaptive uplink power control. In order to calibrate the reduction in CO2 emissions, this article quantifies the ecological and associated economical impacts of energy savings in the proposed deployment. Simulation results quantify the improvements in CO2 emissions and spectral and energy gains of the proposed COE deployment compared to macro-only networks and typical small cell deployment strategies where small cells are randomly deployed within a given macrocell
Adaptive stochastic radio access selection scheme for cellular-WLAN heterogeneous communication systems
This study proposes a novel adaptive stochastic radio access selection scheme for mobile users in heterogeneous cellular-wireless local area network (WLAN) systems. In this scheme, a mobile user located in dual coverage area randomly selects WLAN with probability of ω when there is a need for downloading a chunk of data. The value of ω is optimised according to the status of both networks in terms of network load and signal quality of both cellular and WLAN networks. An analytical model based on continuous time Markov chain is proposed to optimise the value of ω and compute the performance of proposed scheme in terms of energy efficiency, throughput, and call blocking probability. Both analytical and simulation results demonstrate the superiority of the proposed scheme compared with the mainstream network selection schemes: namely, WLAN-first and load balancing
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