458 research outputs found
Energy Efficiency for 5G Multi-Tier Cellular Networks
The heterogeneous cellular network (HCN) is most significant as a key technology for future fifth-generation (5G) wireless networks. The heterogeneous network consists of randomly macrocell base stations (MBSs) overlaid with femtocell base stations (FBSs). Stochastic geometry has been shown to be a very powerful tool to model, analyze, and design networks with random topologies such as wireless ad hoc, sensor networks, and multi-tier cellular networks. HCNs can be energy-efficiently designed by deploying various BSs belonging to different networks, which has drawn significant attention to one of the technologies for future 5G wireless networks. In this chapter, we propose switching off/on systems enabling the BSs in the cellular networks to efficiently consume the power by introducing active/sleep modes, which is able to reduce the interference and power consumption in the MBSs and FBSs on an individual basis as well as improve the energy efficiency of the cellular networks. We formulate the minimization of the power consumption for the MBSs and FBSs as well as an optimization problem to maximize the energy efficiency subject to throughput outage constraints, which can be solved by the Karush-Kuhn-Tucker (KKT) conditions according to the femto tier BS density. We also formulate and compare the coverage probability and the energy efficiency in HCN scenarios with and without coordinated multi-point (CoMP) to avoid coverage holes
Chapter Energy Efficiency for 5G Multi-Tier Cellular Networks
This chapter provides an introduction to quantifying the energy consumed by software. It is written for computer scientists, software engineers, embedded system developers and programmers who want to understand how to measure the energy consumed by the code they write in order to optimize for energy efficiency. We start with an overview of the electrical foundations of energy measurement and show how these are applied by reviewing the most commonly found energy sensing techniques. This is followed by a brief discussion of the signal processing required to obtain energy consumption data from sensing. We then present two energy measurement systems that are based on sensing techniques. Both can be used to directly measure the energy consumed by software running on embedded systems without the need to modify the hardware. As an alternative, regression-based techniques can be used to infer energy consumption based on monitoring events during program execution using counters monitors offered by the hardware. We introduce the foundations of regression analysis and illustrate how an energy model for an ARM processor can be built using linear regression. In the conclusion, we offer a wider discussion on what should be considered when selecting an energy measurement technique
How to Solve the Fronthaul Traffic Congestion Problem in H-CRAN?
The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as heterogeneous cloud radio access network (H-CRAN) has become a challenging task that requires the most effective utilization of fronthaul network resources. In this paper, we propose and analyze possible solutions to facilitate the fronthaul traffic congestion in the scenario of Coordinated Multi-Point (CoMP) for 5G cellular traffic which is expected to reach ZetaByte by 2017. In particular, we propose to use distributed compression to reduce the fronthaul traffic for H-CRAN. Unlike the conventional approach where each coordinating point quantizes and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user messages are conducted in a joint manner. Our results reveal that, in both dense and ultra-dense urban small cell deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate by more than 50% via joint operation
An Upper Bound on Multi-hop Transmission Capacity with Dynamic Routing Selection
This paper develops upper bounds on the end-to-end transmission capacity of
multi-hop wireless networks. Potential source-destination paths are dynamically
selected from a pool of randomly located relays, from which a closed-form lower
bound on the outage probability is derived in terms of the expected number of
potential paths. This is in turn used to provide an upper bound on the number
of successful transmissions that can occur per unit area, which is known as the
transmission capacity. The upper bound results from assuming independence among
the potential paths, and can be viewed as the maximum diversity case. A useful
aspect of the upper bound is its simple form for an arbitrary-sized network,
which allows insights into how the number of hops and other network parameters
affect spatial throughput in the non-asymptotic regime. The outage probability
analysis is then extended to account for retransmissions with a maximum number
of allowed attempts. In contrast to prevailing wisdom, we show that
predetermined routing (such as nearest-neighbor) is suboptimal, since more hops
are not useful once the network is interference-limited. Our results also make
clear that randomness in the location of relay sets and dynamically varying
channel states is helpful in obtaining higher aggregate throughput, and that
dynamic route selection should be used to exploit path diversity.Comment: 14 pages, 5 figures, accepted to IEEE Transactions on Information
Theory, 201
Cooperative wireless networks
In the last few years, there have been a lot of interests in wireless ad-hoc networks as
they have remarkable commercial and military applications. Such wireless networks
have the benefit of avoiding a wired infrastructure. However, signal fading is a severe
problem for wireless communications particularly for the multi-hop transmissions in
the ad-hoc networks. Cooperative communication has been proposed as an effective
way to improve the quality of wireless links. The key idea is to have multiple wireless
devices at different locations cooperatively share their antenna resources and aid
each other’s transmission.
In this thesis, we develop effective algorithms for cooperative wireless ad-hoc
networks, and the performance of cooperative communication is measured based
on various criteria, such as cooperative region, power ratio and end-to-end performance.
For example, the proposed interference subtraction and supplementary cooperation
algorithms can significantly improve network throughput of a multi-hop routing.
Comprehensive simulations are carried out for all the proposed algorithms and
performance analysis, providing quantitative evidence and comparison over other
schemes. In our view, the new cooperative communication algorithms proposed
in this research enable wireless ad-hoc networks to improve radio unreliability and
meet future application requirements of high-speed and high-quality services with
high energy efficiency. The acquired new insights on the network performance of
the proposed algorithms can also provide precise guidelines for efficient designs of
practical and reliable communications systems. Hence these results will potentially
have a broad impact across a range of related areas, including wireless communications,
network protocols, radio transceiver design and information theory
Game Theoretic Efficient Radio Resource Allocation in 5G Resilient Networks:A Data Driven Approach
In recent years, 5G resilient networks have gained significant attention in the wireless industry. The prime concern of commercial networks is to maximize network capacity to increase their revenue. However, in disaster situations during outages when cell sites are down, instead of capacity, coverage becomes predominant. In this paper, we propose a game theory–based optimal resource allocation scheme, while aiming to maximize the sum rate and coverage probability for the uplink transmissions in disaster situations. The proposed hierarchical game theoretical framework optimizes the uplink performance in multitier heterogeneous network with pico base stations and femto access points overlaid under a macro base station. The test simulations are based on a real‐time data set obtained for a predefined amount of time. The data statistics are then manipulated to create practical disaster situations. The solution for the noncooperative game has been obtained by using pure strategy Nash equilibrium. We perform simulations with different failure rates and the results show that the proposed scheme improves the sum rate and outage probability by significant margin with or without disaster scenario
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