Customer experience is becoming of utmost importance for operators in home network management. Hence, a notion of the customers' QoE is vital, but has mostly been neglected in favor of QoS. In this article, we aim to close a significant gap between QoS and QoE in home networks by proposing a framework for inferring QoE from remotely collected network QoS metrics. We focus on video services (e.g., YouTube application) as the main contributor and generator of indoor network traffic. A case study is performed where an experimentally obtained dataset comprising network and application QoS parameters is obtained under varying conditions (i.e., poor coverage, network overload, contention, and interference). Predictive modeling is then used to build a predictor for multiple QoE classes given the network QoS metrics remotely accessible from access points based on industry adopted standards (i.e., TR-181). This enables operators to infer specific QoE metrics using remotely collected passive network measurement with no knowledge of application-specific parameters. We show that the proposed framework achieves accuracy in the range of 85 to 95 percent depending on the QoE class, hence demonstrating the effectiveness and potential of our approach.

In this paper, we investigate the dynamic small cell (SC) clustering strategy and their precoding design problem for interference coordination in two-tier heterogeneous networks (HetNets) with massive MIMO (mMIMO). To reduce interference among different SCs, an interference graph-based dynamic SC clustering scheme is proposed. Based on this, we formulate an optimization problem as design precoding weights at macro base station (MBS) and clustered SCs for maximizing the downlink sum rate of SC users (SUs) subject to the power constraint of each SC BS (SBS), while mitigating inter-cluster, eliminating inter-tier, intra-cluster and multi-macro user (MU) interference. To eliminate the inter-tier and multi-MU interference simultaneously, we propose a clustered SC block diagonalization precoding scheme for the MBS. Next, each SU’s precoding vector at clustered SCs is designed as the product of the following two parts. The first part is designed with singular value decomposition to remove the intra-cluster interference. The second part is designed to coordinate the inter-cluster interference for maximizing the downlink sum rate of SUs, which is a non-convex optimization problem and difficult to solve directly. A non-cooperative game-based distributed algorithm is proposed to obtain a suboptimal solution. Meanwhile, we prove the existence and uniqueness of Nash equilibrium for the formed game. Finally, simulation results verify the effectiveness of our proposed schemes.

This paper provides a comprehensive analysis of the energy efficiency performance for different relaying schemes over the non-Gaussian power line communication (PLC) channel. Specifically, amplify-and-forward (AF), decode-and-forward (DF), selective DF (SDF) and incremental DF (IDF) relaying systems are investigated. For a more realistic scenario, the power consumption profile of the PLC modems is assumed to consist of both dynamic and static power. For each system, we derive accurate analytical expressions for the outage probability and the minimum energy-per-bit performance. For the sake of comparison and completeness as well as to quantify the achievable gains, we also analyze the performance of a single-hop PLC system. Monte Carlo simulations are provided throughout this paper to validate the theoretical analysis. Results reveal that AF relaying over the non-Gaussian PLC channel does not always enhance the performance and that the IDF PLC system offers the best performance compared to all other schemes considered. It is also shown that increasing the channel variance, which is related to the PLC network branching, and impulsive noise probability can considerably deteriorate the system performance. Furthermore, when the end-to-end distance is relatively small, it is found that the single-hop PLC approach can perform better than AF relaying.

Relaying over power line communication (PLC) channels can considerably enhance the performance and reliability of PLC systems. This paper is dedicated to study and analyze the energy efficiency of multi-hop cooperative relaying PLC systems. Incremental decode-and-forward (IDF) relying is exploited to reduce the transmit power consumption. The PLC channel is assumed to experience log-normal fading with impulsive noise. The performances of single-hop and conventional DF relaying systems are also analyzed in terms of outage probability and energy efficiency for which analytical expressions are derived. Results show that using more relays can improve the outage probability performance; however, this is achieved at the expense of increased power consumption due to the increased static power of the relays, especially when the total source-to-destination distance is relatively small. Results also demonstrate that the IDF PLC system has better energy efficiency performance compared to the other schemes.

To alleviate the problem of scarce spectrum resources and meet the ever-increasing of mobile broadband data traffic demands, Licensed Assisted Access (LAA)-Long Term Evolution (LTE), operating in the unlicensed spectrum, is a promising solution. Considering that the unlicensed spectrum is shared by a few incumbent systems, such as IEEE 802.11 (i.e., WiFi), one main target is to guarantee the friendly and harmonious coexistence of LTE with other wireless systems in the unlicensed spectrum. Both listen-before-talk (LBT) and duty cycle methods are regarded as effective ways to solve the coexistence problem in academia and industry so far. Although there are a large number of theoretical researches on LTE in unlicensed spectrum (LTE-U), field trail results are still lacking. In this paper, an experimental testing platform is deployed to model the realistic environment. This paper focuses on three aspects. First, a typical indoor field trial scenario in 5.8 GHz unlicensed bands is deployed, and the performance of LTE-U and WiFi, including coverage and capacity, is evaluated. Specifically, a methodology to determine the proper clear channel assessment energy detection (CCA-ED) threshold for LTE-U is proposed to implement the friendly coexistence between LTE-U and WiFi systems. Second, supplementary downlink (SDL) and Cell ON/OFF mechanisms are investigated to verify the fair coexistence between LAA and WiFi in the unlicensed spectrum. Third, the Enhanced Cell ON/OFF scheme, which introduces Clear to Send (CTS)-to-Self (CTS2S) message, is discussed and evaluated. Based on the built testbed, we obtain threefold conclusions. First of all, introducing LTE into unlicensed spectrums can greatly improve the spectrum efficiency and optimize wireless resources. Furthermore, test results and analyses show that a proper CCA-ED threshold is necessary for coexisting friendly and fairly among different systems, and experiments are also provided to validate the feasibility of the suggested method in various scenarios. Second, experimental results show that SDL mechanism guarantees relatively friendly and harmonious coexistence between LAA and WiFi only in the sparse scenario, while basic Cell ON/OFF mechanism is more effective to ensure coexistence between LAA and WiFi than the SDL. Finally, with the introduction of CTS2S message, the Enhanced Cell ON/OFF scheme is able to achieve more peaceful coexistence between LTE and WiFi users employed in the same bands compared with the Basic Cell ON/OFF scheme.

Rising awareness and emergence of smart technologies have inspired new thinking in energy system management. Whilst integration of distributed energy resources in micro-grids (MGs) has become the technique of choice for consumers to generate their energy, it also provides a unique opportunity to explore energy trading and sharing amongst them. This paper investigates peer-to-peer (P2P) communication architectures for prosumers’ energy trading and sharing. The performances of common P2P protocols are evaluated under the stringent communication requirements of energy networks defined in IEEE 1547.3-2007. Simulation results show that the structured P2P protocol exhibits a reliability of 99.997% in peer discovery and message delivery whilst the unstructured P2P protocol yields 98%, both of which are consistent with the requirements of MG applications. These two architectures exhibit high scalability with a latency of 0.5 s at a relatively low bandwidth consumption, thus, showing promising potential in their adoption for prosumer to prosumer communication.

The upsurge in data traffic pushed Wi-Fi operators to adopt wireless extenders to improve indoor coverage. Existing deployment approaches, however, focused on coordinated scenarios (managed by the same operator) with single-hop communication. In this paper, we propose a self-deployment approach for finding the optimal placement of extenders in which both the wireless back-haul and front-haul throughputs of the extender are optimized. To that end, we propose an AI-CBR framework to enable autonomous self-deployment that allows the network to learn the environment by means of sensing and perception. New actions, i.e. extender positions, are created by problem-specific optimization and semi-supervised learning algorithms that balance exploration and exploitation of the search space. Wi-Fi standard compliant ns-3 simulations evaluated the proposed self-deployment AI approach and compared its performance against existing conventional coverage maximization approaches under practical uncoordinated scenarios. Throughput fairness and ubiquitous QoS satisfaction are achieved which provide the impetus of applying the AI-driven self-deployment in practice.

Cellular networks with hyper-dense deployment of small cells have been identified as the performance-optimizing architecture for fifth generation (5G) mobile systems. A thousand-fold capacity increase is projected when such networks benefit from aggressive spatial multiplexing and huge bandwidth, realizable with massive antenna arrays and millimeter-wave (mmWave) spectrum, respectively. As a precursor to the 5G projections, we show in this paper that network performance (cell capacity, user throughputs and spectral efficiency) can be significantly increased by overlaying mmWave small cells on microwave (μWave) macrocells, due to the elimination of cross-tier interference. This is without any increase in bandwidth or antenna configuration of legacy dense networks. Dramatic performance gains can further be achieved by employing more antenna arrays and larger bandwidth. In addition, we demonstrate that such networks are density-limited. Increasing the number of small cells per macrocell beyond the optimal cell density threshold leads to performance degradation. Adequate consideration should, therefore, be given to this limit in the design, planning and operation of future cellular networks.

Relaying over power line communication (PLC) channels can considerably enhance the performance and reliability of PLC systems. This paper is dedicated to study and analyze the energy efficiency of multi-hop cooperative relaying PLC systems. Incremental decode-and-forward (IDF) relying is exploited to reduce the transmit power consumption. The PLC channel is assumed to experience log-normal fading with impulsive noise. The performances of single-hop and conventional DF relaying systems are also analyzed in terms of outage probability and energy efficiency for which analytical expressions are derived. Results show that using more relays can improve the outage probability performance; however, this is achieved at the expense of increased power consumption due to the increased static power of the relays, especially when the total source-to-destination distance is relatively small. Results also demonstrate that the IDF PLC system has better energy efficiency performance compared to the other schemes.

The ever increasing demand for data traffic for future wireless systems poses challenging requirements for 5G wireless communications, such as high spectral efficiency, better interference management, and extensive connectivity. These challenges open the possibility to use NOMA schemes in future radio access networks. In these schemes, the users are multiplexed in the power domain in the transmitter and de-multiplexed using successive interference cancellation in the receiver. In this work, we propose a hybrid resource allocation technique that consists of orthogonal and non-orthogonal radio resources and also study the improvements in cell capacity achieved in several proposed cases. To this end, we use millimeter- wave-based single-cell deployment to evaluate the performance of this hybrid scheme.

Generally, the probability density function (PDF) of orthogonal frequency division multiplexing (OFDM) signal amplitudes follow the Rayleigh distribution, thus, it is difficult to correctly predict the existence of impulsive noise (IN) in powerline communication (PLC) systems. Compressing and expanding the amplitudes of some of these OFDM signals, usually referred to as companding, is a peak-to-average power ratio reduction technique that distorts the amplitudes of OFDM signals towards a uniform distribution. We suggest its application in PLC systems, such as IEEE 1901 powerline standard (which uses OFDM) to reduce the impacts of IN. This is because the PLC channel picks up impulsive interference that the conventional OFDM driver cannot combat. We explore, therefore, five widely used companding schemes that convert the OFDM signal amplitude distribution to uniform distribution to avail the mitigation of IN in PLC system receivers by blanking, clipping and their hybrid (clipping-blanking). We also apply nonlinear optimization search to find the optimal mitigation thresholds and results show significant improvement in the output signal-to-noise ratio (SNR) for all companding transforms considered of up to 4 dB SNR gain. It follows that the conventional PDF leads to false IN detection, which diminishes the output SNR when any of the above three nonlinear memoryless mitigation schemes is applied.

In this paper, we investigate the power allocation problem in massive multiple-input-multiple-output cognitive radio networks. We propose an orthogonal pilot sharing scheme at pilot transmission phase, where secondary users are allowed to use pilots for channel estimation only when there are temporarily unused orthogonal pilots. Following this, we formulate the power allocation optimization problem of the secondary network (SN) to maximize the downlink sum rate of the SN subject to the total transmit power and primary users’ signal-interference-plus-noise-ratio constraints. Next, we transform the original (nonconvex) problem into a convex one by using convex approximation techniques and propose an iterative algorithm to obtain the solution. Furthermore, we prove that the proposed algorithm converges to Karush–Kuhn–Tucker points of the original problem. Meanwhile, the impact of the number of the secondary base station (SBS) antennas or the primary BS (PBS) antennas on the downlink rate of the SN and primary network is theoretically studied. Finally, the numerical results present the downlink sum rate of the SN under different parameters through our proposed algorithm.