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In this paper, we suggest an RFID tag antenna for ultrahigh frequency band for radio frequency identification for drug runout management and a float motion detection that can be used in hospitals and fishing. The RFID tag antenna works as a sensor which warns of drug runout when the drug inside the drip chamber is completely consumed, while it does not work if the drug remains inside the drop chamber. Also, the antenna which attached to the fishing float propagates signals when it is exposed to air, but it does not work when submerged in water. The fabricated antenna has an average omnidirectional reading range of 10.65 m in the horizontal plane.

In this paper, we propose four transmit power control strategies for the underlay device-to-device (D2D) communications, in which the spectral efficiency (SE) of the D2D communications is maximized while the amount of interference caused to a base station (BS) is kept less than a predefined threshold. To this end, we first propose a centralized power control strategy based on instantaneous and global channel state information (CSI) by formulating a convex optimization problem. Then, three distributed power control strategies are taken into account in which each D2D pair adjusts its transmit power in a distributed manner based on interference price and its local CSI, which significantly reduces the signaling overhead. In the distributed strategies, the interference price can be determined based on (1) the instantaneous local CSI; (2) the statistics of the local CSI (average power); and (3) the number of the D2D pairs without any CSI knowledge. Through extensive computer simulations, we show that the performances of the proposed strategies optimally adjust the transmit power of the D2D communications. Especially, we find that the distributed power control strategies can achieve almost the same SE with the centralized strategy with much lower signaling and control overhead.

In this paper, we propose a novel intelligent reflecting surface (IRS) based wireless channel confusion technique for energy efficient jamming. Since IRS consists of passive reflecting elements, its amplitude and phase can be changed rapidly. Due to its rapid alternation of passive elements, IRS makes legitimate receiver to acquire wrong channel state information (CSI) by changing effective channel of legitimate network so that the channel at pilot signal slot and at data signal slots are different. As a result, channel confusion technique can effectively degrade the communication performance of legitimate network even legitimate transmitter uses much higher transmit power. The jamming performance of proposed IRS based channel confusion technique is evaluated by extensive computer simulation. Moreover, it is shown that proposed IRS based channel confusion technique is better jamming technique than Gaussian jamming technique.

A planar antenna is designed to replace complex structures of many rat-race couplers and 90° hybrids used in conventional target detection antennas. The proposed antenna has 2 × 2 microstrip patch antenna arrays with dual feeding to radiate symmetric polarizations in the 9.375 GHz (X-band). The sum pattern with circular polarization is implemented through a sequence feeding at port 1. The simultaneous feeding of port 2 radiates a difference pattern in all polarizations. Thus, a target detection antenna is designed with features that have fewer ports than the conventional monopulse antennas. The proposed antenna is compact, planar, and has a simple comparator circuit and equal sum and difference levels. Also, in the last section, the antenna feeding network which can be receive the dual-CP (RHCP and LHCP) is proposed.

In this paper, we investigate a multi-pair orbital angular momentum (OAM) interference network adopting mode- division multiplexing (MDM) at each transmitter, where multiple transmitter-receiver pairs exploit the same multiple OAM modes. Even though many previous studies on the OAM-MDM exist in literature, they only focused on a single transmitter-receiver pair and did not consider the inter-pair interference. In practice, wireless fronthaul and backhaul links reuse the same frequency band and they may interfere with each other. We first mathematically characterize the Laguerre-Gaussian (LG) beam-based OAM wireless channel and then analyze the channel capacity of the multi-pair OAM interference channel. It is worth noting that this is the first theoretical result in literature. Through extensive computer simulations, we validate the channel capacity of the multi-pair OAM-MDM interference channel by considering the interference among different OAM beams according to various system parameters such as the number of OAM modes, the distance between the transmitter and receiver, the distance between adjacent transmit antennas, the waist of the OAM beams, etc.

In this paper, we propose a novel opportunistic downlink interference alignment with a beam selection (ODIA-BS) technique for fog-radio access networks (F- RANs). With joint transmit and receive beamforming strategies, inter-cell interference is effectively suppressed and intra-cell interference is perfectly eliminated. The performance in terms of sum-rate is improved by selecting a proper transmit beam through F- RAN with low signaling overheads. We also develop a spectrally-efficient ODIA-BS (SE-ODIA-BS) technique to further improve the sum-rate performance, where the scheduler at remote radio head selects users with the most orthogonal effective channel vector to each other. Through extensive computer simulations, it is shown that the sum-rate of the proposed ODIA-BS and SE-OIDA- BS techniques outperform other conventional schemes in the F-RAN environment.

In this paper, we propose a novel uplink non-orthogonal multiple access (NOMA) for massive internet-of-things (IoT) networks where each device exploits a space-time line code (STLC) to send a small data packet to fusion center (FC) and the FC decodes the received packet without channel state information (CSI). In particular, we mathematically analyze the bit error ratio (BER) performance of the NOMA-based massive IoT network with the STLC by assuming the optimal joint maximum-likelihood (JML) detector. In addition, we propose a phase-steering based STLC (PS-STLC) technique to further improve the BER performance. Through extensive simulations, it is shown that the proposed PS-STLC technique achieves the optimal diversity and significantly improves the BER performance of the NOMA-based massive IoT network.

In this paper, we investigate the performance of uplink non- orthogonal multiple access (NOMA) systems for internet- of-things (IoT) applications, which exploits a space-time line code (STLC) and a binary phase shift keying (BPSK) modulation at each sensor (transmitter). A single transmit antenna is assumed to be equipped at the sensor and two receive antennas are assumed to be equipped at a fusion center (FC). The STLC enables the FC to decode the transmitted symbols from multiple sensors without channel state information (CSI) of each sensor. In particular, we mathematically analyze the symbol error rate (SER) of the super-imposed symbol received at the FC and obtain the diversity order of the uplink NOMA-IoT network. We also propose a phase steering (PS)-based STLC technique to improve the SER performance, in which certain sensors rotate its constellation. The proposed PS-STLC technique significantly outperforms the conventional STLC scheme in the uplink NOMA-IoT network.

This paper investigates achievable rates of a multi- user mode-division multiplexing (MDM) system using orbital angular momentum (OAM), where multiple transceivers exploit the same OAM modes. In general, multiple independent signals with different OAM modes are mutually orthogonal between perfectly aligned transmitter and receiver antennas, but the OAM signals among multiple users may interfere with each other. Note that we analyze the achievable rate of multi-user MDM system that utilizes the microwave OAM for the first time. Through extensive computer simulations, we analyze the achievable rate of the multi-user OAM-MDM system by considering the multi-user interference. It is worth noting that the communication scenario we consider in this paper has not been investigated in literature so far.

We characterize the interference characteristics of directional unmanned aerial vehicle (UAV) networks based on the stochastic geometry, where each UAV is equipped with a directional antenna and is placed in three dimensional (3D) locations. In particular, the 3D location of UAVs is assumed to be uniformly distributed in a certain volume, which is modeled by Poisson point process. Given a beamwidth, we first design an ideal 3D directional antenna model with a constant gain of both main-lobe and side-lobe. Then, we investigate the aggregate interference at a typical UAV receiver from multiple UAVs. Extensive simulation results show that the aggregate interference becomes significantly decreased if the beamwidth decreases or the antenna gain of side-lobe decreases.

In this paper, we consider an unmanned aerial vehicle (UAV)-assisted downlink cellular network consisting of a single base station (BS), two mobile stations (MSs) with N antennas, and K UAV relay stations (RSs). We assume that there exists no direct link between the BS and the MSs due to unexpected blockages such as obstacles and disasters. We propose a UAV-assisted cooperative downlink non-orthogonal multiple access (NOMA) with virtual full-duplex (VFD) operation for improving spectral efficiency in such an environment. In the proposed VFD technique, a single UAV-RS is selected among multiple UAV-RS. Through computer simulations, we verify that the proposed cooperative NOMA technique with VFD operation significantly outperforms the conventional cooperative NOMA technique with half-duplex operation in terms of outage probability. Keywords: Unmanned aerial vehicle (UAV), UAV-assisted cooperative communications, Outage probability, Non-orthogonal multiple access (NOMA), Relay selection algorithm

In massive cellular internet-of-things (IoT) networks, periodic and sporadic traffic may be well processed, while bursty traffic may cause an unexpected network congestion or overload problem. Thus, in this paper, we propose a generalized random access (RA) control mechanism considering whole steps of RA procedure and available resources at each step for handling bursty traffic in cellular IoT networks. The proposed RA control mechanism mainly consists of the estimation method for the number of backlogged nodes and the computation method for access class barring (ACB) factors. Through extensive computer simulations, the proposed RA control mechanism shows the enhanced performance in terms of the total service time, the average access delay, and the energy efficiency, compared to the conventional RA control mechanism, which only focuses on controlling preamble transmissions at the first step of the RA procedure.

Simultaneous wireless information and power transfer (SWIPT) has been considered one of the emerging techniques to overcome power limitation of wireless devices using batteries as well as to send information at the same time. Although the SWIPT techniques have been intensively investigated, the fairness among wireless-powered devices in the SWIPT-enabled multicell networks has not been studied yet. In this paper, we propose an adaptive proportional fairness ( $\alpha$ -PF) scheduling algorithm in SWIPT-enabled multi-cell downlink networks. We define an adjustable weighted sum of achievable rate and harvested energy as the utility function of each user and investigate fairness among utilities of users. Through extensive simulations, we evaluate the proposed scheduling algorithm in terms of rate-energy (RE) tradeoff, the fairness of achievable rate and harvested energy. Compared to various existing scheduling algorithms such as random scheduling, maximum signal-to-interference-plus-noise (SINR) scheduling, and $\alpha$ -adaptive scheduling algorithms, the proposed scheduling algorithm achieves better fairness measure (e.g., Jain's fairness index). In addition, we can adaptively control parameters of the proposed scheduling algorithm to satisfy certain requirements of the system.

This paper proposes a machine learning (ML)-based exponential effective signal-to-noise ratio (SNR) mapping (EESM) method for simulating the system-level performance of cellular networks, which utilizes a deep neural network (DNN) regression algorithm. We first explain overall procedure of the link-to-system (L2S) mapping algorithm which has been used in commercial standardization organizations such as IEEE 802.16 and 3GPP LTE. Then, we apply the proposed ML-based EESM method to the existing L2S mapping procedure. The processing time of the L2S mapping becomes significantly reduced through the proposed method while the mean squared errors (MSE) between the actual block-error rate (BLER) from the link-level simulator and the estimated BLER from the L2S mapping technique is also decreased, compared with the conventional L2S mapping method.

In this paper, we propose a novel pseudo-random beamforming technique with beam selection for improving physical-layer security (PLS) in a downlink cellular network where consists of a base station (BS) with Nt antennas, N MS legitimate mobile stations (MSs), and N E eavesdroppers. In the proposed technique, the BS generates multiple candidates of beamforming matrix each of which consists of orthogonal beamforming vectors in a pseudo-random manner. Each legitimate MS opportunistically feeds back the received signal-to-interference-and-noise ratio (SINR) value for all beamforming vectors to the BS. The BS transmits data to the legitimate MSs with the optimal beamforming matrix among multiple beam forming matrices that maximizes the secrecy sum-rate. Simulation results show that the proposed technique outperforms the conventional random beamforming technique in terms of the achievable secrecy sum-rate.

In this paper, we propose a novel virtual full-duplex cooperative non-orthogonal multiple access (NOMA) technique for a downlink two-hop cellular network which consists of a single base station (BS), two mobile stations (MSs), and K half-duplex decode-and-forward (DF) relay stations (RSs). In the proposed technique, the BS sends super-imposed signals for two MSs via the RSs in each transmission phase, while a selected RS via two-stage relay selection sends the signals to two MSs. Thus, the multiplexing loss due to half-duplex operation of RSs can be overcome by allowing for both the BS and a selected RS to send data at the same time. In the proposed cooperative NOMA, we adaptively reset the successive transmission according to decoding status at RSs. As main results, we mathematically analyze outage probability and diversity-multiplexing tradeoff (DMT) of the proposed technique. Extensive computer simulations show that the proposed technique significantly outperforms the existing schemes in terms of both outage probability and DMT.

In this paper, we propose a novel pseudo-random beamforming (BF) technique in multi-cell downlink networks consisting of multiple base stations (BSs) and one BS coordinator. In the proposed technique, each BS first generates M BF matrices with a pseudo-random manner and each mobile station (MS) opportunistically feeds back the received signal-to-interference-and-noise (SINR) ratio for each random beam to its home-cell BS. Then, each BS selects MSs for each beam based on the feedback information, and it also feeds back the achievable sum-rate for M BF matrices to a BS coordinator via wired backhaul links. Finally, the BS coordinator determines the optimal BF matrix that maximizes the sum-rate over the network, and sends the index of the optimal BF matrix to BSs. Each BS sends data to MSs by using the optimal BF matrix among M BF matrices. Main results indicate that there exists a trade-off between the feedback overhead and the achievable sum-rate, but the sum-rate of the proposed technique with opportunistic feedback approaches to that with full feedback as the number of MSs in each cell increases.

We consider a spatial modulation (SM)-based physical-layer network coding (PNC) technique with convolutional codes (CC) for a two-way relay network (TWRN) consisting of two source nodes and a single relay node. We assume all communicating nodes are equipped with multiple antennas. Two source nodes simultaneously transmit packets by utilizing the SM with CC to the relay node. The relay node detects signal by utilizing a maximum-likelihood detection technique based on a direct decoding or a separate decoding algorithm. Through extensive simulations, it has been shown that the SM-based PNC technique outperforms the conventional PNC technique. Note that the direct decoding has low complexity, while achieving a similar performance to the separate decoding in terms of bit error rate (BER).

In this paper, we propose a novel low-complexity signal detection technique based on compressed sensing for a full-duplex generalized spatial modulation (FD-GSM) system, where a communication node transmits data symbols via some antennas and receives data symbols via the remaining antennas at the same time. Thus, each antenna operates as either transmitter or receiver in each symbol time, which implies FD-GSM can be implemented with half-duplex antennas. In particular, parallel orthogonal matching pursuit (POMP) algorithm is exploited as a sparse signal recovery algorithm for detecting GSM signals. The self-interference (SI) due to full-duplex operation is assumed to be completely removed by help of the recently proposed SI cancellation techniques. The proposed signal detection technique significantly outperforms the conventional OMP algorithm in terms of symbol error rate (SER). Interestingly, there exists an optimal number of active antennas for maximizing effective throughput.

In this paper, we investigate the effect of user scheduling and transmit power control on trade-off between spectral efficiency and energy efficiency in multi-cell uplink networks. We assume that each user adaptively controls the transmit power according to its generating interference to other cell base stations (BSs) and each BS schedules the user having the largest effective channel gain among users in a cell. The users transmit data with the peak power, Pmax, if the generating interference to other cell BSs is smaller than a particular threshold, With the joint interference-aware power control (IAPC) and user scheduling, the trade-off between spectral efficiency and energy efficiency becomes significantly improved as the number of users in each cell increased, compared with the conventional maximum signal-to-noise ratio (maxSNR) user scheduling and minimum interference-to-noise ratio (minINR) user scheduling. In addition, the power consumption becomes significantly reduced with the IAPC and user scheduling for a given spectral efficiency.

In this paper, we propose a novel signal detection technique with parallel orthogonal matching pursuit (POMP) for a multi-user spatial modulation (SM) uplink network which consists of a single base station (BS) with N r antennas and K users with N t antennas. Each user utilizes the SM, and thus it sends a modulated symbol via a single antenna among N t antennas. The BS tries to estimate the symbols simultaneously received from K users. In the proposed signal detection technique, the BS modifies the conventional OMP algorithm, known as one of the most promising detection techniques in sparse signal processing field, by selecting multiple candidates M at the first iteration of the OMP algorithm. Simulation results show that the proposed technique significantly outperforms the OMP algorithm in terms of symbol-error rate. It is worth noting that the proposed technique requires M-times more complexity than the OMP-based technique, but it has still much lower complexity than the maximum likelihood detector.

Wireless local area networks (WLANs) are becoming denser and thus interference-limited due to heavy traffic from a number of adjacent access points (APs) and stations (STAs). We propose a novel interference management technique for overlapping basic service sets (OBSSs) in such WLANs, which intelligently applies an opportunistic interference alignment (OIA) concept to WLANs. Each BSS has an AP and multiple STAs, and operates with a carrier sensing multiple access (CSMA) protocol as commercial IEEE 802.11 WLANs. Both APs and STAs are assumed to have multiple antennas. Specifically, the proposed OIA framework consists of physical (PHY) and medium access control (MAC) layer techniques: transmit beamforming and opportunistic medium access, respectively. First, each STA performs transmit beamforming which minimizes generating interference to other BSSs at the PHY layer. Second, each STA sends packets to its serving AP only when its generating interference to other BSSs is smaller than a pre-determined threshold at the MAC layer. Through extensive simulations, we show that proposed OIA scheme significantly outperforms existing schemes in terms of system throughput. Note that the OIA scheme operates with a distributed manner based on local channel state information at each STA and does not require any coordination among BSSs, leading an easier implementation in practice.

Function computation over wireless sensor networks is investigated, where K sensors measure their observations and a fusion center wishes to estimate a pre-defined function of the observations via fading multiple access channels (MACs). The arithmetic sum and type functions are considered since they yield various fundamental sample statistics such as mean, variance, maximum, minimum, etc. We propose a novel opportunistic in-network computation (INC) scheme in which a subset of sensors with large channel gains opportunistically participate in the transmission at each time slot, while all sensors in a network simultaneously send their observations or only a single sensor sends its observation in the conventional INC schemes. We analyze the ergodic computation rate of the proposed INC scheme and prove that it achieves a non-vanishing computation rate even when the number of sensors K tends to infinity, which provides a significant rate improvement compared to the conventional INC schemes whose computation rates converge to zero as K increases.

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 interferenceaware 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 logN 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, N, scales faster than equation for a constant ϵ ∈ (0,1), where S denotes the number of scheduled users.

A distributed beamforming technique at each user pair (transmitter-receiver) is proposed in a (n, K)-user interference channel where K user pairs are allowed to simultaneously communicate with each other among n user pairs (K ≪ n). Each transmitter sends a single spatial stream and each user pair minimizes generating interference to the scheduled receivers and the received interference from the scheduled transmitters via transmit beamforming and receive beamforming, respectively. We analyze scaling of n to achieve K degrees-of-freedom (DoF) with high probability via the proposed beamforming technique. This results show that the proposed beamforming reduces the required network size (i.e., scaling of n) compared to the previous results on (n, K)-user interference channel.

Due to the difficulty of coordination in cellular uplink networks, it is a practical challenge to achieve better throuhgput with a distributed scheduling. Futhermore, multiple antennas at mobile stations (MSs) can be utilized for reducing interference or for improving the desired signal strength. In this paper, we investigate a joint design of beamforming and user scheduling for multi-cell multiple input multiple output (MIMO) uplink networks. In the proposed scheme, each BS with M antennas adopts M random beamforming techniques and each MS with L antennas utilizes a single beamforming vector which minimizes the sum power of generating interferences to home cell as well as other cells. In each cell, then, the BS selects M MSs such that both sufficiently large desired signal power and sufficiently small generating interference are guaranteed. Numerical results show that the proposed scheme outperforms the existing distributed schemes in terms of sum-rate in practical environments.

In this paper, we propose a cumulative distribution function (CDF)-based scheduling for multi-cell uplink networks in order to exploit multi-user diversity, while satisfying fair resource sharing among users. In the proposed scheduling, each user adjusts its transmit power to reduce the amount of generating interference to other cells, based on a pre-determined threshold. Then, each user calculates CDF of an uplink signal-to-noise ratio with the adjusted transmit power, and feeds the CDF value back to its serving base station (BS). In each time slot, the BS selects the user having the largest CDF value. The proposed scheduling operates with a distributed manner even though it effectively copes with inter-cell interference. As a main result, we prove that the proposed scheduling achieves the double-logarithmic growth of normalized user throughput which is defined as the ratio of user throughput to the probability of the user being selected. Moreover, we observe that a fixed threshold is enough to accommodate diverse network scenarios with different population sizes and user locations in the proposed scheduling.

We introduce a new achievability scheme, termed opportunistic network decoupling (OND), where a novel relay scheduling strategy is utilized in the K × N × K channel with interfering relays, consisting of K source - destination pairs and N half-duplex relays in-between them. A subset of relays using alternate relaying is opportunistically selected in terms of producing the minimum total interference level, thereby resulting in network decoupling. As our main result, it is shown that under a certain relay scaling condition, the OND protocol with alternate half-duplex relaying achieves K degrees-of-freedom even in the presence of interfering links among relays. Numerical evaluation is also shown to validate the performance of the proposed OND scheme.

Opportunistic interference alignment (OIA) has been known to asymptotically achieve the optimal degrees-of-freedom (DoF) in multi-input multi-output (MIMO) interfering multiple-access channels (IMACs) as the number of users scales with signal-to-noise ratio, even though no collaboration between base stations (BSs) is assumed. In some previous studies on OIA, the zero-forcing (ZF) receiver has been used at the BSs since it is sufficient to achieve the optimal DoF. In this paper, we propose a simple minimum distance (MD) receiver in a MIMO IMAC model, enabling us to implement the OIA scheme with no information of other-cell interfering links. Surprisingly, we show that as the number of users increases, the MD receiver not only guarantees the optimal DoF but also asymptotically achieves the optimal capacity obtained along with full information of other-cell interfering links. Simulation results indicates that the MD receiver indeed outperforms the conventional ZF receiver even in practical cellular setups.

We consider a linear multihop relay network adopting Chase-combining type Hybrid ARQ strategy in Rayleigh fading channels. The total number of (re)transmissions is assumed to be not limited, i.e., we consider delay-tolerant applications. We aim at maximizing the average throughput by jointly optimizing the transmit powers and data rates over all hops, while limiting the sum of transmit powers of all nodes. However, it is hard to find the jointly optimal power allocation and rate selection strategy in this problem. In this paper, we propose an iterative algorithm in order to obtain the optimal transmit powers and transmission rates for all the nodes including source and relays. Numerical results show that the proposed algorithm which controls both power and rate yields the best throughput performance among the conventional link adaptation schemes including the schemes that adapt either power or rate.

In this paper, we consider wireless random access networks (RANs) with both single packet reception (SPR) and multi-packet reception (MPR) techniques in fading channels, and compare their performance in terms of sum rate and energy efficiency. We adopt a simple power consumption model including transmission power and idle power. With MPR techniques, the transmission rate selection at each user is very important for achieving higher throughput in the uplink of RANs, but the optimal transmission rate at each user may not be feasible in a distributed manner. Thus, we propose a suboptimal rate selection technique in which each user chooses an appropriate transmission rate and, thus, it operates in a distributed manner for practical RANs. It is shown that the MPR yields higher sum rate than the SPR through extensive computer simulations. As for the energy efficiency, the MPR also significantly outperforms the SPR especially when the transmission power is comparable with the idle power.

In this paper, we consider the joint multiuser detection and channel estimation problem in wireless random access networks which consists of a large number of users with a single antenna and a base station (BS) multiple antennas. We first convert the problem into the compressed sensing framework and then propose a message passing (MP) algorithm which reduces the implementation complexity at BS. Simulation results show that the performance of the proposed MP algorithm becomes improved as the number of antennas at BS.

In this paper, we investigate both link adaptation and user scheduling for an HARQ-based multi-user system in downlink multi-cell environments with inter-cell interference (ICI). First, we analyze two approximation methods on the ICI terms for optimal rate selection. One is a conventional well-known Gaussian approximation (GA) and the other is our proposed identical path-loss approximation (IPLA). Thereafter, we propose a baseline procedure for both the link adaptation and user scheduling. Then, we introduce three conventional policies and our proposed IPLA-based policy. Finally, through system-level simulations, the proposed IPLA-based policy is evaluated in terms of system throughput. Numerical results show that the traditional GA is not accurate any more in the HARQ-based multi-user system with some dominant ICIs. Instead of the GA, our proposed IPLA-based policy achieves more accurate rate selection and higher system performance.

Cumulative distribution function (CDF)-based scheduling is known as an efficient scheduling method that can assign different time fractions for user access or, equivalently, satisfy different channel access ratio requirements of users in cellular downlink while exploiting multi-user diversity. In this paper, we propose CDF-FR, a feedback reduction technique for CDF-based scheduling that reduces feedback overhead from users in a cell. Although several threshold based feedback reduction schemes have been proposed for various scheduling algorithms, none of them considers users' different channel access ratio requirements for which CDF-based scheduling is designed. In the proposed technique, a single threshold is used for all users who have different channel access ratio requirements. We show that this simple setting is sufficient for CDF-FR to satisfy users' diverse channel access ratio requirements. It is proved that the average feedback overhead of CDF-FR is upper-bounded by - lnp for an arbitrary number of users in a cell, where p represents the probability that no user satisfies the threshold condition. Furthermore, the normalized throughput loss due to feedback reduction is upper-bounded by p in fading channels with arbitrary statistics.

In this paper, we study the achievable degree-of-freedom (DoF) of an (n, K)-user interference network where n transmitter-receiver pairs are randomly distributed but only K transmitter-receiver pairs are allowed to communicate (n ≫ K). We propose a distributed user scheduling method to achieve the maximum DoF (i.e., K), which sequentially adds a transmitter-receiver pair causing/receiving interference to/from the previously selected transmitter-receiver pairs below a certain threshold level. It is proven that the maximum K DoF is achievable if the total number of communication pairs n scales ω(SNRK(K-1)) where SNR denotes the received signal-to-noise ratio. In addition, the total amount of the required feedback for the worst case and the feedback overhead per user are investigated in interference limited environments.

In this paper, we illuminate opportunistic interference alignment (OIA) for multi-input multi-output (MIMO) interfering multiple-access channels (IMACs) by tackling the following two practical challenges: i) feedback overhead due to scheduling metrics sent by users and ii) sub-optimality in terms of sum-rate derived from the conventional OIA. To reduce the feedback overhead, we first propose an opportunistic feedback strategy based on interference leakage, which guarantees the total generating interference to other-cell base stations to be smaller than a predefined threshold. In addition, we also consider the channel gain of the desired link for improving the achievable sum-rate for uplink, while the conventional OIA only uses the generating interference to other cells as a scheduling metric. Simulation results show that the effective sum-rate of the proposed technique is significantly higher than that of conventional scheduling methods, including the conventional OIA, for all signal-to-noise ratio (SNR) regimes. The effective sum-rate is obtained by considering the effect of feedback overhead on the total throughput of the MIMO IMAC model.