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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Next generation cellular systems are expected to entail a wide variety of wireless coverage zones, with cells of different sizes and capacities that can overlap in space and share the transmission resources. In this scenario, which is referred to as Heterogeneous Networks (HetNets), a fundamental challenge is the management of the handover process between macro, femto and pico cells. To limit the number of handovers and the signaling between the cells, it will hence be crucial to manage the user’s mobility considering the context parameters, such as cells size, traffic loads, and user velocity. In this paper, we propose a theoretical model to characterize the performance of a mobile user in a HetNet scenario as a function of the user’s mobility, the power profile of the neighboring cells, the handover parameters, and the traffic load of the different cells. We propose a Markov-based framework to model the handover process for the mobile user, and derive an optimal context-dependent handover criterion. The mathematical model is validated by means of simulations, comparing the performance of our strategy with conventional handover optimization techniques in different scenarios. Finally, we show the impact of the handover regulation on the users performance and how it is possible to improve the users capacity exploiting context information. Heterogeneous networks consisting of small cells (e.g. femtocells) are capable of achieving high capacity and improving indoor cellular coverage area, while the fractional frequency reuse (FFR) scheme has been proposed for upcoming and future cellular systems to improve spectral efficiency in cellular OFDM networks. In two-tier networks of macrocells layered with femtocells, the resource allocation will most likely be sharing the same licensed spectrum. In this paper, we formulate a simple femtocells resource allocation strategies that allows a femtocells base station (FBS) to allocate more resources (co-channel) in high usage areas such as commercial FBS (cFBS) and orthogonal resource allocation for randomly deployed home user FBS (hFBS). We analyze our strategy in a multi-cell systems using area spectral efficiency (ASE) in composite fading consisting of Nakagami-m fading, path-loss and log-normal shadowing. Analytical and simulation results show that our simple resource allocation strategies are able to reduce inter-tier interferences and to offer an improvement in the overall spectral efficiency of the two-tier systems. Heterogeneous wireless networks (HetNets) provide a powerful approach to meeting the dramatic mobile traffic growth, but also impose a significant challenge on backhaul. Caching and multicasting at macro and pico base stations (BSs) are two promising methods to support massive content delivery and reduce backhaul load in HetNets. In this paper, we jointly consider caching and multicasting in a large-scale cache-enabled HetNet with backhaul constraints. We propose a hybrid caching design consisting of identical caching in the macro-tier and random caching in the pico-tier, and a corresponding multicasting design. By carefully handling different types of interferers and adopting appropriate approximations, we derive tractable expressions for the successful transmission probability in the general signal-to-noise ratio (SNR) and user density region as well as the high SNR and user density region, utilizing tools from stochastic geometry. Then, we consider the successful transmission probability maximization by optimizing design parameters, which is a very challenging mixed discrete-continuous optimization problem. By exploring structural properties, we obtain a near optimal solution with superior performance and manageable complexity. This solution achieves better performance in the general region than any asymptotically optimal solution, under a mild condition. The analysis and optimization results provide valuable design insights for practical cache-enabled HetNets. We consider a heterogeneous cellular network (HetNet) where a macrocell tier with a large antenna array base station (BS) is overlaid with a dense tier of small cells (SCs). We investigate the potential benefits of incorporating a massive MIMO BS in a TDD-based HetNet and we provide analytical expressions for the coverage probability and the area spectral efficiency using stochastic geometry. The duplexing mode in which SCs should operate during uplink macrocell transmissions is optimized. Furthermore, we consider a reverse TDD scheme, in which the massive MIMO BS can estimate the SC interference covariance matrix. Our results suggest that significant throughput improvement can be achieved by exploiting interference nulling and implicit coordination across the tiers due to flexible and asymmetric TDD operation.