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In this paper, we investigate the feasibility of applying Physical Layer Network Coding (PNC) in Multi-user Massive MIMO systems. In addition, we investigate the performance benefits of the joint Massive MIMO and PNC scheme. PNC has the potential of increasing capacity of a wireless system as the number of timeslots required for end-to-end communication reduces. We adopted a scheme that transforms the channel between a massive-antenna relay and a multitude of multi-antenna user terminals, with a Sum-Difference (SD) matrix. Through Log-Likelihood Ratio (LLR), PNC is achieved by deriving the network coded symbols from the estimates of the SD symbols at the massive-antenna relay node. The equalization matrix for the estimation is based on the SD transformed channel coefficient matrix. The error performance of the proposed joint Massive MIMO and PNC is evaluated through extensive simulation results. It is shown that joint Massive MIMO and PNC performs significantly better than Massive MIMO without PNC for QPSK modulation.

With the introduction of diverse technology paradigms in next-generation cellular and vehicular networks, design and structural complexity are skyrocketing. The beyond-5G use cases such as mobile broadband, 5G-V2X and UAV communications require support for ultra-low latency and high throughput and reliability with limited operational complexity and cost. These use cases are being explored in 3GPP Release 16 and 17. To facilitate end-to-end performance evaluation for these applications, we propose SDN-Sim-an integration of a System Level Simulator (SLS) with a Software Defined Network (SDN) infrastructure. While the SLS models the communication channel and evaluates system performance on the physical and data link layers, the SDN performs network and application tasks such as routing, load balancing, etc. The proposed architecture replicates the SLS-defined topology into an SDN emulator for offloading control operations. It uses link and node information calculated by the SLS to compute routes in SDN and feeds the results back to the SLS. Along with the architecture, data modeling and processing, replication and route calculation frameworks are proposed.

The millimeter wave (mmWave) based full-dimensional (FD) MIMO communication is one of the promising technology to fulfill the demand of high data rate for the sixth generation (6G) services including 6D hologram, haptic and multi-sensory communications. In order to satisfy the requirements of 6G applications, we investigate a non-uniform rectangular array (NURA) structure with FD-MIMO antenna systems for the multiuser mmWave communications. For the dense scenarios where the number of users to be served is high, we propose user selection algorithms for both digital and hybrid transceiver designs in FD-MIMO with NURA for the multiuser mmWave communications. For the digital transceivers, the users are selected based on their channel correlation considering FD-MIMO with NURA structures. For the hybrid transceivers, sequential user and beam selection is performed using the correlation between the beamspace channels in FD-MIMO with NURA case. The superiority of the NURA compared to uniform antenna structure is shown through the performance evaluations in the multiuser mmWave communications. Besides, the sum data rate results and complexity analysis denote the feasibility of the proposed algorithms compared to the joint user and beam selection schemes.

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Mobile edge computing (MEC) has been envisioned as a promising technology for enhancing the computational capacities of mobile devices by enabling task offloading. In this paper, we present a novel framework for a cooperative MEC system by employing Massive Multiple-Input Multiple-Output (MIMO) and non-orthogonal multiple access (NOMA) technologies, including security aspects. Specifically, in the proposed cooperative MEC system, there is no strong direct transmission link between the cell-edge user and the MEC server; consequently, the user sends their tasks to the MEC server through the helpers at the cell-centers. In the proposed framework, we minimize the overall delay, including secure offloading under the constraints of computing capability and transmit power. The proposed algorithm minimizes the overall delay in downlink and uplink transmission while satisfying security constraints to solve the formulated problem. The simulation results show that Massive MIMO based NOMA improves the performance of the secure MEC system by employing more than one helper.INDEX TERMS Secure offloading, delay minimization, massive multiple input multiple output (MIMO), mobile edge computing (MEC), non-orthogonal multiple access (NOMA)

In this paper, we explore the resilience of Physical Layer Network Coding (PNC) to jamming attacks, focusing on the bit error rate (BER) performance metric. The broadcast nature of the wireless medium has undoubtedly propelled some significant innovations, allowing ubiquitous access to broadband services. In spite of this, it has also created an enormous challenge in mitigating unfriendly interference, where jamming is categorized. A MIMO-PNC based algorithm shows significant improvement in error performance in the lower signal-to-noise ratio (SNR), where the base station (BS) applies linear detection, based on a linear transformed channel matrix, to received symbols, in order to estimate the network coded symbols. We investigate this algorithm in a centralized system of multi-antenna BS with multi-antenna legitimate users, against a barraging attack from a jammer, where the jamming channel is not known to the BS, and the jammer can use any number of transmit antennas. Over Rayleigh fading channels, our simulation results reveal that MIMO-based PNC perform better in lower SNR to jamming attack, as opposed to the non-jammed MIMO system, at twice the spectral efficiency.

In this paper, we develop a practical approach for deploying Physical Layer Network Coding (PNC) in multi-user M-Ary Quadrature Amplitude Modulation (M-QAM) Massive Multiple-Input Multiple-Output (MIMO) systems. We formulate a PNC mapping scheme as a function of clusters of estimated summation and difference (SD) of the transmitted symbols from user pairs. Utilizing existing linear detection schemes, such as Zero Forcing (ZF) and Minimum Mean Square Error (MMSE), a cluster of SD symbols are detected using an SD linearly transformed channel matrix. Furthermore, utilizing Maximum a Posteriori (MAP) soft decoding, the SD symbols are mapped to the PNC symbols, leveraging on the PNC symbol that maximizes the likelihood function. For each variant of M-QAM, we derive and simplify a specialization of the generalized PNC mapping function. The error performance results, through simulation, reveal that the proposed PNC scheme achieves twice the spectral efficiency in Massive MIMO, without changing the latter's underlying framework and without any degradation in the biterror-rate (BER). In fact, our investigation has proved that the BER of the proposed Massive MIMO and PNC is slightly better than that of the conventional Massive MIMO. The feasibility of deploying our proposed PNC scheme in Massive MIMO systems paves way for NC applications to be realized in cellular systems.