In this paper, we propose a novel digital over-the-air computation (AirComp) framework employing space–time line codes (STLC) to achieve optimal spatial diversity gain with only local channel state information (CSI) at transmitters in uplink scenarios. The proposed technique alleviates the overhead of conventional AirComp, where the access point (AP) must acquire global CSI from all sensors, and is tailored to compute target functions under peak power constraints. Each sensor uniformly quantizes its measurement, applies bit slicing with low-order modulation, and transmits STLC-encoded symbols over two time slots. The AP subsequently performs linear combining of the received signals to detect the superimposed symbols and reconstruct the target sum. Simulation results demonstrate that the proposed technique achieves lower normalized mean-squared error than conventional analog and digital AirComp approaches.

In this paper, we propose a novel sequence index grouping-based multiple access (SIGMA) technique for multi-user orthogonal frequency division multiplexing-based integrated sensing and communication (OFDM-ISAC) systems. The proposed technique ensures collision-free access by performing a pre-assignment of orthogonal sequences (OSs) between the base station (BS) and each user equipment (UE), where each UE modulates its communication data onto the allocated sequence index and transmits it to the BS. By exploiting the autocorrelation property of the received sequences, the BS estimates the distance to each UE, while the direction of each user is obtained using a uniform linear array (ULA) antenna equipped at the BS. Furthermore, to achieve accurate localization even in non-line-of-sight (NLoS) multipath environments, a clustering algorithm and an oversampling technique are incorporated. Extensive simulation results demonstrate that the proposed system achieves robust localization and communication performance in multi-user scenarios.

In this paper, we propose a novel orthogonal frequency-division multiplexing (OFDM)-based interleave-division multiple access (IDMA) technique for non-terrestrial Internet-of-Things (IoT) networks utilizing low Earth orbit (LEO) satellites. Specifically, considering the direct links between LEO satellites and IoT devices, we tailor the IDMA framework by incorporating repetition to ensure stable performance even under severe path loss conditions. Furthermore, in accordance with the adoption of OFDM, which is expected to play a key role in sixth-generation (6G) mobile communications, we conducted practical simulations incorporating channel coding to verify the applicability of IDMA to non-terrestrial networks (NTNs). To enhance the reliability of performance evaluation, channel modeling was established based on standard-compliant NTN specifications. The comprehensive performance analysis confirms that IDMA provides stable and reliable multiple access, indicating its potential as a promising solution for future 6G non-terrestrial IoT networks.

This paper proposes a user scheduling algorithm to mitigate the critical cross-link interference (CLI) problem in in-band full duplex (IBFD) systems. In the proposed scheme, downlink (DL) user equipments (UEs) acquire effective CLI channel information from the beamformed pilot signals of scheduled uplink (UL) UEs. This allows the DL UEs to design receive beamformers that actively suppress CLI before the base station performs DL scheduling based on the mitigated interference. Simulation results demonstrate that our algorithm significantly improves the DL sum rate compared to conventional CLI measurement based schemes.

Recently, integrated sensing and communication (ISAC) techniques have gained significant attention due to their ability to simultaneously perform sensing, localization, and communication using shared wireless resources and signal waveforms, thereby enhancing spectral and cost efficiency. Orthogonal frequency division multiplexing (OFDM) is also expected to remain a key technology in next-generation mobile communication systems due to its robustness against multipath fading and its strong support for high data rates. Building on these points, we propose a novel orthogonal sequence (OS)- based OFDM-ISAC technique fully compatible with conventional OFDM-based communication systems. This technique intelligently exploits the autocorrelation properties of OSs and the spectral efficiency of index modulation while incorporating a clustering algorithm to address challenges in multipath environments. Extensive computer simulations verify that the proposed OFDM-ISAC system delivers reliable communication and localization performance in realistic multipath environments. even in the absence of a line-of-sight (LOS) link.

Recently, Internet of Things (IoT) devices have been installed everywhere, and these devices are connected through wireless communication networks. In particular, unmanned aerial vehicles (UAVs), one of the most promising IoT devices, are expected to be used actively in Internet of Battlefield-Things (IoBT) networks due to their flexible three-dimensional (3D) mobility. To react to enemy UAV attacks in the IoBT networks, the ground-to-air (G2A) or air-to-air (A2A) radio jamming can be an effective counterattack technique that disrupts the communication and control signals of adversary equipment. That is, it can be a very effective means of coping with attacks by UAVs in modern battlefields characterized by electronic warfare. Accordingly, this paper proposes a hierarchical distributed deep reinforcement learning-based cooperative jamming (HDRL-CJ) method for secure air-ground integrated networks. The proposed method uses two types of jammers: ground jammers (GJ) and UAV jammers (UJ). The GJ optimizes the beamwidth to maximize the effectiveness of jamming, and the UJ tracks the malicious UAV (MU) and controls the jamming power to minimize the MU’s signal-to-jamming-plus-noise ratio (SJNR) while considering the UJ’s limited battery capacity. Moreover, to reduce the computational complexity of reinforcement learning (RL) method, we devise a hierarchical RL architecture that separates the UJ’s movement control and transmit power control. Through extensive simulations, we demonstrate that the proposed HDRL-CJ method converges to the optimal solution obtained by the optimal exhaustive search algorithm. Furthermore, by comparing the jamming performance with several benchmark methods, we validate the proposed method’s superior performance under various 3D network environments.

Addressing the limitations of traditional sensor-based systems vulnerable to environmental constraints and trust issues, this article introduces a blockchain-assisted maximum evacuation framework in zero trust hiking trail and mountainous terrain using Internet of Things (IoT) devices that leverages blockchain technology for enhanced security and reliability. We devise three innovative algorithms that are designed to maximize the activation of evacuation nodes, ensuring rapid and efficient disaster response. By updating safe areas and evacuation routes dynamically in real-time IoT environment, the developed algorithms aim to significantly improve emergency response capabilities in challenging terrains. Also, the extensive simulations are achieved to demonstrate the performances of the proposed schemes with discussions for obtained outcomes.

We propose a novel physical-layer security (PLS) technique for multiple-input multiple-output (MIMO) two-way untrusted relay-assisted (TWUR) internet-of-things (IoT) networks by combining constellation-overlapping-based over-the-air encryption (OTAE) and space-time codes. Like the conventional two-way relay system, the proposed system operates in two phases: multiple access and broadcast. In the first phase, two IoT devices exploit the power-controlled space-time line code (STLC) with truncated channel inversion to transmit data frames such that their constellations completely overlap at the untrusted relay. This makes it impossible for the relay to distinguish the exact signals of the IoT devices, thereby enhancing security. In the second phase, the relay amplifies and forwards the superimposed signal using the space-time block code (STBC). From the superposed signal, each IoT node decodes data transmitted by the other using self-interference cancellation. Simulation results demonstrate that the proposed technique achieves the same security performance as the conventional constellation-overlapping-based OTAE scheme while significantly improving communication performance by effectively leveraging multiple antennas at both the untrusted relay and IoT devices. Specifically, the proposed technique maintains an error floor above 0.1 at the untrusted relay, ensuring secure communication by preventing unauthorized signal decoding. Furthermore, compared to the conventional OTAE scheme, it significantly improves the bit error rate (BER) at IoT devices while maintaining low computational complexity. In contrast to existing MIMO-based PLS schemes, the proposed technique operates without requiring global channel state information (CSI), thereby reducing signaling overhead and making it more practical for IoT networks. Finally, we mathematically analyze the error rate of the proposed technique using the piecewise linear approximation (PLA) and confirm that the derived analytical results closely match the simulation outcomes.

We consider a downlink reconfigurable intelligent surfaces-based non-orthogonal multiple access technique with constellation adjustment (RIS-NOMA-CA) for 6G wireless communication systems. We mathematically analyze the bit-error-rate (BER) performance of the RIS-NOMA-CA technique assuming the optimal joint maximum likelihood (JML) detector at receivers. To the best of our knowledge, theoretical analysis of the downlink RIS-NOMA-CA technique has not been reported in the literature. We show that the RIS-NOMA-CA technique yields a better BER performance than the conventional RIS-NOMA technique without CA through computer simulations, and our analytical result matches well with simulation results.

We propose a novel hierarchical multiple signal classification (H-MUSIC) technique that elaborately estimates the direction-of-arrival (DOA) of multiple signal sources arriving from similar directions. In general, the conventional MUSIC technique does not result in a good DOA estimation performance in this case. The basic idea of the proposed H-MUSIC technique is to combine the conventional MUSIC and beam-space MUSIC techniques. The receiver performs a coarse DOA estimation using the conventional MUSIC technique as a first step, considering a whole range of directions. Then, in the subsequent step, the receiver additionally performs a fine DOA estimation using the beam-space MUSIC technique, focusing on the directions where the signals are likely to exist. Through extensive computer simulations, we show that the proposed H-MUSIC technique significantly outperforms the conventional MUSIC technique even in the low signal-to-noise (SNR) regions and with a small number of time samples.

We mathematically characterize the coverage probability of spectrum-shared wireless networks based on stochastic geometry over Nakagami-m fading channel, where the exclusion zone is adopted for protecting the primary network and all communication nodes are equipped with directional antennas. In particular, the actual antenna radiation pattern of practical directional antennas is first modeled via a step-wise approximation method. Based on the model, we obtain a closed-form mathematical expression on the coverage probability at a (typical) primary receiver. Also, it is approximated by a simple expression.

We propose a novel practical access point (AP) deployment technique for 6G ultra-reliable industrial Internet-of-things (IIoT) networks. In particular, a cell-free massive multiple-input multiple-output (CF -mMIMO) architecture is adopted to improve reliability with macro-diversity, where a station (STA) is simultaneously associated with and served by multiple APs. We first mathematically formulate an integer linear programming (ILP)-based optimization problem that minimizes the number of required APs while satisfying a certain quality-of-service (QoS) of IIoT networks, such as the minimum number of concurrent communication links and the minimum required signal-to-noise ratio (SNR). However, the optimal technique requires significant computational complexity and time, unfortunately. Hence, we propose a low-complexity AP deployment algorithm based on parallel search methods, named PRADA. The proposed algorithm sufficiently reduces the number of required APs in a computationally efficient manner while satisfying the QoS constraints.

We propose a novel array antenna-based global navigation satellite system (GNSS) anti-spoofing technique. In this paper, we consider a sophisticated spoofing attack scenario where a target single GNSS receiver equipped with an array antenna, a single spoofer with its own GNSS receiver, and multiple GNSS satellites exist. It is assumed that the spoofer knows the accurate location of a target GNSS receiver. The target GNSS receiver can estimate the direction of arrival (DoA) of all pseudo-random noise (PRN) code signals including the spoofing signals in real-time during the signal acquisition process. The target GNSS receiver can obtain a direction of the spoofer by exploiting the spatial characteristics of the spoofing signals in the estimated DoA information. Then, the target GNSS receiver performs the minimum mean squared error (MMSE) beamforming using the estimated authentic and spoofing DoA information. Through computer simulations, we verify that the proposed technique can effectively detect the spoofing attack with a few samples and elaborately mitigate the spoofing signal.

In line-of-sight (LoS) communication environments, geometrical placement and adjustment of antennas are crucial to improving achievable rates while ensuring robust communication performances for varying transmission distances between transmitter and receiver. In this paper, hence, we propose a novel low-complexity subarray-based uniform circular concentric array (UCCA) selection technique for robust line-of-sight (LoS) MIMO communication systems. In particular, we dynamically control the allocated power to each antenna of UCCA at the transmitter while the conventional schemes only consider the radius and the relative rotation angle of UCCA. Through extensive computer simulations, we show that the proposed subarray-based UCCA selection technique significantly outperforms the conventional scheme in terms of achievable rate and robustness for varying transmission distances in practical LoS MIMO communication environments.

In this study, we first present a framework that jointly optimizes energy harvesting and information decoding for Internet of Things (IoT) devices, which are capable of simultaneous wireless information and power reception, in a smarty city. In particular, a generalized power-splitting receiver for IoT devices is designed, where each antenna in the receiver has an independent power splitter, unlike the existing works in which only one power splitter is employed regardless of the number of antennas in the receiver. Such a receiver design can provide a great degree of freedom to improve the network performance. Based on the presented framework, for each IoT device, we formulate an optimization problem whose objective is to maximize the harvested energy of each IoT device while satisfying its data rate requirement. To solve this problem, we propose a double-deep deterministic policy gradient-based online learning algorithm which enables each IoT device to jointly determine receive beamforming and power-splitting ratio vectors in real time. Furthermore, each IoT device can implement the proposed algorithm in a distributed manner using only its local channel state information. As such, cooperation and information exchange among the base stations and IoT devices are not necessary when performing the proposed algorithm at IoT devices. The extensive simulation results show the validity of the proposed algorithm.

We propose a spectrally efficient uplink cooperative relaying protocol with$K$multiple half-duplex relay stations (RNs) for wireless Internet of Things (IoT) networks, where two IoT devices (IDs) and an access point (AP) cannot directly communicate with each other. The two IDs simultaneously transmit signals over the same spectrum resource using the nonorthogonal multiple access (NOMA) technique. In the proposed technique, at a certain time slot, a single RN is selected to send the received packets from two IDs in the previous time slot, while the remaining$K-1$RNs receive new packets from two IDs. Thus, the proposed relaying protocol can send$N$packets from an ID to the AP during$N+1$time slots without a duty-cycle loss in conventional half-duplex relaying schemes. We call the proposed protocol a spectrally efficient cooperative NOMA. The main highlight of our results is that we mathematically derive a closed-form outage probability of the proposed protocol by considering inter-relay interference, assuming an optimal joint decoding technique instead of successive interference cancelation (SIC) decoding at each RN. To the best of our knowledge, this is the first theoretical result in the literature. Extensive computer simulations are used to validate the mathematical results. Furthermore, it is shown that the proposed protocol significantly outperforms the existing two-hop half-duplex cooperative NOMA technique and the SIC decoding scheme in terms of outage probability.

A massive number of Internet-of-Things (IoT) and machine-to-machine (M2M) communication devices generate various types of data traffic in cellular IoT networks: periodic or nonperiodic, bursty or sporadic, etc. In particular, bursty and nonperiodic traffic may cause an unexpected network congestion and temporary lack of radio resources. In order to effectively accommodate such bursty and nonperiodic traffic, we propose a novel recursive access class barring (R-ACB) technique to optimally utilize the available resources associated with the random access procedure (RAP) that consists of multiple steps in cellular IoT networks, while existing ACB schemes only considered the resource of the first step of RAP, i.e., the number of available preambles. The proposed R-ACB technique consists of two main parts: 1) online estimation of the number of active IoT/M2M devices who have data to transmit to an eNodeB and 2) adjustment of the ACB factor that indicates the probability that an active device sends a preamble to eNodeB. It is notable that the estimation and the adjustment recursively affect each other when R-ACB operates. In addition, we also propose mathematical models to analyze the performance of R-ACB in terms of total service time, average access delay, resource efficiency, and energy efficiency (EE). Through extensive computer simulations, we show that the proposed R-ACB technique outperforms the conventional ACB schemes.

Grant-free multiple access (GFMA) is an emerging technology to accommodate a massive number of devices for 6G-enabled Internet of Things (IoT) networks. The main advantages of GFMA are to efficiently reduce control signaling overhead for resource scheduling while improving resource efficiency. In this article, we propose anovelresource-hopping-based GFMA (RH-GFMA) framework with resource hopping schemes for providing massive connectivity in 6G cellular IoT networks, where each IoT device is allowed to access physical radio resources by using a preassigned resource hopping pattern without not only resource request but also grant procedure, which is the so-called “one-shot” noninteractive multiple access. We exploit three types of resource hopping schemes in the proposed RH-GFMA framework: 1) random hopping; 2) resource group hopping; and 3) Latin-square group hopping. We mathematically analyze the RH-GFMA system performance in terms of the hopping pattern collision probability, maximum allowable packet delay, and interference-over-thermal. Finally, we derive an accommodation capacity of the proposed RH-GFMA framework, which is defined as the expected number of IoT devices accommodated in a cell under a maximum allowable packet-delay requirement and an interference-over-thermal constraint. With the proposed GFMA, massive IoT devices are expected to be efficiently accommodated in 6G wireless networks, while satisfying strict latency and reliability requirements.

Unslotted ALOHA protocol has been adopted as a channel access mechanism in commercial low-power wide-area networks (LPWANs), such as Sigfox and long-range (LoRa) alliance. This work examines the throughput and random access (RA) delay distribution of unslotted ALOHA systems by considering exponential random backoff (ERB) or uniform random backoff (URB) algorithm. We further characterize the operating region of the systems as unsaturated stable, bistable, and saturated regions in terms of the new packet arrival and retransmission rates. To run the system stably with the maximum throughput, we propose a Bayesian online backoff algorithm that estimates the number of backlogged devices. Its performance is compared with other algorithms, such as particle filter (PF)-based algorithm, binary exponential backoff (BEB) algorithm, and the algorithm of exploiting exact backlog size information. Through extensive simulations, it is demonstrated that the performance of the proposed algorithm is very close to the upper bound and robust to time-varying traffic condition.

In this paper, we propose a novel access control (AC) mechanism for cellular internet of things (IoT) networks with massive devices, which effectively satisfies various performance metrics such as access throughput, access delay, and energy efficiency. Basic idea of the proposed AC mechanism is to adjust access class barring (ACB) factor according to performance targets. For a given performance target, we derive the optimal ACB factors by considering not only the conventional preamble collision detection technique but also the early preamble collision detection technique, respectively. In addition, the proposed AC mechanism considers overall radio resources to optimize the ACB factor, which includes the number of preambles, random access response (RAR) messages, and physical-layer uplink shared channels (PUSCHs), while most conventional ACB schemes consider only the number of preambles. In particular, the proposed AC mechanism is illustrated with two representative performance metrics: latency and energy efficiency. Through extensive computer simulations, it is shown that the proposed versatile AC mechanism outperforms the conventional ACB schemes in terms of various performance metrics under diverse resource constraints.

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.

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.

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.

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.

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.

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 ( α-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 α-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.

We study multi-stream transmission in the K x N x K channel with interfering relay nodes, consisting of K multi-antenna source-destination (S-D) pairs and N single-antenna half-duplex relay nodes between the S-D pairs. We propose a new achievable scheme operating with partial effective channel gain, termed multi-stream opportunistic network decoupling (MS-OND), which achieves the optimal degrees of freedom (DoF) under a certain relay scaling law. Our protocol is built upon the conventional OND that leads to virtual full-duplex mode with one data stream transmission per S-D pair, generalizing the idea of OND to multi-stream scenarios by leveraging relay selection and interference management. Specifically, two subsets of relay nodes are opportunistically selected using alternate relaying in terms of producing or receiving the minimum total interference level. For interference management, each source node sends S (1 <; S <; M) data streams to selected relay nodes with random beamforming for the first hop, while each destination node receives its desired S streams from the selected relay nodes via opportunistic interference alignment for the second hop, where M is the number of antennas at each source or destination node. Our analytical results are validated by numerical evaluation.

In this paper, we propose a virtual full-duplex cooperative non-orthogonal multiple access (NOMA) framework for a downlink two-hop network assisted by multiple half-duplex decode-and-forward (DF) relay stations (RSs). In the proposed virtual full-duplex framework, the RSs except for a selected RS to forward the received signal suffer from inter-RS interference since both the BS and the selected RS transmit the super-imposed signal simultaneously. To address this problem, we propose an RS selection algorithm with adaptive inter-RS interference management and we mathematically attain the closed-form outage probability, which is challenging in general. In addition, we investigate diversity-multiplexing tradeoff (DMT) performance of a modified version of the proposed RS selection algorithm based on a discrete Markov chain, which adaptively resets the successive transmission. Simulation results show that the proposed RS selection algorithm outperforms the conventional cooperative NOMA algorithm in terms of both the outage probability and the DMT, which has the best performance reported in the literature.

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 consider a two-way relay network consisting of a single relay node and two source nodes, where both the relay node and source nodes are equipped with multiple antennas. Two source nodes are assumed to transmit data with spatial modulation (SM) and the relay node is assumed to try to decode the network-coded packet (via bit-wise exclusive OR operation) of the two packets received from two source nodes, respectively. We propose a maximum-likelihood (ML) signal detection technique for the physical-layer network coded packet with SM for the relay node. Extensive simulation results show that the bit-error rate (BER) at the relay node becomes significantly improved with the proposed SM-based physical-layer network coding (PNC) technique, compared with the conventional PNC technique that achieving the same data rate. In particular, the performance of the proposed technique becomes excellent when the number of antennas at the nodes is large and the data rate is high, which implies that the proposed technique is suitable for the next-generation wireless communication system, i.e. 5G. Note that the proposed SM-based PNC technique does not require channel state information at transmitter (CSIT) and thus it can be implemented easily in practice.

The authors propose an adaptive cell‐breathing (ACB) technique to improve the energy efficiency (EE) of a downlink cellular network consisting of small‐cell base stations (BSs), wherein each BS adaptively adjusts its transmission power such that the received signal strength of the worst‐case user is larger than a pre‐defined threshold. They also propose an aggressive BS on–off (ABO) technique in which the small‐cell BSs having a number of users smaller than a certain value, , are turned off, whereas conventional techniques only turn off the empty BSs. They adopt a stochastic geometry for modelling the locations of both BSs and users. Simulation results show that the ACB technique yields a much better EE than the power on–off technique with a fixed power, including the ABO technique. In particular, the EE of the ACB technique is proportional to , where denotes the BS density and the exponent c denotes the increasing ratio of the EE to in the domain. The EE of the ABO technique tends to increase as increases.

In cellular Internet-of-Things (IoT) systems, system overload may occur during a random access (RA) procedure under a limited number of preamble resources and physical uplink shared channel (PUSCH) resources especially when there exist massive IoT devices in a cell. In order to resolve the system overload, the commercial system like 3GPP LTE adopted a group paging (GP)-based uplink access technique, but it has been known that the performance of the GP-based technique drastically degrades as the number of devices increases. In this paper, we first propose a dynamic access control (DAC) mechanism for the GP-based cellular massive IoT system, which dynamically adjusts RA-attempting probability by considering not only the number of available preambles but also the number of available PUSCH resources. We also intelligently combine the proposed DAC mechanism with an early preamble collision detection technique to further improve the RA performance of the cellular IoT system. Through extensive computer simulations, we show that the proposed DAC mechanism outperforms the conventional access control mechanisms, which consider only the number of available preamble resources, in terms of GP completion time, PUSCH resource efficiency, transmission efficiency, and energy efficiency.

A pricing‐based distributed spectrum access technique for cognitive radio (CR) networks which adopt the geolocation database (GD) is proposed. The GD contains which frequency bands are occupied by the primary system in a particular location. Given that multiple CR systems may attempt to transmit data over the same frequency band when the GD is used, the achievable rate of the CR systems becomes deteriorated due to interference. In the proposed technique, each (secondary) CR system determines whether it utilises vacant frequency bands by considering the cost of using them, which is calculated by taking into account the interference. The authors analyse the behaviour of the CR systems based on game theory. In particular, it is shown that the sum capacity of CR systems is maximised when the number of utilised bands is proportional to the relative channel gain with respect to the average channel gain at each CR system. In addition, the authors obtain the optimal cost for the vacant bands, which achieves the maximum sum capacity of CR systems. Finally, it is shown that the sum capacity of the (secondary) CR systems is significantly improved via proper pricing policy on the vacant frequency bands through extensive computer simulations.

We introduce a new achievability scheme, termed opportunistic network decoupling (OND), operating in virtual full-duplex mode. In the scheme, 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 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. Our protocol basically operates in a fully distributed fashion along with local channel state information, thereby resulting in relatively easy implementation.

In this paper, we propose an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that the minimum number of users required to achieve a target degrees-of-freedom can be fundamentally reduced, i.e., the fundamental user scaling law can be improved by using the ODIA, compared with the existing downlink IA schemes. In addition, we adopt a limited feedback strategy in the ODIA framework, and then analyze the number of feedback bits required for the system with limited feedback to achieve the same user scaling law of the ODIA as the system with perfect channel state information. We also modify the original ODIA in order to further improve the sum-rate, which achieves the optimal multiuser diversity gain, i.e., log log N, per spatial stream even in the presence of downlink inter-cell interference, where N denotes the number of users in a cell. Simulation results show that the ODIA significantly outperforms existing interference management techniques in terms of sum rate in realistic cellular environments. Note that the ODIA operates in a non-collaborative and decoupled manner, i.e., it requires no information exchange among BSs and no iterative beamformer optimization between BSs and users, thus leading to an easier implementation.

In this paper, we propose a novel user scheduling that achieves the optimal multi-user diversity gain in multi-cell uplink networks with multiple eavesdroppers. In the proposed scheduling, each base station (BS) selects a certain user based on two pre-determined thresholds (i.e., scheduling criteria). The first threshold is related to the amount of generating interference of the users to other BSs and the second threshold is related to the maximum amount of information overheard by the eavesdroppers in the network. Simulation results show that the proposed scheduling significantly outperforms the other scheduling algorithms in terms of secrecy throughput. Note that the proposed scheduling can operate with a distributed manner when time division duplex is adopted, i.e., no coordination among different BSs is needed.

Function computation over wireless sensor networks is investigated, where a set of K sensors observe their sensor readings and a fusion center wishes to learn a predefined function of the sensor readings via fading multiple access channels (MACs). In this paper, the arithmetic sum and type functions are considered since they can yield various fundamental sample statistics such as mean, variance, maximum, and minimum. We propose a novel opportunistic in-network computation (INC) framework in which a subset of sensors with large channel gains opportunistically participate in the transmission at each time, while all sensors simultaneously send their observations or only a single sensor sends its observation in the conventional schemes. We mathematically analyze the long-term average computation rate of the proposed INC, and prove that it achieves a nonvanishing computation rate even when the number of sensors K tends to infinity, which is in fact a significant improvement and the first theoretical result in fading MACs. Note that the computation rates of the conventional schemes become zero as K increases. We further show that a similar multiuser diversity gain is still achievable under delay constraints, which implies that the proposed INC is restricted to exploit a fixed and finite number of time slots (or fading instances) for the function computation.

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.

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.

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.

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.

In this paper, we investigate fundamental performance limits of cumulative distribution function (CDF)-based scheduling (CS) in downlink cellular networks. CS is known as an efficient scheduling method that can assign different time fractions for users or, equivalently, satisfy different channel access ratio (CAR) requirements of users while exploiting multiuser diversity. We first mathematically analyze the throughput characteristics of CS in arbitrary fading statistics and data rate functions. It is shown that the throughput gain of CS increases as the CAR of a user decreases or the number of users in a cell increases. For Nakagami-m fading channels, we obtain the average throughput in closed form and investigate the effects of the average signal-to-noise ratio, the shape parameter m, and the CAR on the throughput performance. In addition, we propose a threshold-based opportunistic feedback technique in order to reduce feedback overhead while satisfying the CAR requirements of users. We prove that the average feedback overhead of the proposed technique is upper-bounded by -lnp, where p is the probability that no user satisfies the threshold condition in a cell. Finally, we adopt a novel fairness criterion, called qualitative fairness, which considers not only the quantity of the allocated resources to users, but also the quality of the resources. It is observed that CS provides a better qualitative fairness than other scheduling algorithms designed for controlling CARs of users.

The parallel relay network is studied, in which a single source node sends a message to a single destination node with the help of N parallel relays. Channel coefficients are assumed to vary over time and channel state information (CSI) is causally available only at the receiver side (CSIR). Opportunistic noisy network coding is proposed for intelligently exploiting CSIR at each relay in a distributed manner by operating the noisy network coding scheme with adaptive compression. More specifically, each relay opportunistically vector-quantizes the collection of received symbols that is received with channel gains larger than a certain threshold. It then forwards the digital compression information to the destination node using independently generated Gaussian codes. For independent and identically distributed (i.i.d.) Rayleigh fading, the proposed scheme is shown to achieve the ergodic capacity in the large number of relays regime. Furthermore, the proposed scheme is extensively compared with several alternative schemes, the decode-forward scheme, the adaptive amplify-forward scheme, and the non-adaptive noisy network coding scheme over geometric models. We show that the new proposed scheme provides significant gain over these schemes in various cases.

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.

In this paper, we propose an opportunistic interference alignment (OIA) technique for cellular downlink networks, which efficiently reduces the effect of inter-cell interference from base stations (BSs) in other cells and eliminates intra-cell interference among spatial streams in the same cell. We show that the user scaling per cell required to achieve a target degrees-of-freedom can be fundamentally lowered, compared with the previous results. In addition, we relate the derived user scaling law to the interference decaying rate with respect to the number of users for given signal-to-noise ratio. Simulation results show that the proposed OIA significantly outperforms the previous schemes in terms of both sum-interference and achievable sum-rate even 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.

We introduce an opportunistic downlink interference alignment (ODIA) for interference-limited cellular downlink, which intelligently combines user scheduling and downlink IA techniques. The proposed ODIA not only efficiently reduces the effect of inter-cell interference from other-cell base stations (BSs) but also eliminates intra-cell interference among spatial streams in the same cell. We show that compared to the existing downlink IA schemes, the minimum number of users required to achieve a target degrees-of-freedom (DoF) can be fundamentally reduced, i.e., the fundamental user scaling law can be improved, by using the ODIA. In addition, we introduce a limited feedback strategy in our ODIA framework, and then analyze the minimum number of feedback bits required to obtain the same performance as that of the ODIA assuming perfect feedback.

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 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 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.

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 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.

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.

We investigate achievable degrees-of-freedom (DoF) of an (N, K)-user interference channel where only K user (transmitter-receiver) pairs among N user pairs are allowed to simultaneously communicate in a dense network (N ≫ K). Each node is assumed to have M antennas and to be randomly located. We propose a distributed scheduling protocol to achieve the maximum DoF (i.e., MK), which sequentially and opportunistically selects a user pair causing/receiving interference lower than a pre-determined threshold to/from already selected user pairs in each step. It is proven that the proposed protocol achieves the maximum DoF, MK, in the (N, K)-user interference channel with less stringent network size N, compared with the conventional centralized protocol which has been known as the best. With zero-forcing detector at receiver, we prove that it is sufficient that the network size N scales at least as ω(SNR(M2)K(K-1))to achieve the maximum number of DoF MK, where SNR denotes the received signal-to-noise ratio. We also investigate the required feedback overheads of the proposed protocol and show that it is quite small when the network is strongly interference-limited because only a small number of users are required to transmit their signaling. Our numerical results show that our proposed scheme controls interference more effectively than the centralized protocol.

This paper presents a spectrally efficient protocol for half-duplex multi-relay systems in block fading channels where a direct source-destination link is unavailable. The proposed protocol adaptively selects either successive interference cancelation (SIC) or joint decoding according to the causal decoding status of each relay. We also adopt dynamic refreshing that restarts the protocol whenever it is advantageous to do so, even if the relay decoding set (the set of relays that are able to decode the message) is not empty. The achievable diversity-multiplexing tradeoff (DMT) of the proposed protocol with m-antenna nodes is analyzed via a Markov chain whose states are related to the cardinality of a decoding set. This protocol strictly improves the DMT of the existing DF half-duplex relay-selection protocols without decoding delay, and in the low multiplexing gain region is able to meet the DMT upper bound. The main contributions of the paper are the state-dependent decoding strategies in DF multi-relay systems and also the dynamic refresh for the flushing of residual interferences in the system, concepts that may find usefulness beyond the gains in the high-SNR regime.

We consider the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N users having L antennas each. In this paper, we propose two opportunistic interference alignment (OIA) techniques utilizing multiple transmit antennas at each user: antenna selection-based OIA and singular value decomposition (SVD)-based OIA. Their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting users per cell. We assume that each selected user transmits a single data stream at each time-slot. It is shown that the antenna selection-based OIA does not fundamentally change the user scaling condition if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case, which is given by SNR(K-1)S, where SNR denotes the signal-to-noise ratio. In addition, we show that the SVD-based OIA can greatly reduce the user scaling condition to SNR(K-1)S-L+1through optimizing a weight vector at each user. Simulation results validate the derived scaling laws of the proposed OIA techniques. The sum-rate performance of the proposed OIA techniques is compared with the conventional techniques in MIMO IMAC channels and it is shown that the proposed OIA techniques outperform the conventional techniques.

We consider a new opportunistic interference alignment (OIA) for the K-cell multiple-input multiple-output (MIMO) interfering multiple-access channel (IMAC) with time-invariant channel coefficients, where each cell consists of a base station (BS) with M antennas and N mobile stations (MSs) having L antennas each. In this paper, we propose three OIA techniques: antenna selection-based OIA, singular value decomposition (SVD)-based OIA, and vector-quantized (codebook-based) OIA. Then, their performance is analyzed in terms of user scaling law required to achieve KS degrees-of-freedom (DoF), where S(≤ M) denotes the number of simultaneously transmitting MSs per cell. As our main result, it is shown that the antenna selection-based OIA does not fundamentally change the user scaling required to achieve KS DoF if L is fixed, compared with the single-input multiple-output (SIMO) IMAC case. In contrast, it is shown that the SVD-based OIA can greatly reduce the required user scaling to SNR(K-1) S-L+1through optimizing weight vectors at each MS. Furthermore, we show that the vector-quantized OIA can achieve the same user scaling as the SVD-based OIA case if the codebook size is beyond a certain value. For the vector-quantized OIA, we analyze a fundamental tradeoff between the quantization level (i.e., codebook size) and the required user scaling.

IEEE 802.11ac standard has newly adopted a downlink multi-user multiple-input and multiple-output (DL-MU-MIMO) scheme. For user multiplexing in downlink WLAN, we can also use a frame aggregation scheme for multiplexing multiple users' data with space-time block coding (STBC) for achieving spatial diversity. We compare the performance of the two downlink user multiplexing schemes: multi-user MIMO and frame aggregation in IEEE 802.11ac. If each user's encoded data stream has a similar length, the multi-user MIMO scheme yields better average throughput than the frame aggregation scheme. On the other hand, if each user's encoded data stream has a different length, the frame aggregation scheme outperforms the multi-user MIMO scheme in terms of average throughput. In a fast-varying channel, the multi-user MIMO scheme yields worse throughput due to the channel feedback overhead, compared to that with the frame aggregation scheme. We also observe that the multi-user frame aggregation scheme with STBC always outperforms a single-user transmission scheme with STBC in terms of average throughput due to enhanced MAC layer efficiency through frame aggregation.

We introduce an opportunistic interference mitigation (OIM) protocol, where a user scheduling strategy is utilized in K-cell uplink networks with time-invariant channel coefficients and base stations (BSs) having M antennas. Each BS opportunistically selects a set of users who generate the minimum interference to the other BSs. Two OIM protocols are shown according to the number of simultaneously transmitting users per cell, S: opportunistic interference nulling (OIN) and opportunistic interference alignment (OIA). Then, their performance is analyzed in terms of degrees-of-freedom (DoFs). As our main result, it is shown that KM DoFs are achievable under the OIN protocol with M selected users per cell, if the total number of users in a cell, N, scales at least as SNR(K-1)M. Similarly, it turns out that the OIA scheme with S((K-1)S. These results indicate that there exists a trade-off between the achievable DoFs and the minimum required N. By deriving the corresponding upper bound on the DoFs, it is shown that the OIN scheme is DoF-optimal. Finally, numerical evaluation, a two-step scheduling method, and the extension to multi-carrier scenarios are shown.

We introduce a distributed opportunistic scheduling (DOS) strategy, based on two pre-determined thresholds, for uplink K-cell networks with time-invariant channel coefficients. Each base station (BS) opportunistically selects a mobile station (MS) who has a large signal strength of the desired channel link among a set of MSs generating a sufficiently small interference to other BSs. Then, performance on the achievable throughput scaling law is analyzed. As our main result, it is shown that the achievable sum-rate scales as K log(SNR log N) in a high signal-to-noise ratio (SNR) regime, if the total number of users in a cell, N, scales faster than SNRK-1/1-εfor a constant ε∈(0,1). This result indicates that the proposed scheme achieves the multiuser diversity gain as well as the degrees-of-freedom gain even under multi-cell environments. Simulation results show that the DOS provides a better sum-rate throughput over conventional schemes.

The recently developed noisy network coding naturally extends compress-forward coding for the relay channel by Cover and El Gamal to arbitrary relay networks. In particular, the noisy network coding scheme achieves the best known capacity lower bound for general Gaussian networks. Motivated by the recent development of noisy network coding, we propose a novel extension of noisy network coding specialized for the fading parallel relay network. In the new scheme, the relay observation is opportunistically compressed by adapting on the local channel state information of the source-relay link. More specifically, each relay node opportunistically compresses the collection of output symbols with channel gains above a certain threshold, and forwards the digital compression to the destination node using independent Gaussian codes. To present the potential of the new scheme, we focus on the symmetric setting in which the channel coefficients within each hop are identically and independently distributed. We show that in the large number of relays regime, our scheme achieves the capacity while outperforming other schemes such as amplify-forward and decode-forward. Our result demonstrates that adaptation using channel state information at the receiver side can be beneficial.

A practical protocol jointly considering PHY and MAC for MIMO based concurrent transmissions in wireless ad hoc networks, called Contrabass, is presented. Concurrent transmissions refer to simultaneous transmissions by multiple nodes over the same carrier frequency within the same interference range. Contrabass is the first-to-date open-loop based concurrent transmission protocol which implements simultaneous channel training for concurrently transmitting links without any control message exchange. Its MAC protocol is designed for each active transmitter to independently decide to transmit with near optimal transmission probability. Contrabass maximizes the number of successful concurrent transmissions, thus achieving very high aggregate throughput, low delays and scalability even under dynamic environments. The design choices of Contrabass are deliberately made to enable practical implementation which is demonstrated through GNURadio implementation and experimentation.

Due to high spectral-efficiency of multiple-input multiple-output (MIMO) transmission techniques, IEEE 802.11n WLAN system adopted a single-user MIMO (SU-MIMO) scheme in which multiple symbol streams are transmitted from a single station (STA) to enhance the system performance. On the other hand, recently, adoption of a multi-user MIMO (MU-MIMO) scheme for multi-packet reception (MPR) in uplink WLAN has also attracted attention. The SU-MIMO scheme achieves a MIMO multiplexing gain at physical (PHY) layer while the MU-MIMO scheme achieves a MIMO multiplexing gain at medium access control (MAC) layer. Thus, there is a fundamental question which scheme is a better solution for uplink WLANs and, in this paper, we analyze and compare these two schemes with random STA distribution scenarios. Moreover, with the adaptation of MAC layer parameters, we also analyze and compare the maximum throughput performance of both the SU- and MU-MIMO schemes in uplink WLANs and we find a proper decision criterion to select the MIMO mode in uplink WLANs.

This paper investigates power allocation algorithms for OFDM-based cognitive radio systems, where the intra-system channel state information (CSI) of the secondary user (SU) is perfectly known. However, due to loose cooperation between the SU and the primary user (PU), the inter-system CSI is only partially available to the SU transmitter. Two types of PUs are considered to have different capabilities. One is a dumb (Peak Interference-Power tolerable) system that can tolerate a certain amount of peak interference at each subchannel. The other is a more sophisticated (Average Interference-Power tolerable) system that can tolerate the interference from the SU as long as the average interference over all subchannels is within a certain threshold. Accordingly, we introduce an interference power outage constraint, with which the outage is maintained within a target level. The outage is here defined as the probability that peak or average interference power to the PU is greater than a given threshold. With both this interference-power outage constraint along with a transmit-power constraint, we propose optimal and suboptimal algorithms to maximize the capacity of the SU. We evaluate the spectral efficiency through extensive simulations and show that the SU can achieve higher performance (up to two times) with the more sophisticated PU than with the dumb PU.

In this paper, we propose a cognitive p-persistent carrier sense multiple access (CpCSMA) scheme for spectrum sharing based cognitive radio (CR) networks. In order to guarantee the quality of service of the primary (licensed) network, secondary users are allowed to transmit their data as long as the interference received at a primary receiver is limited by the predetermined level. In the proposed CpCSMA scheme, secondary users adaptively control the transmit power with ON/OFF fashion according to whether the interference constraint at primary receivers is violated or not. We show that the proposed CpCSMA scheme can be mathematically analyzed by adopting the scaling factor to the conventional p-persistent CSMA analysis framework. The numerical examples illustrate that the analytical results match well to the simulation results and the throughput of the proposed CpCSMA scheme approaches to that of the conventional p- persistent CSMA scheme for high input load. Moreover, the proposed CpCSMA scheme is backward compatible and, thus, can easily be implemented with little modification of the conventional CSMA scheme.

Collision mitigation is one of classical research issues for wireless local area networks (WLANs). Recently, multiple-input multiple-output (MIMO) transmission techniques have been widely deployed in wireless systems, while a multi-user MIMO-based collision mitigation scheme in uplink WLANs was proposed by authors, and we showed the scheme is very efficient for the uplink performance. However, for an infrastructure-based WLAN, we observe a significant performance unbalance problem between uplink and downlink, compared to the conventional WLANs. Moreover, access point (AP) yields lower throughput performance than each contending station(STA). In order to solve this unbalance problem between uplink and downlink, we adopt a modified minimum contention window (CWmin) adjustment scheme and a random piggyback scheme to the multi-user MIMO-based WLANs. We also develop an analytical model to evaluate the performance of multi-user MIMO-based WLANs in a saturated traffic environment. The result shows that the random piggyback scheme performs more efficiently for the multi-user MIMO-based WLANs.

In this paper, we propose an adaptive sub-band exclusion (ASE) scheme as a means of intercell interference coordination (ICIC) technique to improve the performance of wireless cellular systems in a decentralized manner. Since ICIC is performed at each mobile station (MS), the proposed ASE scheme can be classified as a decentralized ICIC scheme. Compared to conventional centralized ICIC schemes, our proposed decentralized ASE scheme has the following advantages: cell and user coordinations are easier in the proposed ASE scheme, the complexity of ICIC at base stations (BSs) is reduced, and frequency selectivity characteristics of interference channels to neighboring base stations can be utilized in ICIC. Using the ASE scheme, each MS first finds which neighboring BS suffers most from the interference induced by the MS. Then, it determines an exclusion ratio alpha according to how much intercell interference the MS induces to the selected BS. Finally, it excludes alpha of orthogonal frequency division multiplexing (OFDM) sub-bands under the consideration of the frequency characteristics of the channel between the selected BS and itself. Through extensive computer simulations, we show that the proposed ASE scheme is effective in improving cell edge user performance by eight times at a reasonable degradation of average user performance.

Underlay transmission in cognitive radio enables a secondary (unlicensed) system to utilize a frequency band of primary (licensed) system as long as the unlicensee interferes less than a certain threshold with the licensee. The secondary system needs to carefully consider not only its own channel to achieve a capacity gain by this sharing spectrum in multi- carrier systems, but also the interference channel to reduce interference at the primary receiver. In this paper, we formulate a capacity maximization problem of the secondary system under an interference-power constraint as well as a conventional transmit- power constraint, and propose an optimal power allocation policy in which we exploit a two-dimensional frequency-selectivity on both channels. Through extensive simulations, we compare the performance of optimal power allocation policy with that of equal power allocation policy and further investigate the effect of the primary's power allocation policy on the performance of the secondary system. Numerical results show that the optimal power allocation policy can achieve a higher capacity in more frequency- selective channels, compared to an equal power allocation policy. Interestingly, a water-filling policy for the primary system also gives additional opportunities to the secondary system than the equal power allocation policy.

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.

We propose an orthogonal code hopping multiple access (OCHMA) scheme in order to improve the capacity of an uplink-synchronized code division multiple access (CDMA) systems. When orthogonal codes (OCs) are used for channelization in uplink-synchronized CDMA systems, a finite set of OCs tends to severely limit the capacity gain of the uplink-synchronized CDMA systems. The OCHMA system allows each user to use a different OC for each symbol according to an allocated hopping pattern (HP). It also allows multiple users to use the same OC at a specific symbol time, which is called an HP collision. Thus, the proposed OCHMA scheme can accommodate more users than the number of available OCs. We analyze the capacity of the OCHMA scheme and compare the performance of the OCHMA with that of conventional schemes including the system using multi-scrambling codes (MSC) which have also been proposed to overcome a code-limited situation.

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.

In this paper, we compare the performance of wireless local area networks (WLANs) with single-user MIMO (SU-MIMO) and multi-user MIMO (MU-MIMO) in terms of collision probability, average throughput, and delay. In the SU-MIMO scheme, multiple antennas are used for transmitting multiple data streams of a single user and this MIMO technique increases link capacity at physical (PHY) layer. In the MU-MIMO scheme, however, multiple antennas at different users are used for transmitting data streams of multiple users. The MU-MIMO scheme reduces the collision probability at medium access control (MAC) layer and increases the link capacity. Both MIMO schemes yield different collision, throughput, and delay performance at the MAC layer of WLANs. Numerical results show that the MU-MIMO scheme yields lower collision probability and shorter delay performance than the SU-MIMO scheme. Furthermore, the SU-MIMO scheme yields better throughput performance for high SNR values and a small number of contending stations. In other cases, the MU-MIMO scheme yields better throughput performance.

We propose an optimal modulation and coding scheme (MCS) selection criterion for maximizing user throughput in cellular networks. The proposed criterion adopts both the Chase combining and incremental redundancy based hybrid automatic repeat request (HARQ) mechanisms and it selects an MCS level that maximizes the expected throughput which is estimated by considering both the number of transmissions and successful decoding probability in HARQ operation. We also prove that the conventional MCS selection rule is not optimized with mathematical analysis. Through link-level and system-level simulations, we show that the proposed MCS selection criterion yields higher average cell throughput than the conventional MCS selection schemes for slowly varying channels.

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 this paper, the capacity of a TH-PPM UWB system with an outage constraint in multi-user environments is mathematically analyzed and evaluated. To mitigate a near-far problem, a near-interference erasure scheme is adopted and the capacity of the TH-PPM UWB system using the near-interference erasure scheme is evaluated through numerical analysis and Gaussian approximation. The numerical results show that the capacity of the TH-PPM UWB system using the near-interference erasure scheme is significantly improved and there exists an optimum threshold for the near-interference erasure scheme which maximizes the capacity. The capacity which is mathematically derived is very similar to that of numerical results in the region near the optimum threshold. Furthermore, the results are more accurate as the number of bit repetitions increases.

In this paper, we propose an adaptive sub-band nulling technique in order to improve the performance of orthogonal frequency division multiplexing (OFDM)-based wireless communication systems. It excludes some sub-bands experiencing deep-fading and the transmission power for the excluded sub-bands is reallocated for the remaining sub-bands. We compute the optimal number of nulled sub-bands in order to maximize the capacity. Water-filling is one well-known optimal resource allocation scheme. However, it has tremendous complexity at the transmitter and requires full channel state information from the receiver. We compare the performance of the proposed scheme with that of the water-filling scheme and the result shows that the performance of the proposed scheme is similar to that of the water-filling in a wide range of signal-to-noise ratio (SNR) values. Furthermore, the proposed adaptive sub-band nulling can be used as an enhanced distributed transmission mode in future OFDM-based wireless communication systems after a small modification in the frame structure.

We analyze the user capacity of downlink CDMA systems with quasi-orthogonal sequences (QOSs) considering various system parameters, such as user activity, spreading factor, the amount of transmission symbol energy allocated to common control channels, the amount of outer-cell interference, and sectorization factor. We also consider a power control mechanism with geometric factors such as propagation loss and shadowing effect. This user capacity analysis gives us the pole capacity of the system, which is the user capacity when all BSs transmit signals with unlimited power. Numerical examples show that the introduction of QOSs makes it possible to overcome the code limitation. We discuss how much the user capacity is increased according to various system parameters. For example, in an omni-cell environment with minimum outer-cell interference, if the mean channel activity and the required (Eb/I0) value are set to 0.2 and 2.0 [dB] respectively, the user capacity is 194 which is much higher than the code limitation.

We compare the performance of the downlink capacity improvement schemes based on orthogonal code hopping multiplexing (OCHM) and multiple scrambling codes (MSC). Both OCHM and MSC have been proposed in order to overcome a code-limitation problem in CDMA downlink. However, both schemes exhibit different characteristics. In order to increase user capacity in CDMA downlink, OCHM allocates a random hopping pattern using a set of orthogonal codes instead of orthogonal code for each connection and MSC allocates a non-orthogonal codeword to each connection. In the OCHM scheme, hopping pattern (HP) collisions may degrade the system performance. The HP collisions in OCHM systems differ from the hits in frequency- hopping (FH) systems because it can be effectively controlled through synergy and perforation techniques. In OCHM, the receiver requires additional energy for a given frame error rate (FER) due to the HP collision. In the MSC scheme, inner-cell interference is induced by non-orthogonal codewords and it degrades the performance. Numerical examples show that the OCHM-based system is more effective than the MSC-based system.

In orthogonal code hopping multiplexing (OCHM) systems, hopping pattern (HP) collisions may degrade the system performance. Previous studies on the effect of HP collisions in OCHM systems were mainly based on computer simulations and there was no rigorous mathematical analysis of bit error rate (BER) performance. The HP collisions in OCHM systems differ from the hits in frequency-hopping (FH) systems or intracell interference in DS-CDMA systems because it can be effectively controlled through synergy and perforation techniques. In this paper, we introduce a received signal model for OCHM systems and analyze the BER performance for OCHM systems. Through the analysis of the BER performance, OCHM systems can be characterized more clearly and the allocated power at base station can be estimated. Furthermore, the user capacity is analyzed for a given channel coding scheme.

In this paper, we propose a new transmission scheme that can improve greatly the performance of turbo-coded orthogonal frequency division multiplexing (OFDM) systems by making all the turbo-coded symbols have the same reliability for OFDM transmission over a frequency selective fading channel. The same reliability, that is, the same fading can be accomplished through multiplexing of turbo-coded symbols using distinct orthogonal codes and spreading over the whole effective subcarriers (hereafter, called the orthogonal code multiplexing (OCM)). This idea of the same fading for all symbols is the key of the performance improvement using the proposed scheme. As for the orthogonal code selection, a set of Walsh codes could be the best selection in terms of the complexity. However, in the fast Fourier transform (FFT) implementation of OFDM, the number of the whole effective subcarriers may be slightly less than the number of FFT points used. Hence, we choose the set of the discrete Fourier transform (DFT) basis sequences as a good substitute for a set of orthogonal codes, since the code set can hold the orthogonality irrespective of the length. We perform computer simulations using the log-maximum-a-posteriori (log-MAP) algorithm for iterative decoding in order to assess the performance of the proposed system and to compare it with that of the conventional turbo-coded OFDM system.