On optimal relay placement for improved performance in non-coverage limited scenarios

More flexible spectrum access policies that take advantage of the cognitive radio capabilities of small cells are required to improve the suboptimal spectrum utilization at small cells. However, care must be taken to ensure that interference from autonomously deployed small cells is tightly controlled when developing such policies. This paper presents a dynamic spectrum access framework that enables small cells employing a specific Radio Access Technology (RAT) to access the spectrum allocated to other RATs as secondary users without degrading the performance of primary RATs. Secondary small cells opportunistically access unutilized spectrum in their coverage area and the protection of primary RATs is achieved by preventing secondary small cells from accessing spectrum when a potential interference scenario is detected. A system where HSPA and LTE-Advanced are co-deployed is considered. Simulation results show that substantial performance gains for both RATs are achieved by increasing spectrum utilization through secondary access for small cells. Furthermore, gains are achieved without degrading the performance of primary RATs.

Heterogeneous Network (HetNet) where small cells served by Low Power Nodes (LPNs) are overlaid onto conventional macro cells is considered to meet the requirements of the increasing need for higher data rates. In this paper, we investigate the uplink interference situation in 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) HetNet and the corresponding impacts on the efficiency of UL link adaptation, with the focus on small cells. It is observed that the efficiency of UL link adaptation of LPN cells is seriously affected by a small number of dominant interferers. In addition, we study two Uplink Coordinated Multi-point (UL CoMP) schemes which exploit the fluctuation nature of UL interference strength to mitigate the influences. A simplified approach to perform cooperative link adaptation for HetNet is also addressed. System level simulations are carried out to evaluate these schemes, and promising performance gains are observed.

Deploying low-power nodes (LPNs) overlaid with Macro cells is a promising strategy to improve the coverage and capacity of cellular systems. Meanwhile, cell range expansion (CRE) scheme is proposed to select a proper serving base station (BS) for users between Macro eNodeBs and LPNs, and then offloading of traffic from Macro cell is made. In this paper, first, we introduce the LPNs deployment strategy and its activation criteria in the heterogeneous system. Then, a quality of experience (QoE)-based CRE scheme to adjust the coverage area of LPNs adaptively is proposed. Different from the existing CRE schemes, the QoE values for different users with different services are considered when the users try to select an appropriate serving BS. Finally, simulation results demonstrate that the proposed scheme can improve cell edge user experience for various services as well as overall system performance.

Small cells are low power nodes, which have lower transmit power than the macro eNodeB. They are regarded as one of the important solutions in long term evolution advanced (LTE-A) to deal with the dramatically increased mobile data traffic. Small cells deployments in LTE-A release 12 with 4 small cells in a cluster suffer from stronger inter-cell interference than heterogeneous network (HetNet) in the previous release of LTE-A, where one small cell exists in a cluster. We investigate the joint least squares channel estimation (JLSCE) over demodulation reference signals (DMRS) spreading in time and frequency resources in LTE-A systems. Furthermore, different receiver structures using least square channel estimation (LSCE) and JLSCE are investigated in small cell deployments with the presence of strong inter-cell interference. Our results show the linear minimum mean square error (LMMSE)-interference rejection combining (IRC) with LSCE is the most efficient receiver structure compared to the enhanced (e)LMMSE-IRC with JLSCE, interference cancellation (IC) with eLMMSE-IRC and maximum ratio combining (MRC) receiver structures for signal detection in small cell deployments.

Over the past decade, the telecommunication industry has witnessed excessive growth in the number of mobile users. Market forecasts envision that there will be nearly 8.6 billion mobile devices worldwide by 2017. This tremendous increase in the number of cellular users demands an expansion in the wireless Base Stations (BSs) for improved coverage and capacity. However, this hike in the deployment of base stations will lead to immense energy consumption, because in mobile networks 70–80 % of the power is consumed by BSs. This upsurge in the energy consumption of telecommunication networks implies an increase in CO\(_{2}\) emissions in the environment. In addition, energy bills also represent a major chunk of wireless network operators’ expenditures. These ecological and economical challenges have provoked the curiosity of telecommunication standardization bodies and researchers in an emerging research area termed ‘energy-aware Heterogeneous Networks (HetNets)’. HetNets are a mix of various cell shapes and sizes, including high power macro cells and low power nodes such as micro cells, pico cells and relays. The large macro cells are responsible for the basic coverage of the cell users, and the small cells are effective in providing higher data rates to their nearby users in dense areas with reduced power consumption. The combination of various BSs with different cell sizes and a wide range of power levels can lead to substantial gains in network energy consumption by creating hotspots and enabling dense spatial reuse. It is envisioned that a dense deployment of low power BSs will take place in the near future. HetNets in particular are considered as a promising solution for Fifth Generation (5G) in order to meet the exponentially growing demand for multimedia traffic. The main focus of this chapter is to investigate optimal energy efficient deployment strategies for low power nodes such as relays and small cells in 5G HetNets. In this chapter, a comprehensive overview of remarkable small cell deployment schemes is presented in order to facilitate the debate on technical challenges in deploying HetNets. It goes on to discuss some useful techniques to mitigate the severe interference in 5G dense HetNets. Finally, a novel Long Term Evolution (LTE)-Advanced relay deployment scheme is introduced using graph theory, not only to address some of the identified deficiencies of existing solutions, but also to optimize the energy efficiency of 5G cellular networks.

Power efficient ultra-wideband based wireless communication for wireless body area network applications

Wireless backhaul has been received much attention as an enabler of future broadband mobile communication systems because it can reduce deployment cost of pico-cells, an essential part of high capacity system. A high performance network in terms of high throughput, low average delay and low packet loss rate, is highly appreciated to sustain the increasing proliferation in multimedia transmissions. The critical issue reducing the performance of wireless backhaul is the interference occurred in the network due to simultaneous nodes transmissions. In this research, we propose a high performance wireless backhaul using the low interference sensitivity MIMO based nodes. MIMO transmission has a better BER performance over SISO one even with the same transmission rate and bandwidth, which means that MIMO can operate at lower SINR values than SISO and give the same performance. This MIMO robust performance against interference gives us a greater benefit when adopted as a wireless interface in wireless backhaul than SISO. These facts motivated us to use the IEEE 802.11n the current MIMO standard to design a MIMO based wireless backhaul. In addition and to justify our assumptions, we investigate the effect of MIMO channels correlation, a major drawback in MIMO transmission, upon the system performance, and prove the robustness of the scheme under different MIMO channels correlation values. After proving the effectiveness of MIMO as a wireless interface for wireless backhaul, we further improve the performance of this MIMO-backhaul using the high efficient Intermittent Periodic Transmit (IPT) protocol. IPT is a reduced interference packet forwarding protocol with a more efficient relay performance than conventional relay in which packets are transmitted continuously form the source nodes. By using these two techniques (IEEE 802.11n (MIMO) + IPT), wireless backhaul nodes can meet more demanding communication requirements such as higher throughput, lower average delay, and lower packet dropping rate than those achieved by simply applying IEEE 802.11n to conventionally relayed backhaul. The proposed wireless backhaul (MIMO+IPT) will accelerate introduction of picocell based mobile communication systems.

This paper presents an improved resource scheduling scheme by integrating cognitive radio into LTE-A self-organizing networks (SON). To avoid mass signaling overheads produced by traditional channel quality indicator (CQI) report mechanism in frequency scheduling, we particular adopt power sensing provided by low power nodes (LPNs) to compute the quality of each resource block (RB), then take advantage of the classical schedulers and construct a distributed adaptive resource allocation model for LPN in HetNets. Our work not only facilitates the frequency domain packet scheduling (FDPS) implementation with less computation complexity compared with traditional scheme. Simulation results also show that our proposed scheme can achieve considerable system performance improvement.

An Ultra-Dense Network (UDN) is foreseen as a key element of 5G, where small cells operating at millimeter-wave frequencies will be placed in hotspots to accommodate extreme traffic volumes. A fully distributed wired backhaul is not feasible in these UDN deployments because it is not practical to connect each small cell to the core over fiber. A likely substitute is wireless backhaul, where small cells are connected to one or few gateways over multi-hop millimeter-wave wireless links. The backhaul network capacity of the wireless backhaul is directly related to the average number of simultaneous transmissions in the wireless backhaul of an UDN. The problem of finding the average number of simultaneous transmissions is analogous to the minimum coloring problem, which is NP-Hard. In this paper, we adapt our previously proposed heuristic algorithm for solving this problem and then study the effect of varying the interference range of small cells on the backhaul network capacity. From the results of our Monte Carlo simulations, it is observed that the backhaul network capacity decreases significantly as the interference range increases.

Traditional macro-cell networks are experienced an increase of data traffic and small-cells are deployed help to offload the traffic from macro-cells. The Energy Aware Traffic Offloading for Green Heterogeneous Networks (EATOG) approach is analyzed on grid power saving by offloading traffic for green heterogeneous networks to increase the efficient utilization of harvested energy for on-grid power saving while satisfying the Quality of Service (QoS) requirement. The EATOG is mainly intends to of energy-aware traffic offloading for HCN with multiple Small cell Base Station (SBS) powered by diverse energy sources which reduces the on-grid network power consumption while satisfying the QoS requirement in terms of rate outage probability. The performance of energy consumption is degraded due to the Overlapped Small Cell Based Stations. An optimal deploying low power node within macrocell coverage area is proposed in this paper to improve the system utility while minimizing the installation cost. The proposed Optimized Energy Aware Traffic Offloading for Green Heterogeneous Networks (OEATOG) approach is considers the inter-cell interference and the configuration of Almost Blank Sub-frames (ABS) when maximizing the system utility. The proposed paper deals with the placement of Pico Base Station within the macro cell in LTE (Long Term Evolution) heterogeneous networks. A Pico Cell is a small cellular Base Station (BS) which supports low power nodes and offers greater capacity and coverage areas. Furthermore the heuristic algorithm is introduced too efficiently solve the formulated problem and obtain the optimal picocell placement. The simulation results indicate that the proposed algorithm is to improve the utility of the network, especially in regions with high traffic density, while maintaining the installation cost at a reasonable level.

In the present study self-backhauled small cells for LTE-Advanced (a particular kind of small cells with wireless backhauling) are analyzed from the energy efficiency point of view. We perform an assessment of system performances with respect to traditional homogeneous LTE-Advanced networks, not only in terms of capacity and energy consumption, but also showing the potential impacts on the Quality of Service (QoS) of the system. In particular the self-backhauled small cell architecture considered in this paper is based on the type I relay architecture specified in Release 10 of 3GPP. Moreover, a scheduling framework based on MBSFN subframe switching is described and proposed as potential enabler for further energy efficiency enhancements. In addition, a possible Centralized RAN (C-RAN) implementation is described, consisting in a partially centralized algorithm and the application of this mechanism in a centralized processing unit instructing local scheduling entities implemented in the protocol stack of Small Cells. The presence of these schedulers in conjunction with on-board sleep-modes can be a promising tool for maximizing energy efficiency benefits in conditions of low traffic load. System level simulation results showed that these Small Cells in urban and suburban environments can satisfy the need of increasing traffic demand by providing an higher energy efficiency without compromising the QoS and the system capacity.

By pushing computation to the mobile network edge, Multi-access Edge Computing (MEC) has been an enabler for the stringent latency and energy requirements of the new Internet of Things (IoT) services. On the other hand, ultra-dense heterogeneous networks with wireless backhaul have been proposed as a low-cost solution, allowing Network Operators (NOs) to extend the network capability, by deploying densified close-proximity small-cells and hence supporting a large number of low-latency low-energy IoT devices. In this paper, we study the problem of IoT task offloading in a MEC-enabled heterogeneous network, which to the best of our knowledge, is the first attempt to thoroughly explore the task offloading problem in a heterogeneous network with MEC support and wireless backhaul. We jointly optimize the offloading decision, transmission power, and the allocation of radio and computational resources, with the objective of minimizing the devices energy consumption, while respecting their latency deadline. We mathematically formulate our problem as a non-convex mixed-integer program, and due to its complexity, we propose an iterative algorithm based on the Successive Convex Approximation (SCA) method for providing an approximate solution on the original problem. Through numerical analysis, we perform simulations based on multiple scenarios, and find out how NOs can respond to the requested load and help in minimizing the total devices energy consumption.

In this study, the effects of decreasing clutter cell size on radar system performance are analyzed. The mean and variance of the clutter cross section for small clutter cells, characteristic of high resolution radar, are calculated. Typically, the statistical distribution of the clutter cross section is assumed to be exponential. As the clutter cell size decreases, however, the statistical distribution of the clutter cross section is no longer well modeled by an exponential distribution. The variance increases as the clutter cell size decreases. The calculated means and variances for small cell sizes were used as input parameters to four clutter cross section distribution functions and the effect on system performance examined. Because a definitive statistical distribution of the clutter cross section for small clutter cells has not been identified, four common distribution functions were used to represent the clutter statistics: the exponential; Weibull; chi-squared and log-normal. Detection probabilities were found to decrease as the cell size decreased due to the non-Gaussian clutter characteristics of small cells. In some cases, order of magnitude reductions in the probability of detections were observed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Small cells with wireless backhaul are promising, whereas challenges of severe overlapping coverage and strong interference are yet to be addressed. Coordinating small cells could resolve the challenges; however, existing multicell coordinated beamforming techniques involve high cost of communication overhead, synchronization and backhaul. Such problems may deteriorate in practical cellular applications, where there could be many users, each generating high channel feedback overhead to compete for an opportunity of being scheduled, and the downlink data signals of the coordinated cells need to be precisely synchronized at each of the users. We propose a new scheme, which cuts the overhead by 80% and enables the coordination to be practically implemented in a decentralized manner. Our scheme is a user-centric downlink scheduling approach, where mobile terminals trigger and participate in the scheduling decisions of small cells. We also develop a new recursive algorithm to optimize the quantization levels of mobile terminals' feedback, minimizing the feedback requirement. Analysis, confirmed by simulations, shows that our scheme is able to achieve 94.4% of the sum-rate upper-bound which can only be approached by idealized centralized coordination. In terms of throughput, given the 80% reduced overhead, our scheme is 139.5% better than the idealized centralized coordination approach.

We analyze an inband full-duplex access node that is serving mobile users while simultaneously connecting to a core network over a wireless backhaul link, utilizing the same frequency band for all communication tasks. Such wireless self-backhauling is an intriguing option for the next generation wireless systems since a wired backhaul connection might not be economically viable if the access nodes are deployed densely. In particular, we derive the optimal transmit power allocation for such a system in closed form under quality-of-service (QoS) requirements, which are defined in terms of the minimum data rates for each mobile user. For comparison, the optimal transmit power allocation is solved also for two reference scenarios: a purely half-duplex access node, and a relay-type full-duplex access node. Based on the obtained expressions for the optimal transmit powers, we then show that the systems utilizing a full-duplex capable access node have a fundamental feasibility boundary, meaning that there are circumstances under which the QoS requirements cannot be fulfilled using finite transmit powers. This fundamental feasibility boundary is also derived in closed form. The feasibility boundaries and optimal transmit powers are then numerically evaluated in order to compare the different communication schemes. In general, utilizing the purely full-duplex access node results in the lowest transmit powers for all the communicating parties, although there are some network geometries under which such a system is not capable of reaching the required minimum data rates. In addition, the numerical results indicate that a full-duplex capable access node is best suited for relatively small cells.