The explosive demand for data has called for solution approaches that range from spectrally agile cognitive radios with novel spectrum sharing, to use of higher frequency spectrum as well as smaller and denser cell deployments with diverse access technologies, referred to as heterogeneous networks (HetNets). Simultaneously, advances in electronics and storage, has led to the advent of wireless devices equipped with multiple radio interfaces (e.g. WiFi, WiMAX, LTE, etc.) and the ability to store and efficiently process large amounts of data. Motivated by the convergence of HetNets and multi-platform radios, we propose HetNetwork Coding as a means to utilize the available radio interfaces in parallel along with network coding to increase wireless data throughput. Specifically we explore the use of random linear network coding at the network layer where packets can travel through multiple interfaces and be received via multihoming. Using both simulations and experimentation with real hardware on WiFi and WiMAX platforms, we study the scaling of throughput enabled by such HetNetwork coding. We find from our simulations and experiments that the use of this method increases the throughput, with greater gains achieved for cases when the system is heavily loaded or the channel quality is poor. Our results also reveal that the throughput gains achieved scale linearly with the number of radio interfaces at the nodes.
Heterogeneous networks have been studied for increasing the LTE throughput and coverage area by using a variety of cell sizes, access techniques and transmit powers @cite_18 @cite_31 . There are many technical challenges associated with HetNets such as resource allocation, interference, backhauling and handover among others and some of which is addressed by authors in @cite_16 @cite_32 . HetNets are being considered as the major solution to handle the huge data traffic demand in cellular networks and methods to efficiently and effectively model these are discussed in @cite_10 .
@cite_18 @cite_32 @cite_31 @cite_16 @cite_10
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As the spectral efficiency of a point-to-point link in cellular networks approaches its theoretical limits, with the forecasted explosion of data traffic, there is a need for an increase in the node density to further improve network capacity. However, in already dense deployments in today's networks, cell splitting gains can be severely limited by high inter-cell interference. Moreover, high capital expenditure cost associated with high power macro nodes further limits viability of such an approach. This article discusses the need for an alternative strategy, where low power nodes are overlaid within a macro network, creating what is referred to as a heterogeneous network. We survey current state of the art in heterogeneous deployments and focus on 3GPP LTE air interface to describe future trends. A high-level overview of the 3GPP LTE air interface, network nodes, and spectrum allocation options is provided, along with the enabling mechanisms for heterogeneous deployments. Interference management techniques that are critical for LTE heterogeneous deployments are discussed in greater detail. Cell range expansion, enabled through cell biasing and adaptive resource partitioning, is seen as an effective method to balance the load among the nodes in the network and improve overall trunking efficiency. An interference cancellation receiver plays a crucial role in ensuring acquisition of weak cells and reliability of control and data reception in the presence of legacy signals. Disruptive innovations in mobile broadband system design are required to help network providers meet the exponential growth in mobile traffic demand with relatively flat revenues per bit. Heterogeneous network architecture is one of the most promising low-cost approaches to provide significant areal capacity gain and indoor coverage improvement. In this introductory article, we provide a brief overview of heterogeneous network architectures comprising hierarchical multitier multiple radio access technologies (RAT) deployments based on newer infrastructure elements. We begin with presenting possible deployment scenarios of heterogeneous networks to better illustrate the concepts of multitier and multi-RAT. We then focus on multitier deployments with single RAT and investigate the challenges associated with enabling single frequency reuse across tiers. Based on the spectrum usage, heterogeneous networks can be categorized into single carrier usage, where all devices within the network share the same spectrum, and distinct carrier usage, where different types of devices are allocated separate spectra. For single carrier usage, we show that interference management schemes are critical for reducing the resulting cross-tier interference, and present several techniques that provide significant capacity and coverage improvements. The article also describes industry trends, standardization efforts, and future research directions in this rich area of investigation. 3GPP LTE-Advanced has recently been investigating heterogeneous network (HetNet) deployments as a cost effective way to deal with the unrelenting traffic demand. HetNets consist of a mix of macrocells, remote radio heads, and low-power nodes such as picocells, femtocells, and relays. Leveraging network topology, increasing the proximity between the access network and the end users, has the potential to provide the next significant performance leap in wireless networks, improving spatial spectrum reuse and enhancing indoor coverage. Nevertheless, deployment of a large number of small cells overlaying the macrocells is not without new technical challenges. In this article, we present the concept of heterogeneous networks and also describe the major technical challenges associated with such network architecture. We focus in particular on the standardization activities within the 3GPP related to enhanced intercell interference coordination. Imagine a world with more base stations than cell phones: this is where cellular technology is headed in 10-20 years. This mega-trend requires many fundamental differences in visualizing, modeling, analyzing, simulating, and designing cellular networks vs. the current textbook approach. In this article, the most important shifts are distilled down to seven key factors, with the implications described and new models and techniques proposed for some, while others are ripe areas for future exploration.