Precoding Method Interference Management for Quasi-EVD Channel

The Cholesky decomposition-block diagonalization (CD-BD) interference alignment (IA) for a multiuser multiple input multiple output (MU-MIMO) relay system is proposed, which designs precoders for the multiple access channel (MAC) by employing the singular value decomposition (SVD) as well as the mean square error (MSE) detector for the broadcast Hermitian channel (BHC) taken advantage of in our design. Also, in our proposed CD-BD IA algorithm, the relaying function is made use to restructure the quasieigenvalue decomposition (quasi-EVD) equivalent channel. This approach used for the design of BD precoding matrix can significantly reduce the computational complexity and proposed algorithm can address several optimization criteria, which is achieved by designing the precoding matrices in two steps. In the first step, we use Cholesky decomposition to maximize the sum-of-rate (SR) with the minimum mean square error (MMSE) detection. In the next step, we optimize the system BER performance with the overlap of the row spaces spanned by the effective channel matrices of different users. By iterating the closed form of the solution, we are able not only to maximize the achievable sum-of-rate (ASR), but also to minimize the BER performance at a high signal-to-noise ratio (SNR) region

Integer Forcing-and-Forward Transceiver Design for MIMO Multi-Pair Two-Way Relaying

In this paper, we propose a new transmission scheme, named as Integer Forcing-and-Forward (IFF), for communications among multi-pair multiple-antenna users in which each pair exchanges their messages with the help of a single multi antennas relay in the multiple-access and broadcast phases. The proposed scheme utilizes Integer Forcing Linear Receiver (IFLR) at relay, which uses equations, i.e., linear integer-combinations of messages, to harness the intra-pair interference. Accordingly, we propose the design of mean squared error (MSE) based transceiver, including precoder and projection matrices for the relay and users, assuming that the perfect channel state information (CSI) is available. In this regards, in the multiple-access phase, we introduce two new MSE criteria for the related precoding and filter designs, i.e., the sum of the equations MSE (Sum-Equation MSE) and the maximum of the equations MSE (Max-Equation MSE), to exploit the equations in the relay. In addition, the convergence of the proposed criteria is proven as well. Moreover, in the broadcast phase, we use the two traditional MSE criteria, i.e. the sum of the users' mean squred errors (Sum MSE) and the maximum of the users' mean squared errors (Max MSE), to design the related precoding and filters for recovering relay's equations by the users. Then, we consider a more practical scenario with imperfect CSI. For this case, IFLR receiver is modified, and another transceiver design is proposed, which take into account the effect of channels estimation error. We evaluate the performance of our proposed strategy and compare the results with the conventional amplify-and-forward (AF) and denoise-and-forward (DF) strategies for the same scenario. The results indicate the substantial superiority of the proposed strategy in terms of the outage probability and the sum rate.Comment: 30 pages, 7 figures, Submitted to a IEEE journa

On the Design of Cognitive-Radio-Inspired Asymmetric Network Coding Transmissions in MIMO Systems

In this paper, a cognitive-radio-inspired asymmetric network coding (CR-AsNC) scheme is proposed for multiple-input-multiple-output (MIMO) cellular transmissions, where information exchange among users and base-station (BS) broadcasting can be accomplished simultaneously. The key idea is to apply the concept of cognitive radio (CR) in network coding transmissions, where the BS tries sending new information while helping users' transmissions as a relay. In particular, we design an asymmetric network coding method for information exchange between the BS and the users, although many existing works consider the design of network coding in symmetric scenarios. To approach the optimal performance, an iterative precoding design for CR-AsNC is first developed. Then, a channel-diagonalization-based precoding design with low complexity is proposed, to which power allocation can be optimized with a closed-form solution. The simulation results show that the proposed CR-AsNC scheme with precoding optimization can significantly improve system transmission performance

Denoise-and-forward network coding for two-way relay MIMO systems

In this paper, we propose a denoise-and-forward network coding (DNF-NC) transmission scheme for its applications in two-way relay multiple-input and multiple-output (MIMO) systems. We first consider a scenario with a single pair of source nodes, and minimum mean square error (MMSE) receiver is applied at each node. The global optimal precoding design based on the mean square error (MSE) criterion can be achieved by solving two independent convex optimization problems. To achieve a better tradeoff between performance and complexity, an alternative power optimization approach is proposed using a channel diagonalization technique. Then, we proceed to considering a more challenging bidirectional communication scenario with multiple pairs of source nodes. With intrapair coordination at the sources, we modify DNF-NC by employing a signal alignment technique to combat interpair interference. The numerical results demonstrate that the proposed DNF-NC schemes can significantly improve bit error rate (BER) performance in both two scenarios, and such performance gains can be achieved with relatively low computational complexity

Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Towards 6G

The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. Finally, future research directions toward beyond 5G IoT networks are pointed out.Comment: Submitted for review to IEEE CS&