Outage probability analysis for the multi-carrier NOMA downlink relying on statistical CSI

In this treatise, we derive tractable closed-form expressions for the outage probability of the single cell multi-carrier non-orthogonal multiple access (MC-NOMA) downlink, where the transmitter side only has statistical CSI knowledge. In particular, we analyze the outage probability with respect to the total data rates (summed over all subcarriers), given a minimum target rate for the individual users. The calculation of outage probability for the distant user is challenging, since the total rate expression is given by the sum of logarithmic functions of the ratio between two shifted exponential random variables, which are dependent. In order to derive the closed-form outage probability expressions both for two subcarriers and for a general case of multiple subcarriers, efficient approximations are proposed. The probability density function (PDF) of the product of shifted exponential distributions can be determined for the near user by the Mellin transform and the generalized upper incomplete Fox’s H function. Based on this PDF, the corresponding outage probability is presented. Finally, the accuracy of our outage analysis is verified by simulation results

On the performance of multiuser MIMO systems relying on full-duplex CSI acquisition

IEEE In this paper, we propose a combined full duplex (FD) and half duplex (HD) based transmission and channel acquisition model for open-loop multiuser multiple-input multipleoutput (MIMO) systems. Assuming residual self interference (SI) at the BS, the idea is to utilize the FD mode during the uplink (UL) training phase in order to achieve simultaneous downlink (DL) data transmission and UL CSI acquisition. More specifically, the BS begins serving a user when its CSI becomes available, while at the same time, it also receives UL pilots from the next scheduled user. We investigate both zero-forcing (ZF) and maximum ratio transmission (MRT) MIMO beamforming techniques for the DL data transmission in the FD mode. The BS switches to the HD mode once it receives the CSI of all users and it employs ZF beamforming for the DL data transmission until the end of the transmission frame. Furthermore, we derive closedform approximations for the lower bounded ergodic achievable rate relying on the proposed model. Our numerical results show that the proposed FD-HD transmission and channel acquisition approach outperforms its conventional HD counterpart and achieves higher data rates

Energy efficiency and delay optimization for edge caching aided video streaming

In this paper, we design a computing, communication and caching scheme for edge caching-based video streaming in order to improve the network performance. Firstly, we optimize the system's energy efficiency and delay with the aid of network function virtualization. Then, a dynamic edge caching decision is developed, and based on Lyapunov optimization, an alternating resource optimization algorithm is proposed for allocating the optimal subcarrier and power resources, video caching and computing resources. Our numerical results show that the proposed scheme outperforms both the traditional caching scheme as well as the least frequently used (LFU)-40% regime, and strikes a compelling tradeoff between the energy efficiency and delay

Physical layer security: Detection of active eavesdropping attacks by support vector machines

This paper presents a framework for converting wireless signals into structured datasets, which can be fed into machine learning algorithms for the detection of active eavesdropping attacks at the physical layer. More specifically, a wireless communication system, which consists of an access point (AP), K legitimate users and an active eavesdropper, is considered. To detect the eavesdropper who breaks into the system during the authentication phase, we first build structured datasets based on different features and then apply sophisticated support vector machine (SVM) classifiers to those structured datasets. To be more specific, we first process the signals received by the AP and then define a pair of statistical features based on the post-processing of the signals. By arranging for the AP to simulate the entire process of transmission and the process of constructing features, we form the so-called artificial training data (ATD). By training SVM classifiers on the ATD, we classify the received signals associated with eavesdropping attacks and nonattacks, thereby detecting the presence of the eavesdropper. Two SVM classifiers are considered, including a classic twin-class SVM (TC-SVM) and a single-class SVM (SC-SVM). While the TC-SVM is preferred in the case of having perfect channel state information (CSI) of all channels, the SC-SVM is preferred in the realistic scenario when we have only the CSI of legitimate users. We also evaluate the accuracy of the trained models depending on the choice of kernel functions, the choice of features and on the eavesdropper’s power. Our numerical results show that careful parameter-tuning is required for exceeding an eavesdropper detection probability of 95%

Open-source multi-access edge computing for 6G: opportunities and challenges

Multi-access edge computing (MEC) is capable of meeting the challenging requirements of next-generation networks, e.g., 6G, as a benefit of providing computing and caching capabilities in the close proximity of the users. However, the traditional MEC architecture relies on specialized hardware and its bespoke software functions are closely integrated with the hardware, hence it is too rigid for supporting the rapidly evolving scenarios in the face of the demanding requirements of 6G. As a remedy, we conceive the compelling concept of open-source-defined cellular networking and intrinsically amalgamate it with MEC, which is defined by open-source software running on general-purpose hardware platforms. Specifically, an open-source-defined MEC (OpenMEC) scheme is presented relying on a pair of core principles: the decoupling of the MEC functions and resources from each other with the aid of network function virtualization (NFV); as well as the reconfiguration of the disaggregated MEC functions and resources into customized edge instances. This philosophy allows operators to adaptively customize their users’ networks. Then, we develop improved networking functions for OpenMEC decoupling and discuss both its key components as well as the process of OpenMEC reconfiguration. The typical use cases of the proposed OpenMEC scheme are characterized with the aid of a small-scale test network. Finally, we discuss some of the potential open-source-related technical challenges when facing 6G

Open-source multi-access edge computing for 6G: opportunities and challenges

Multi-access edge computing (MEC) is capable of meeting the challenging requirements of next-generation networks, e.g., 6G, as a benefit of providing computing and caching capabilities in the close proximity of the users. However, the traditional MEC architecture relies on specialized hardware and its bespoke software functions are closely integrated with the hardware, hence it is too rigid for supporting the rapidly evolving scenarios in the face of the demanding requirements of 6G. As a remedy, we conceive the compelling concept of open-source-defined cellular networking and intrinsically amalgamate it with MEC, which is defined by open-source software running on general-purpose hardware platforms. Specifically, an open-source-defined MEC (OpenMEC) scheme is presented relying on a pair of core principles: the decoupling of the MEC functions and resources from each other with the aid of network function virtualization (NFV); as well as the reconfiguration of the disaggregated MEC functions and resources into customized edge instances. This philosophy allows operators to adaptively customize their users’ networks. Then, we develop improved networking functions for OpenMEC decoupling and discuss both its key components as well as the process of OpenMEC reconfiguration. The typical use cases of the proposed OpenMEC scheme are characterized with the aid of a small-scale test network. Finally, we discuss some of the potential open-source-related technical challenges when facing 6G