A joint-channel diagonalization for multiuser MIMO antenna systems

In this paper, we address the problem of improving the performance of multiuser space-division multiplexing (SDM) systems where multiple independent signal streams can be transmitted in the same frequency and time slot. The problem is important in multiuser multiple-input multiple-output systems where communication from one base station to many mobile stations can occur simultaneously. Our objective is to devise a multiuser linear space-time precoder for simultaneous channel diagonalization of the multiuser channels enabling SDM. Our new approach is based on diagonalizing the multiuser channel matrices and we use a variation of successive Jacobi rotations. In addition to the diagonalization, our approach attempts to optimize the resultant channel gains for performance enhancement. Our method is valid for both frequency-flat and frequency-selective fading channels but we assume that the base station knows all the channels and that they are quasi-stationary

UAV-Assisted Wireless Powered Cooperative Mobile Edge Computing:Joint Offloading, CPU Control, and Trajectory Optimization

This article investigates the unmanned-aerial-vehicle (UAV)-enabled wireless powered cooperative mobile edge computing (MEC) system, where a UAV installed with an energy transmitter (ET) and an MEC server provides both energy and computing services to sensor devices (SDs). The active SDs desire to complete their computing tasks with the assistance of the UAV and their neighboring idle SDs that have no computing task. An optimization problem is formulated to minimize the total required energy of UAV by jointly optimizing the CPU frequencies, the offloading amount, the transmit power, and the UAV’s trajectory. To tackle the nonconvex problem, a successive convex approximation (SCA)-based algorithm is designed. Since it may be with relatively high computational complexity, as an alternative, a decomposition and iteration (DAI)-based algorithm is also proposed. The simulation results show that both proposed algorithms converge within several iterations, and the DAI-based algorithm achieve the similar minimal required energy and optimized trajectory with the SCA-based one. Moreover, for a relatively large amount of data, the SCA-based algorithm should be adopted to find an optimal solution, while for a relatively small amount of data, the DAI-based algorithm is a better choice to achieve smaller computing energy consumption. It also shows that the trajectory optimization plays a dominant factor in minimizing the total required energy of the system and optimizing acceleration has a great effect on the required energy of the UAV. Additionally, by jointly optimizing the UAV’s CPU frequencies and the amount of bits offloaded to UAV, the minimal required energy for computing can be greatly reduced compared to other schemes and by leveraging the computing resources of idle SDs, the UAV’s computing energy can also be greatly reduced

Precision medicine in the era of artificial intelligence: implications in chronic disease management.

Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reaction of the immune system to a variety of stimuli, such as pathogens, damaged cells, and harmful substances. Metabolically triggered inflammation, also called metaflammation or low-grade chronic inflammation, is the consequence of a synergic interaction between the host and the exposome-a combination of environmental drivers, including diet, lifestyle, pollutants and other factors throughout the life span of an individual. Various levels of chronic inflammation are associated with several lifestyle-related diseases such as diabetes, obesity, metabolic associated fatty liver disease (MAFLD), cancers, cardiovascular disorders (CVDs), autoimmune diseases, and chronic lung diseases. Chronic diseases are a growing concern worldwide, placing a heavy burden on individuals, families, governments, and health-care systems. New strategies are needed to empower communities worldwide to prevent and treat these diseases. Precision medicine provides a model for the next generation of lifestyle modification. This will capitalize on the dynamic interaction between an individual's biology, lifestyle, behavior, and environment. The aim of precision medicine is to design and improve diagnosis, therapeutics and prognostication through the use of large complex datasets that incorporate individual gene, function, and environmental variations. The implementation of high-performance computing (HPC) and artificial intelligence (AI) can predict risks with greater accuracy based on available multidimensional clinical and biological datasets. AI-powered precision medicine provides clinicians with an opportunity to specifically tailor early interventions to each individual. In this article, we discuss the strengths and limitations of existing and evolving recent, data-driven technologies, such as AI, in preventing, treating and reversing lifestyle-related diseases

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

This article investigates the unmanned aerial vehicle (UAV)-assisted wireless powered Internet-of-Things system, where a UAV takes off from a data center, flies to each of the ground sensor nodes (SNs) in order to transfer energy and collect data from the SNs, and then returns to the data center. For such a system, an optimization problem is formulated to minimize the average Age of Information (AoI) of the data collected from all ground SNs. Since the average AoI depends on the UAV's trajectory, the time required for energy harvesting (EH) and data collection for each SN, these factors need to be optimized jointly. Moreover, instead of the traditional linear EH model, we employ a nonlinear model because the behavior of the EH circuits is nonlinear by nature. To solve this nonconvex problem, we propose to decompose it into two subproblems, i.e., a joint energy transfer and data collection time allocation problem and a UAV's trajectory planning problem. For the first subproblem, we prove that it is convex and give an optimal solution by using Karush-Kuhn-Tucker (KKT) conditions. This solution is used as the input for the second subproblem, and we solve optimally it by designing dynamic programming (DP) and ant colony (AC) heuristic algorithms. The simulation results show that the DP-based algorithm obtains the minimal average AoI of the system, and the AC-based heuristic finds solutions with near-optimal average AoI. The results also reveal that the average AoI increases as the flying altitude of the UAV increases and linearly with the size of the collected data at each ground SN

Coded cooperation for improved distance spectrum and diversity in wireless systems

Cooperative transmission has been gaining enormous attention recently where users share their resources for an overall improved performance. In this work, coded cooperation is of interest where a novel strategy is proposed with remarkable performance under various scenarios. In contrast to conventional works that focus on cooperative diversity, the proposed scheme successfully explores further coding benefits even when cooperative diversity is physically unavailable. Signal space diversity is also exploited for better cooperative diversity achievement. Imperfect inter-user channels are considered as well where the detrimental error propagation issue due to cooperative coding on erroneously detected messages is solved. Impressive mutual benefit is achieved for users with or without detection problems on their partners' messages. © 2007 IEEE

CFO estimation and compensation in SC-IFDMA systems

Single carrier interleaved frequency division multiple access (SC-IFDMA) has been recently receiving much attention for uplink multiuser access in the next generation mobile systems because of its lower peak-to-average transmit power ratio (PAPR). In this paper, we investigate the effect of carrier frequency offset (CFO) on SC-IFDMA and propose a new low-complexity time domain linear CFO compensation (TD-LCC) scheme. The TD-LCC scheme can be combined with successive interference cancellation (SIC) to further improve the system performance. The combined method will be referred to as TD-CC-SIC. We shall study the use of user equipment (UE) ordering algorithms in our TD-CC-SIC scheme and propose both optimal and suboptimal ordering algorithms in the MMSE sense. We also analyze both the output SINR and the BER performance of the proposed TD-LCC and TD-CC-SIC schemes. Simulation results along with theoretical SINR and BER results will show that the proposed TD-LCC and TD-CC-SIC schemes greatly reduce the CFO effect on SC-IFDMA. We also propose a new blind CFO estimation scheme for SC-IFDMA systems when the numbers of subcarrier sets allocated to different UEs are not the same due to their traffic requirements. Compared to the conventional blind CFO estimation schemes, it is shown that by using a virtual UE concept, the proposed scheme does not have the CFO ambiguity problem, and in some cases can improve the throughput efficiency since it does not need to increase the length of cyclic prefix (CP). © 2010 IEEE

A hybrid time-frequency domain equalizer for single carrier broadband MIMO systems

Single carrier frequency domain equalization (SC-FDE) has recently been receiving much attention as an attractive technology for broadband wireless communications for its advantages such as low peak-to-average ratio and reduced sensitivity to carrier frequency offsets, when compared to orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we investigate its combination with multi-input multi-output (MIMO) technology and propose a novel hybrid time-frequency domain equalizer, FDE-NP, which consists of a feedforward frequency domain equalizer and an array of time domain noise predictors (NFs). It is shown that the proposed scheme has lower complexity and achieves better performance and complexity trade-off than the conventional FDE designs. To evaluate the system performance, we will propose an accurate theoretical analysis based on the modified Chernoff bound and show that it is not only applicable to the proposed FDE-NP scheme, but also to general MIMO systems with equalization. By using the developed modified Chernoff bound and along with the simulation results, we will show that the proposed FDE-NP scheme can achieve significant performance improvement over the conventional FDE MIMO schemes. © 2006 IEEE

Design and outage performance analysis of relay-assisted two-way wireless communications

Two-way wireless communication has regained significant attention recently over relay channels and network coding techniques have been adopted to improve the spectral efficiency. In the literature, most works assumed knowledge of the channel state information at the transmitter (CSIT) and focused mainly on the three-step network coding (NetC) and two-step superposition coding (SupC) schemes. This work instead targets systems without CSIT and explores in detail the features and limitations of SupC and NetC under both the two-step and three-step frameworks. Equal-rate bi-directional traffic is considered and a comparative study of the schemes is provided. The maximum goodput and robustness to channel knowledge discrepancies are evaluated. Key results include theoretically derived outage regions and performance, and the analysis of the complementary role of NetC and SupC. Special features of the three-step framework and a simple yet efficient protocol, adaptive relay-assisted and direct transmission (ARDT), which smartly exploits the direct link in the absence of CSIT, will also be presented. Optimal power allocation at the relay is also derived for the three-step SupC scheme by exploiting the channel reciprocity (no CSIT required). A significant advantage of ARDT is demonstrated over the recently developed two-step SupC scheme. Numerical results together with extensive discussions are provided. © 2006 IEEE