Internet of Things (IoT) technologies have so deeply penetrated our daily lives that IoT devices have been everywhere. Not only do IoT devices provide basic means to convenient living but they also offer intelligent services tailored to diverse user needs. For instance, beyond remotely turning ON and OFF small gadgets, such as lamps and switches, users can now control appliances via smartphones and also interact with them verbally. In the backdrop of multifarious, complex IoT applications, their reliability becomes of paramount importance. This article focuses on achieving user-level reliability in an IoT operating system (OS) that executes both real-time (RT) and non-real-time (NRT) tasks concurrently. For example, smart appliances typically run RT tasks such as a motor controller, as well as NRT tasks such as Wi-Fi-based network functions, concurrently. In general, RT tasks are critical and should be protected from error-prone tasks. Otherwise, a motor controller failure may cause appliances to malfunction. To this end, we propose a novel, reliable IoT OS, called TizenRT that achieves user-level reliability through two key features, namely, fault isolation and fast recovery, while maintaining RT constraints. Our evaluation shows that TizenRT can isolate faulty tasks in memory space, while guaranteeing normal RT tasks to complete their missions within a required time, e.g., 50 $\mu \text{s}$ . Moreover, corrupted tasks can be recovered within a few milliseconds, e.g., 10 ms, without the need for a system reboot. This makes TizenRT a preferred choice for mission-critical IoT applications.

One of major issues in the efficient use of radio resource for multiuser multiple-input/multiple-output (MU-MIMO) systems is the selection of users to achieve the maximum system throughput. The optimal user selection algorithm, which requires exhaustive search, is prohibitive due to its high computational complexity where Block diagonalization (BD) method is applied and known as a suboptimal precoding technique for downlink MU-MIMO systems, which intents to perfectly eliminate inter-user interference. In this paper, we propose efficient, iterative user selection algorithms with low complexity, where the product of eigenvalues of effective channels is utilized as a selection metric by applying the concept of principal angles between subspaces. And, we further examined the applicability of the proposed algorithms to limited feedback systems and proportional fair (PF) scheduling. Through computational complexity analysis, we show that the proposed algorithm has low complexity with a little loss in throughput. Simulation results validate that the proposed algorithm achieves almost the same system throughput by a capacity-based algorithm under high SNR regime with considerable reduction in complexity.

In this paper, we suggest a multiple-input/single-output (MISO) transmission technique for free-space optical links with intensity modulation and direct detection. Specifically, time-domain repetition coding is investigated over slow and weak turbulence fading channels, where we suggest a set of efficient codewords for MISO transmission with time-domain repetition coding. The proposed approach increases signal to noise ratio (SNR) most effectively by allocating total radiated power fully into only one transmit aperture for a single bit period with postprocessing followed by equal gain combining at a receiver. We evaluate instantaneous electrical SNR and conditional bit error rate (BER) numerically. Numerical results show that as the number of transmit apertures increases the BER performance gap increases, which reveals its outperformance over other schemes not only in weak turbulence channels but also in weak turbulence channel with misalignment problem.

In heterogeneous networks (HetNet), interference coordination techniques among cells have been widely investigated to reduce co-channel interference (CCI), which causes severe system performance degradation when a same channel is shared at both femtocells and macrocell. In this paper, we examine a coordinated beamforming technique to reduce downlink (from macrocell to femtocells) CCI and processing complexity. Using uplink sounding reference signal (SRS), we propose an efficient beamforming searching function for a macro-BS reducing feedback burden compared to conventional schemes. Simulation results are provided for performance comparison in terms of the spectrum efficiency of femtocells and system throughput.

In downlink multi-user multiple-input/multiple- output (MU-MIMO) systems with BD where there are a lot of users, selecting a user set supported by a base station (BS) is very critical to maximize the total throughput. The optimal user selection algorithm, which requires exhaustive search, is computationally prohibitive in real systems. In this paper, we propose a user selection algorithm with low complexity, where the product of eigenvalues of effective channels is utilized as a selection metric. We adopt the concept of principal angles between subspaces to obtain the product of eigenvalues of effective channel matrix at each iteration. Contrary to conventional low complex user selection algorithms, the proposed algorithm is straightforward to apply to PF scheduling because the proposed selection metric indicates data rate in high SNR regime. Computational complexity analysis and simulation results show that the proposed algorithm achieves almost the same the system throughput of capacity-based algorithm in high SNR regime with considerable reduction in complexity.

In uplink 3GPP LTE, SC-FDMA has been regarded as an attractive alternative to OFDMA due to lower Peak-to-Average Power Ratio (PAPR) characteristic. However, in order to get the benefit of PAPR, it requires a contiguous assignment of resource blocks to a single user. In this paper, we suggest heuristic algorithm for proportional fair (PF) scheduling which is known to be NP-hard problem. Under the contiguity constraint, conventional heuristic algorithms assign resource block to a user who has the highest metric and keep on doing assignment according to greedy selection but without any examination of prior selected choice. Our work differs from the conventional works in considering user selection based on PF metric difference and comparison of marginal scheduling metric for examination of selected choice. In simulation results, we demonstrated that the proposed scheme shows better fairness in terms of CDF of normalized throughput and Jain's fairness index.

In uplink 3GPP Long-Term Evolution (LTE), single-carrier frequency division multiple access (SC-FDMA) is considered partly because of the fact that Peak-to-Average Power Ratio (PAPR) for Multi-Carrier Orthogonal Frequency Division Multiplexing (MC-OFDM) is still a hindrance. But, an unique characteristic of SC-FDMA is that subcarriers have to be assigned by contiguous manner for a specific user, which induces a complicated scheduling algorithm to SC-FDMA because a user is not able to exploit frequency selectivity gain fully. To increase system throughput, we propose a new frequency scheduling method using each user's channel gain difference and a contiguity assigning method. Focused on maximizing the total system capacity of SC-FDMA uplink, we compare our algorithms with others in uplink 3GPP LTE. Simulation results show that our proposed scheme outperforms over the existing schemes.

In mobile WiMAX based on the IEEE 802.16e wireless MAN technologies using an OFDMA, the system throughput is improved by subchannelization schemes such as Diversity and AMC in multipath fading channel environment. Especially, in high mobility environment, mobile WiMAX systems uses FUSC which is one of the diversity subchannelization schemes, and get frequency diversity under multipath fading channel. However, the FUSC scheme is not flexible for channel variations inherent to user's speed. In this paper, we propose dynamic subchannelization scheme under multipath fading channels which is varied with a user's speed. Simulation results show that the proposed subchannelization algorithm leads to better the system throughput as compared to conventional subchannelization scheme such as FUSC in various channel environments.