MIMO relay channels with partial channel knowledge/estimation error and spatial correlation

In this paper we show the effect of partial channel knowledge at the receiver which causes estimation error of the channel at the receiver and the spatial correlation on MIMO Relay wireless communication systems. We assume that the transmitter has perfect knowledge of statistical parameters of the channel such as covariance or mean. We show how the topology of the equipment can upgrade or degrade the channel and we generalize a relaying MIMO scenario. We mathematically approach the gain of a system that uses relaying antennas. We assume a Zero Mean Circular Symmetric Complex Gaussian(ZMCSCG) channel elements and ZMCSCG noise elements. As we examine spatial correlation at the transmitter only, we assume that the elements of the rows of the channel matrix of the first hop are correlated. Partial CSI at the receiver causes errors at the estimation of the channel at the receiver which results the channel capacity to degrade and to saturate at certain levels of SNR. Numerical simulations are conducted in order to support the theoretical results used in this pape

Adaptive virtual MIMO single cluster optimization in a small cell

Adaptive Virtual MIMO optimized in a single cluster of small cells is shown in this paper to achieve near Shannon channel capacity when operating with partial or no Channel State Information. Although, access links have enormously increased in the recent years, the operational system complexity remains linear regardless of the number of access nodes in the system proposed. Adaptive Virtual MIMO optimized in a single cluster performs a theoretical information spectral efficiency, almost equal to that of the upper bounds of a typical mesh network, up to 43 bits/s/Hz at a SNR of 30dB while the BER performance remains impressively low hitting the 10−6 at an SNR of about 13 dB when the theoretical upper bound of an ideal small cell mesh network achieves the 10−6 at a SNR of 12.5 dB. In addition, in a sub-optimum channel condition, the channel capacity and BER performance of the proposed solution is shown to drastically delay saturation even for the very high SNR

Dynamic Bit Loading with the OGFDM Waveform Maximizes Bit Rate of Future Mobile Communications

A new Dynamic Bit Loading (DBL) scheme with the Orthogonal Generalized Frequency Division Multiplexing (OGFDM) is, for the first time, proposed, discussed and assessed. The key concept of this hybrid modulation format depends substantially on the adaptive distribution of the bit stream to be more compatible with the gained capacity of the realistic channel state. Due to the negative impact of employing the AQ1 fixed schemes of digital modulation on the performance of the conventional telecommunications systems, the influence of using the multi-level modulation system is investigated for the future applications of mobile communications. Utilising the DBL in the physical layer (PHY), a flexible range of modulation formats can be optimally assigned for each applied frequency sub-carrier in accordance with wireless channel circumstances. In addition, depending on the supportive features of the proposed modulation system, the performance in terms of channel capacity can be maximised at the acceptable limit of the Bit Error Rate (BER). As such, an extra enhancement can be achieved in the spectrum efficiency (SE) of the adaptively modulated wireless signal. Thus, an adjustable boost of the transmission range of used modulation formats can be reached with the introduced adaptation system. The performance of the DBL system through a wireless mobile channel under the Additive White Gaussian Noise (AWGN) is evaluated according to a various level of the Signal to Noise Ratio (SNR). Ultimately, regarding the numerical simulation, a MATLAB code is employed to simulate the performance (channel capacity & BER) of the proposed DBL that is fundamentally accommodated by the recent candidate waveform of future mobile technology (OGFDM)

Convolutional Neural Network based algorithm for Early Warning Proactive System security in Software Defined Networks

Software-Defined Networking is an innovative architecture approach in the networking field. This technology allows networks to be centrally and intelligently managed by unified applications such as traffic classification and security management. Traditional networks’ static nature has a minimal capacity to meet organisations business requirements. Software-Defined Networks (SDNs) are the emerging architectures that address a range of networking challenges with new solutions. Nevertheless, these centralised and programmable techniques face various challenges and issues that require contemporary security solutions such as Intrusion Detection Systems. Recently, the majority of this type of security solution has been developed using Machine Learning techniques. Deep Learning algorithms have recently been used to provide more accuracy and efficiency. This paper presents a new detection approach based on Convolutional Neural Network (CNN). The experiments proved that the proposed model could be successfully implemented in a Software-Defined Network controller to detect various attacks with 100% accuracy, achieved a low degradation rate of 2.3% throughput and 1.8% latency when executed in a large-scale network

Overhead Reduction Technique for Software-Defined Network based Intrusion Detection Systems

In Software-Defined Networks, the Intrusion Detection System is receiving growing attention, due to the expansion of the internet and cloud storage. This system is vital for institutions that use cloud services and have many users. Although the Intrusion Detection System offers several security features, its performance is lagging behind in large enterprise’s networks. Existing approaches are based on centralised processing and use many features to implement a protection system. Therefore, system overload and poor performance occur at the controller and OpenFlow switches. As a result, the current solutions create issues that must be considered, especially when they are implemented on large networks. Furthermore, enhancements in security applications improve the reliability of networks. Following a literature review of the existing Intrusion Detection Systems, this paper presents a new model that offers decentralised processing and exchanges data over a trusted, independent channel, in order to solve issues relating to system overload and poor performance. Our model utilises an appropriate feature selection method to reduce the number of extracted features and minimise the data transmitted over the channels. Additionally, the Naive Bayes algorithm has been employed for flow classification purposes, since it is a fast classifier. We successfully implemented our framework, using the Mininet emulator, which provides a suitable networking environment. Evaluations indicate that our proposed system can detect various attacks with an accuracy of 98.46% and nominal decreasing rates of 1.5% in throughput and 0.7% in latency analyses, when the model is implemented in wide range networks

Heuristic Optimization for Microload Shedding in Generation Constrained Power Systems

While the causes of power system outages are often complex and multi-faceted, an apparent deficit in generation compared to a known demand for electricity could be more alarming. A sudden hike in demand at any given time may ultimately result in the total failure of an electricity network. In this paper, algorithms to efficiently allocate the available generation is investigated. Dynamic programming based algorithms are developed to achieve this constraint by uniquely controlling home appliances to reduce the overall demands for electricity by the consumers on the grid in context. To achieve this, heuristic optimization method (HOM) based on the consumers’ comfort and the benefits to the electricity utility is proposed. This is then validated by simulating microload management in generation constrained power systems. Three techniques; General Shedding (GS), Priority Based Shedding (PBS) and Excess Reuse Shedding (ERS) techniques were studied for effecting efficient microload shedding. The research is aimed at reducing the burden imposed on the consumers in a generation constrained power system by the traditional load shedding approach. Additionally, the reduction of the excess curtailment is a prime objective in this paper as it helps the utility companies to reduce wastage and ultimately reduce losses resulting from over shedding. Reducing the peak-to-average ratios (PAR) on the entire network in context as a critical factor in the determination of the efficiency of an electricity network is also investigated. In the long run, the PAR affects the price charged to the final consumer. Simulation results show the associated benefits that include effectiveness, deployability, and scalability of the proposed HOM to reduce these burdens

Enhancing BER performance limit of BCH and RS codes using multipath diversity

Modern wireless communication systems suffer from phase shifting and, more importantly, from interference caused by multipath propagation. Multipath propagation results in an antenna receiving two or more copies of the signal sequence sent from the same source but that has been delivered via different paths. Multipath components are treated as redundant copies of the original data sequence and are used to improve the performance of forward error correction (FEC) codes without extra redundancy, in order to improve data transmission reliability and increase the bit rate over the wireless communication channel. For a proof of concept Bose, Ray-Chaudhuri, and Hocquenghem (BCH) and Reed-Solomon (RS) codes have been used as FEC to compare their bit error rate (BER) performances. The results showed that the wireless multipath components significantly improve the performance of FEC. Furthermore, FEC codes with low error correction capability and employing the multipath phenomenon are enhanced to perform better than FEC codes which have a bit higher error correction capability and did not utilise the multipath. Consequently, the bit rate is increased, and communication reliability is improved without extra redundancy