Energy‐efficient relay deployment in cellular systems using fractional frequency reuse and transmit antenna selection techniques

To cope with the steep surge in mobile traffic, network operators are now expanding their infrastructure for mobile access networks. However, since energy costs and greenhouse gas emissions are a large burden to network operators, they are making great efforts to improve the energy efficiency (EE) of their networks by promising techniques, including relaying and multiple‐input multiple‐output (MIMO). Relaying technique can considerably improve the EE when the interference between base stations (BSs) and relay stations (RSs) is effectively coordinated by an elaborate relay deployment using the fractional frequency reuse (FFR) technique. Also, MIMO techniques improve the radio channel quality through diversity gains, so the system capacity and the EE can be improved. Therefore, a combination of relaying/MIMO techniques can be considered to achieve the higher performance, particularly, if the system complexity and costs of using such techniques are low. Since the transmit antenna selection (TAS), one of MIMO techniques, can provide a sufficient transmit diversity gain and satisfy the requirements for low complexity and cost (thus, practical), the TAS is recommended for use with the relaying technique. In this paper, for an energy‐efficient relay deployment using FFR and TAS techniques, we derive the EE and the resource partitioning according to RS positions and the number of BS antennas by a mathematical analysis. Then, the optimal RS positions according to the number of antennas can be determined by an optimization approach. The numerical and simulation results indicate that the proposed analysis method can efficiently analyze the EE and locate the RSs.     

On the Ergodic Capacity and Energy Efficiency for Fading MIMO NOMA Systems

Non-orthogonal multiple access (NOMA) is expected to be a promising multiple access techniques for 5G networks due to its superior spectral efficiency (SE). Previous research mainly focus on the design to improve the SE performance with instantaneous channel state information (CSI). In this paper, we consider the fading MIMO channels with only statistical CSI at the transmitter, and explore the potential gains of MIMO NOMA scheme in terms of both ergodic capacity and energy efficiency (EE). The ergodic capacity maximization problem is first studied for the fading multiple-input multiple-output (MIMO) NOMA systems. We derive the optimal input covariance structure and propose both optimal and low complexity suboptimal power allocation schemes to maximize the ergodic capacity of MIMO NOMA system. For the EE maximization, the optimization problem is formulated to maximize the system EE (defined by ergodic capacity under unit power consumption) under the total transmit power constraint and the minimum rate constraint of the weak user. By transforming the EE maximization problem into an equivalent one-dimensional optimization problem, the optimal power allocation for EE design is proposed. To further reduce the computation complexity, a near-optimal solution based on golden section search and suboptimal closed form solution are proposed as well. Numerical results show that the proposed NOMA schemes significantly outperform the traditional orthogonal multiple access scheme with traditional orthogonal multiple access transmission in terms of both SE and EE.     

Multipath multihop mmWave backhaul in ultra-dense small-cell network

Ultra-Dense Network (UDN) is considered to be the key enabler for realizing capacity goals set by 5G. The major concern in UDN deployment is the backhaul network, which should be scalable, cost-effective, and have sufficient capacity to support massive small cell traffic. Otherwise, the backhaul can become the bottleneck of the network. In this paper, we propose a wireless backhaul solution for UDN deployment by considering MultiPath-MultiHop (MPMH) backhaul architecture in mmWave frequency band. In addition, we propose a distributed routing scheme to forward the backhaul traffic over the multihop network. Backhaul capacity and line-of-sight probability of the proposed backhaul architecture for various picocell densities were compared with direct, multiple-association, and multihop backhaul schemes under interference limited scenarios in outdoor and indoor small cell deployments. The simulation results indicate that the MPMH mmWave backhaul is the most cost-effective and scalable solution for UDN deployment.     

Dynamic Cooperative Base Station Selection Scheme for Downlink CoMP in LTE-Advanced Networks

Coordinated Multi-Point (CoMP) transmission is a technique proposed to enhance the spectral efficiency and system throughput in an interference limited cellular networks. In CoMP joint processing (JP) scheme multiple base stations (BSs) are coordinately transmit data streams to each user. As more than two base stations are involved, abundant spatial resources are exploited and more backhaul spectrum for JP cooperation is required. The backhaul architecture for CoMP JP is crucial to provide low latency, unlimited capacity, less power consumption, and perfect synchronization among the BSs. However, satisfying all these constraints is impossible as the number of cooperative BSs increases for each user. In this paper, a dynamic cooperative base station selection scheme is proposed to reduce the backhaul load for CoMP user by selecting the appropriate number of coordinated BSs from the CoMP cluster to ensure the certain quality of service (QoS). In particular, for cell edge user the number of cooperative BSs per user has been selected in order to achieve reduced overhead and the allocation of backhaul capacity is performed under the max–min fairness criterion. Simulation results show that the proposed selection scheme achieves significant performance improvement than other transmission modes in terms of the average sum rate per backhaul use and minimal total power consumption.     

Designing multihop wireless backhaul networks with delay guarantees

As wireless access technologies improve in data rates, the problem focus is shifting towards providing adequate backhaul from the wireless access points to the Internet. Existing wired backhaul technologies such as copper wires running at DSL, T1, or T3 speeds can be expensive to install or lease, and are becoming a performance bottleneck as wireless access speeds increase. Longhaul, non-line-of-sight wireless technologies such as WiMAX (802.16) hold the promise of enabling a high speed wireless backhaul as a cost-effective alternative. However, the biggest challenge in building a wireless backhaul is achieving guaranteed performance (throughput and delay) that is typically provided by a wired backhaul. This paper explores the problem of efficiently designing a multihop wireless backhaul to connect multiple wireless access points to a wired gateway. In particular, we provide a generalized link activation framework for scheduling packets over this wireless backhaul, such that any existing wireline scheduling policy can be implemented locally at each node of the wireless backhaul. We also present techniques for determining good interference-free routes within our scheduling framework, given the link rates and cross-link interference information. When a multihop wireline scheduler with worst case delay bounds (such as WFQ or Coordinated EDF) is implemented over the wireless backhaul, we show that our scheduling and routing framework guarantees approximately twice the delay of the corresponding wireline topology. Finally, we present simulation results to demonstrate the low delays achieved using our framework.     

Tradeoff between energy efficiency and spectral efficiency in a delay constrained wireless system

Because of the inevitable trend of green networking, energy efficiency (EE) is quickly becoming one of the key performance metrics to evaluate wireless communication systems, together with spectrum efficiency (SE) and quality of service (QoS) that have been traditionally used. This paper studies the fundamental tradeoff between EE and SE in the presence of statistical QoS requirements in wireless transmission systems. Earlier studies have shown that the performance with QoS requirements in the wireless transmission can be measured through effective capacity, which can capture the physical layer fading channel characteristics in the link layer QoS requirements, such as delay and data rate. Under this context, SE is defined as effective capacity per unit frequency bandwidth, and EE is defined as energy consumed per effective capacity bit. Both circuit power and transmission power are considered in the energy model, based on which we derive the quasi‐convex generalized EE formulation. To exploit the tradeoff between EE and SE with QoS considerations, we propose a generic close‐form approximation for EE–SE formulation by employing a curve fitting approach. The impacts of QoS and circuit power consumption on EE–SE tradeoff are respectively analyzed. QoS requirement and circuit power consumption affect the EE–SE tradeoff differently. In the low‐SNR regime, circuit power shows more impact on the EE–SE tradeoff, whereas QoS impacts EE–SE tradeoff more in the high‐SNR regime. Copyright © 2014 John Wiley & Sons, Ltd.     

Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity

Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.     

A Multichannel Scheduler for High-Speed Wireless Backhaul Links with Packet Concatenation

Capacity has been an important issue for many wireless backhaul networks. Both the multihop nature and the large per packet channel access overhead can lead to its low channel efficiency. The problem may get even worse when there are many applications transmitting packets with small data payloads, e.g., Voice over Internet Protocol (VoIP). Previously, the use of multiple parallel channels and employing packet concatenation were treated as separate solutions to these problems. However, there is no available work on the integrated design and performance analysis of a complete scheduler architecture combining these two schemes. In this paper, we propose a scheduler that concatenates small packets into large frames and sends them through multiple parallel channels with an intelligent channel selection algorithm between neighboring nodes. Besides the expected capacity improvements, we also derive delay bounds for this scheduler. Based on the delay bound formula, call admission control (CAC) of a broad range of scheduling algorithms can be obtained. We demonstrate the significant capacity and resequencing delay improvements of this novel design with a voice-data traffic mixing example, via both numerical and simulation results. It is shown that the proposed packet concatenation and channel selection algorithms greatly outperform the round-robin scheduler in a multihop scenario.     

Improving Cooperative Transmission Feasibility by Network Reconfiguration in Limited Backhaul Networks

For coordinated multi-point (CoMP), sets of base stations (BSs) have to be selected to jointly serve user equipments (UEs). These sets are typically selected based on wireless characteristics only. However, using CoMP also poses strict capacity and latency requirements on the backhaul network. Hence, these requirements additionally need to be taken into account when selecting BSs for CoMP. We have developed a mixed integer linear program and a BSs selection heuristic for CoMP that takes into account both aspects: the wireless channels and the backhaul network status. This heuristic can also identify which bottlenecks in the backhaul network make a desired BSs selection infeasible. We exploit this to dynamically reconfigure the backhaul network to the wireless requirements. Our simulations show that the heuristic’s solution quality is close to the optimum while execution time and memory consumption are reduced by multiple orders of magnitude compared to solving the problem via mathematical optimization. In addition, we simulate the network reconfiguration in different backhaul network scenarios. The results illustrate how our approach helps to better exploit available backhaul resources.     

回传链路容量受限条件下分布式大规模MIMO系统的联合用户调度及天线选择(英文)

Massive MIMO systems offer a high spatial resolution that can drastically increase the spectral and/or energy efficiency by employing a large number of antennas at the base station(BS).In a distributed massive MIMO system,the capacity of fiber backhaul that links base station and remote radio heads is usually limited,which becomes a bottleneck for realizing the potential performance gain of both downlink and uplink.To solve this problem,we propose a joint antenna selection and user scheduling which is able to achieve a large portion of the potential gain provided by the massive MIMO array with only limited backhaul capacity.Three sub-optimal iterative algorithms with the objective of sumrate maximization are proposed for the joint optimization of antenna selection and user scheduling,either based on greedy fashion or Frobenius-norm criteria.Convergence and complexity analysis are presented for the algorithms.The provided Monte Carlo simulations show that,one of our algorithms achieves a good tradeoff between complexity and performance and thus is especially fit for massive MIMO systems.     

Radio versus backhaul bottlenecks: an integrated quality of service provisioning approach for small cell gateways

Small cell traffic is expected to experience a continuous increase during the upcoming years, and thus, backhauling challenges should be timely addressed. Regardless the fact that radio resource management continues to be a major research problem in coexisting heterogeneous wireless networks, a mentality shift is observed in the research community towards dealing with wired backhaul bottleneck situations, too. Hence, specific small cell network deployments such as the one considered in this paper have to adopt an integrated quality of service provisioning approach. A femtocell utilizing an existing internet protocol (IP) infrastructure has usually to share the backhaul capacity with several IP networks. As these networks do not provide an efficient admission control process, the capacity allocated to the femtocell can fluctuate unpredictably over time. As a remedy, we propose a scheme for small cells' efficient integration (SCEI) in the IP infrastructure. SCEI is able to manage the total incoming traffic load and continuously adjust the distribution of the backhaul capacity among the existing networks. Simulation results show that SCEI provides significantly higher utilization of the backhaul capacity and more resilience regarding quality‐of‐service‐related metrics in overload state situations compared with state‐of‐the‐art hybrid partitioning techniques. Finally, this work also provides hints on ways that SCEI concepts can be applicable in more future Internet and small cell network deployment variants. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimal transmit antenna selection using hybrid algorithm for massive MIMO technology

Massive multiple input multiple output (M-MIMO) methods make reference to a useful method for using multipath propagation to communicate and receive multiple data signals at once over a single radio channel. To simultaneously transfer numerous data streams, it makes use of various antennas. The quantity of power used grows as the quantity of antennas rises. As a result, choosing the best transmit antennas, which is a major difficulty in M-MIMO systems, becomes important. In this research, “Hybrid Sea Lion-Whale Algorithm (HS-WA)” is introduced by choosing a best transmit antenna while taking into account several objectives. This method optimizes overall capacity and efficiency. The chosen method combines the “Whale Optimization Algorithm (WOA) and Sea Lion Optimization Algorithm (SLnO)” that determines which antenna should be chosen while also optimizing the antenna quantity. Finally, energy efficiency (EE) and capacity analysis results demonstrate that the provided approach is superior to all other models.     

Smart Backhauling for 5G Heterogeneous Network with Millimeter Wave Backhaul Links to Perform Switching Off,Interference Management and Backhaul Routing

Developments made in the fifth generation (5G) and the cellular networks have greatly influenced the lifestyle of the wireless users. Increased demand on higher data rates has also increased the network traffic. In the viewpoint of cellular networks, several Small Cells (SCs) are combined together with the help of microwave communications and millimeter wave communication models, in order to support the heterogeneous environments. In this paper, we have proposed a hybrid communication framework which can efficiently support the interference management, routings in backhaul links and the joint issue during on/off status of the mobile using 5G mmWave backhaul links. A novel cache-enabled technology is designed to develop backhaul links using heuristic search models. Along with that, an effective data access framework is also formulated using distance based cluster head selection that resolves the interference issues. Without modifying the content of the mobile users, the services are offered to the uses associated with backhaul links. Since a fast iterative model is developed, the throughput rate and the energy savings are maximized. A simulation analysis is carried out with a static number of mobile nodes which has proved the efficiency of the proposed framework.

     

Performance optimization of cell-free massive MIMO system with power control approach

The cell-free massive MIMO (multiple-input multiple-output) system involves a large number of access points serving a smaller number of mobile users (MUs) over identical time/ frequency resource. By providing large number of service antennas closer to the MUs, the cell-free massive MIMO can offer great spectral efficiency, better macro-diversity and minimal path loss. Despite several advantages, the cell-free massive MIMO suffers from energy overloading caused by uncontrolled backhaul power consumption for large number of distributed access points (APs) and pilot contamination during channel estimation. In this paper, we have taken into consideration a cell-free massive MIMO system with APs equipped with multiple antennas performing time-division-duplex (TDD) operation. Here, all the APs coordinate through a constrained backhaul network for joint transmission of signals to all the users simultaneously by multiplying the received signal with the normalized conjugate of the estimated channel state information (CSI) and send back a rounded off version of the weighted pattern to the central processing unit (CPU). Finally, an effective user defined algorithm is presented involving selection and grouping of various APs based on their individual contributions for a particular MU to improve the overall performance of the system.     

Energy Efficiency Improvements in Heterogeneous Network Through Traffic Load Balancing and Sleep Mode Mechanisms

Heterogeneous network (HetNet) is one of the most promising approaches of IMT Advanced, which not only offers higher capacity and data rate, but also network Energy Efficiency (EE). HetNet is an advanced network that promotes complex cooperation between multiple tiers or sizes of base stations, i.e. macro, micro, pico, and femto base stations towards the above benefits. In this paper, a theoretical model for evaluating the EE of HetNet is proposed. Then, a sleep mode mechanism on picocells is proposed to reduce the total energy consumption which subsequently improves the EE. Simulation results show that EE can be increased by balancing the traffic load between different types of base stations. In fact, the improvement very much depends on the percentage of traffic that is offloaded to picocells. At low to medium traffic load conditions, significant improvements in EE can be observed through the proposed sleep mechanism. It is observed that by combining the sleep mode feature of picocells and load balancing between the different types of base stations in HetNet, further EE improvements up to 68 % for low traffic load and up to 33 % for medium traffic load can be achieved.     

小小区网络中基于本地存储协作传输策略的增益

网络的密集化是满足未来移动通信系统高吞吐量需求的有效手段,但当业务负载高时其吞吐量受到小区间干扰的严重制约。在基站端存储流行文件可以降低回传链路的成本和文件的下载时间,也为无需高容量回传链路进行基站协作提供了可能。本文分析了在小基站部署存储器后基站协作所能带来的吞吐量增益,推导了基于存储的基站协作策略的平均吞吐量,并与无干扰管理的基准小小区网络的吞吐量进行比较。分析和仿真结果表明,本地存储带来的性能增益在网络负载较高时和文件请求分布集中时非常明显。      

An energy-efficient power allocation scheme for millimeter-wave MIMO-NOMA systems

There are many challenges in fifth generation (5G) telecommunication systems, due to the increasing demands and applications. The most important of which are need to have higher energy efficiency (EE) and spectral efficiency (SE). They are critical in the practical multiple-input multiple-output (MIMO) telecommunication systems. Non-orthogonal multiple access (NOMA) methods and millimeter-waves can be used in conjunction with MIMO systems to improve their EE and SE performance. In this paper, we investigate the application of NOMA and mm-Wave transmission in the downlink of MIMO systems. Then, we formulate the optimization problem for users in MIMO-NOMA systems to maximize the EE that is subject to minimum data rate to satisfy required quality of service (QoS) and maximum transmission power. To achieve the optimal power allocation for users, we reach a problem for the EE maximization that is non-convex and solution of the optimization problem is not trivial. We exploit a lower bound of the data rate and the Lagrange dual function to convert it to a convex and unconstrained problem, which is easy to solve. In the next step, we derive a relation for determining the optimal power allocation of users. In addition, a numerical algorithm is presented that can be used to solve the problem. According to the simulation results of the proposed algorithm, our method performs better and provides higher EE than both orthogonal multiple access and equal power allocation schemes.     

Energy‐efficient cluster division for multi‐cell joint transmission technology

Coordinated Multi‐Point (CoMP) is an effective way to improve user performance in next‐generation wireless cellular networks, such as 3GPP LTE‐Advanced(LTE‐A). The base station cooperation can reduce interference, and increase the signal to interference and noise ratio (SINR) of cell‐edge users and improve the system capacity. However, the base station cooperation also adds additional power consumption for signal processing and sharing information through back‐haul links between cooperative base stations. As such, CoMP may potentially consume more energy. This paper studies such energy consumption issue in CoMP, presents a semi‐dynamic CoMP cluster division algorithm based on energy efficiency (SCCD‐EE) that can effectively adapt to users' real‐time interference, and employs the idea of Maximal Independent Set (MIS) to solve the problem of cluster overlapping. To verify the feasibility of the proposed algorithm, this paper performs comprehensive evaluations in terms of energy efficiency and system capacity. The simulation results show that the proposed semi‐dynamic cluster division algorithm can not only improve the system capacity and the quality of service (QoS) of cell‐edge users, but also achieve higher network energy efficiency compared with static cluster methods and Non‐CoMP approaches. Copyright © 2016 John Wiley & Sons, Ltd.     

Downlink energy efficiency modeling and optimization with backhaul awareness and interference price in ultra cellular HetNet

The cellular heterogeneous network(HetNet) with ultra dense small cells is called ultra cellular HetNet.The energy efficiency for this network is very important for future green wireless communications.The data rates and power consumptions for three parts(i.e.,macro cells,small cells,and mixed backhaul links) in ultra cellular HetNet are jointly formulated to model downlink energy efficiency considering the active base stations(BSs) and inactive BSs.Then,in order to decrease the downlink co-channel interference,the interference price functions are also jointly set up for the three parts in ultra cellular HetNet.Next,energy efficiency optimization iterative algorithm scheme using the fractional programming and Lagrangian multiplier with constraints for density of ultra dense small cells and fraction of mixed backhaul links is presented with interference pricing.The convergence and computation complexity are also proved in this scheme.The numerical simulations finally demonstrate convergence behavior of the proposed algorithm.By comparison,some conclusion can be drawn.Maximizing energy efficiency of system is lower as the density of small cell is high.The effect on maximizing energy efficiency with interference price outperforms that without interference price.And the energy efficiency increases as the fraction of mixed backhaul links is higher because of more power consumption in the microwave backhaul links.     

多无线电协作技术与异构网络融合

异构网络融合是未来网络技术发展的必然趋势。异构网络的融合面临着高延迟、高消耗、低速率等诸多方面的“瓶颈”。为克服这些“瓶颈”,满足异构网络融合的需求,多无线电协作技术应运而生。通过多无线电间的相互协作和对多无线电资源的有效管理及合理分配,能够有效地提高网络吞吐量,降低无线设备的能量消耗,减少异构网络间切换的延迟,从而为实现真正的异构网络无缝融合提供了可能。