In uncrewed aerial vehicle (UAV)-aided Internet of Things (IoT) networks, providing seamless and reliable wireless connectivity to ground devices (GDs) is difficult owing to the short battery lifetimes of UAVs. Hence, we consider a deep reinforcement learning (DRL)-based UAV base station (UAV-BS) control method to maximize the network-wide energy efficiency of UAV-aided IoT networks featuring continuously moving GDs. First, we introduce two centralized DRL approaches; round-robin deep Q-learning (RR-DQL) and selective-k deep Q-learning (SK-DQL), where all UAV-BSs are controlled by a ground control station that collects the status information of UAV-BSs and determines their actions. However, significant signaling overhead and undesired processing latency can occur in these centralized approaches. Hence, we herein propose a quasi-distributed DQL-based UAV-BS control (QD-DQL) method that determines the actions of each agent based on its local information. By performing intensive simulations, we verify the algorithmic robustness and performance excellence of the proposed QD-DQL method based on comparison with several benchmark methods (i.e., RR-DQL, SK-DQL, multiagent Q-learning, and exhaustive search method) while considering the mobility of GDs and the increase in the number of UAV-BSs.

This paper proposes a new scheme that allows the measurement of traffic loads of radio networks by decoding some information about the cell, such as downlink control information (DCI) broadcast on the physical downlink control channel (PDCCH). In the proposed scheme, a client decodes the entire DCI for all user equipments (UEs) with ongoing connections in a cell and extracts some information about the cell, such as the number of active UEs, the number of radio resources occupied, as well as the modulation and coding scheme used by each UE. Based on this information, mobile network carriers can measure exact traffic loads of cells preemptively without affecting ongoing connections. Contrary to an exhaustive searching scheme that attempts to decode DCI with all radio network temporary identifiers (RNTIs), the proposed scheme derives a small set of valid RNTIs by using an inverse function and attempts to decode DCI only with the valid RNTIs instead of the entire set of RNTIs. This reduction enables the client to recover the correct DCI with marginal computational complexity, which allows for real-time decoding of DCI. The simulation results show that the proposed scheme can significantly reduce the complexity required to decode the entire DCI in a cell, compared to the exhaustive searching scheme.

Cellular networks are becoming dense due to deployment of small cells and a number of user devices. Such networks are called ultra-dense networks (UDNs). In this paper, we propose a novel distributed scheduling with interference-aware power control for an uplink of the UDN operating with time-division duplex (TDD). In the proposed technique, each user adjusts transmit power according to a pre-determined threshold of generating interference to other cell base stations (BSs) and each BS selects the users having the highest effective channel gains adjusted according to the transmit power of users. We assume that each user has a single transmit antenna and each BSs have M receive antennas. It is shown that the proposed technique with a carefully chosen threshold significantly outperforms the existing distributed user scheduling schemes through extensive simulations. In addition, we prove that the optimal multiuser diversity gain, i.e., log log N is achieved by the proposed technique in each cell even in the presence of intercell interference when S = 1, if the number of users in a cell, K-1 N, scales faster than SNRK-1/1-ϵfor a constant ϵ ∈ (0, 1), where S denotes the number of scheduled users.

We investigate the cooperative diversity gain in underlay cognitive radio (CR) systems where secondary users access the spectrum licensed to primary users under an interference power constraint at primary receivers. Our analysis shows that the cooperative diversity gain has different characteristics from that in non-CR systems since the transmit power of a secondary transmitter is limited by the interference power constraint. If a fixed interference power constraint is imposed, the cooperative diversity gain is lost regardless of the number of relays even if peak transmit power grows to infinity. We analyze the critical value of peak transmit power beyond which increasing peak transmit power does not help in improving the outage probability. However, if a proportional interference power constraint is imposed, a full diversity gain is shown to be attained even without instantaneous interference channel information at the secondary transmitters.

In cognitive radio (CR) systems, the Gaussian approximation (GA) has been widely used in determining the optimal threshold for spectrum sensing owing to its analytical simplicity because the GA has been known to be accurate when the number of samples is large. However, this paper shows that if the received signals are weak, the determined sensing threshold by the GA causes significant performance degradation of CR systems even when the number of received samples is large. We analytically quantify the degradation in terms of throughput efficiency and show that the threshold for spectrum sensing should be determined by an exact distribution which is derived in this paper if the received signals are weak.

Most analytical studies on hybrid automatic repeat request (HARQ) have been carried out in either slow fading or fast fading assumptions. However, since practical wireless channels typically exhibit a time-correlated property, we need to take into account the effects of time correlation in the design of HARQ. In this paper, we analyze the outage probability and delay-limited throughput of HARQ with rate adaptation in a time-correlated channel model. Then, we propose a rate adaptation scheme to maximize the delay-limited throughput and evaluate the performance of the proposed scheme under a delay constraint. Our analytical and numerical results show that the proposed rate adaptation scheme outperforms the conventional rate adaptation schemes. The proposed rate adaptation scheme is further simplified by using a Gaussian approximation on the effective channel power gain. The rate adaptation based on the proposed Gaussian approximation reduces the complexity and achieves a throughput gain comparable to that with the exact channel distributions.

We propose a decode-and-forward (DF) based cooperative phase steering scheme and analyze its outage probability. The cooperative phase steering scheme is to make the received signals from multiple relay nodes co-phased at a destination node by pre-adjusting the phase differences.With a reasonable amount of feedback information from a destination node, the cooperative phase steering scheme circumvents the drawbacks of conventional cooperative diversity techniques such as maximal ratio combining (MRC) reception, maximal ratio transmission (MRT), and opportunistic relay selection schemes. Our analytical and simulation results show that the cooperative phase steering scheme outperforms the opportunistic relay selection scheme and approaches the MRT scheme known as a theoretically optimal cooperative diversity technique. It is also shown that cooperative phase steering has sufficient robustness to phase incoherence.

We investigate the effects of multi-user diversity in a spectrum sharing system where secondary users restrictively utilize a spectrum licensed to primary users only if interference perceived at primary users is regulated below a predetermined level. This interference regulation affects the characteristics of multiuser diversity gains previously known in non-spectrum sharing systems. Our numerical and analytical results show that the multiuser diversity gain in a spectrum sharing system increases differently according to conditions given by the transmit power of secondary users, P, and a predetermined interference temperature, Q - if P is sufficiently larger than Q, the multiuser diversity gain in terms of capacity scales like log2(W (Ns)) similarly to a previously known scaling law in the non-spectrum sharing systems, where W(middot) and Nsdenote a Lambert W function and the number of secondary transmitters, respectively. However, the scaling law of multiuser diversity gain becomes log2(Ns) as P becomes sufficiently larger such that P Gt QNs.

This paper investigates the capacity and energy efficiency of spectrum sharing systems with opportunistic user selection where a secondary network utilizes spectrum bands licensed to a primary network under interference regulation. In spectrum sharing systems, secondary users consume a fraction of their resources in sensing the channels to the primary users to comply with the interference constraints. Although more resources for sensing improve reliability and performance, the throughput loss due to time overhead and energy loss due to power overhead should be properly incorporated in performance evaluation. In this context, we define and derive a new metric-average capacity normalized by the total energy consumption-reflecting time and power overhead for spectrum sensing. Based on the developed framework, the optimal normalizedcapacity is investigated. We also propose a simple and practical suboptimal best-n scheme motivated by the infeasibility and high computational complexity of the optimal strategy, where n denotes the number of sensing secondary users. Our analytical and simulation results show that the proposed best-1 scheme is an energy-efficient technique with near optimality in terms of the capacity normalized by the energy consumption.

We analyze the capacity of an opportunistic scheduling system in a spectrum sharing environment where multiple secondary users can share a frequency spectrum with multiple primary users as long as secondary users do not cause interference power exceeding a given threshold to the primary users. We consider three different power control schemes of secondary users: fixed transmit power, adaptive transmit power, and infinite transmit power schemes. Our numerical and simulation results show that the capacity of the adaptive transmit power scheme is similar to that of the fixed transmit power scheme in the low transmit power region, while the capacity of the adaptive transmit power scheme is close to that of the infinite transmit power scheme in the high transmit power region and is saturated beyond a certain point.

We propose two relay selection in cooperative relay communications. In a fixed scheme, M multiple relays that have strong signal strength are selected out of K relays and forward their received data from a source node to a destination node. As an alternative approach, a threshold-based adaptive relay selection scheme is also proposed to minimize the number of forwarding relays while satisfying a given outage requirement because if the number of forwarding relays increases, then the number of interfering sources also increases. The minimum number of relays that can prevent an outage event are selected to forward data to a destination. The performance of both schemes are evaluated through numerical analysis and Monte-Carlo simulations in terms of end-to-end outage probability and the number of forwarding relays. The result presents a bound that the fixed and adaptive relay selection schemes can achieve information-theoretically. Furthermore, the outage performance of the adaptive relay selection scheme is identical to that of the fixed relay selection scheme with M = K, while the number of forwarding relays is much less than that of the fixed relay selection scheme with M = K.

In mobile communication systems, there are areas where signal coverage is not adequately accomplished by base stations. These areas may be underground parking zones, underground stores, tunnels, and insides of buildings, etc. In these areas, repeaters are broadly used as an economical solution. However, the capacity is decreased as the number of repeaters increases because the power of the noise that flows into a base station in the reverse link is proportional to the number of repeaters. The reduction of capacity in the reverse link is no longer negligible in the case that several tens or hundreds repeaters are connected to a base station. We propose automatic on-off switching (AOS) repeater that is switched off automatically when there is no active user within its coverage. With the AOS repeater, we can reduce the unnecessary noise level enhancement when there is no active user within the repeater's coverage. The reverse link capacity of a DS/CDMA system with AOS repeater is analyzed mathematically and compared with that without AOS. From the numerical results, noticeable improvement with the proposed AOS repeaters is shown.