This paper proposes a joint access point (AP) clustering and beamforming design method for network-assisted full-duplex cell-free massive multiple-input multiple-output (NAFD CF-mMIMO) systems that maximizes energy efficiency (EE) while maintaining high spectral efficiency (SE). The proposed method improves energy efficiency (EE) by reducing power consumption of APs with low contributions to performance. Numerical results demonstrate that the proposed approach achieves SE performance comparable to that of conventional methods designed to maximize SE.

This paper proposes a joint channel and data estimation (JCDE) algorithm for uplink multiuser extremely large-scale multiple-input-multiple-output (XL-MIMO) systems. The initial channel estimation is formulated as a sparse reconstruction problem based on the angle and distance sparsity under the near-field propagation condition. This problem is solved using non-orthogonal pilots through an efficient low complexity two-stage compressed sensing algorithm. Furthermore, the initial channel estimates are refined by employing a JCDE framework driven by both non-orthogonal pilots and estimated data. The JCDE problem is solved by sequential expectation propagation (EP) algorithms, where the channel and data are alternately updated in an iterative manner. In the channel estimation phase, integrating Bayesian inference with a model-based deterministic approach provides precise estimations to effectively exploit the near-field characteristics in the beam-domain. In the data estimation phase, a linear minimum mean square error (LMMSE)-based filter is designed at each sub-array to address the correlation due to energy leakage in the beam-domain arising from the near-field effects. Numerical simulations reveal that the proposed initial channel estimation and JCDE algorithm outperforms the state-of-the-art approaches in terms of channel estimation, data detection, and computational complexity.

We consider robust hybrid beamfocusing schemes against statistical and norm-bounded positioning errors in order to improve a total system data rate in near-field communications. To this end, baseband and analog beamfocusing designs are formulated as an ergodic sum rate maximization, which is solved via deterministic and stochastic optimization. In particular, a closed-form expression of the erdodic sum rate is introduced, which makes the problem tractable by deterministic optimization. In turn, a new stochastic optimization algorithm is proposed for further data rate improvements, which incorporates matrix fractional programming (FP) and element-wise phase derivatives into stochastic learning frameworks by penalize methods. The proposed stochastic algorithm theoretically guarantees convergence to stationary points of the original problem. Numerical results confirm that the proposed approaches achieve higher data rates than non-robust approaches and a singular value decomposition (SVD) beamfocusing with perfect position information.

In this paper, we consider near-field beams that can mitigate signal attenuation and blockage effects using a uniform linear array (ULA). In particular, closed-form expressions for phase distributions in a ULA are derived to generate Bessel beams and curving beams based on the desired propagation directions and trajectories. Based on the phase distributions, the maximum steering angle and propagation distance of Bessel beams with a ULA are revealed. In addition, from the sampling theorem in the spatial domain, the requirements for ULAs to properly generate Bessel beams are clarified. For curving beams, trajectories to reach a user while avoiding one obstacle are designed via the Lagrangian method. Numerical results obtained by electromagnetic wave simulations confirm the effectiveness of the analyses for Bessel beams and the curving beam designs. Furthermore, the characteristics of Gaussian beams, beamfocusing, Bessel beams, and curving beams are summarized in terms of the statistical behavior of their intensity and signal processing.

In this paper, the optimal wavefronts for maximum ratio transmission (MRT) are investigated under path blockage effects in the near-field region. To characterize the behavior of the optimal wavefronts, a new deterministic channel model is proposed in the presence of obstacles, which describes blockage effects by the variation of the electric field based on the uniform theory of diffraction (UTD). With the proposed channel model, the linear precoder designs are formulated as optimization problems to maximize the power density at the desired point under fully digital and analog array assumptions, where the amplitude and phase distributions of the solutions characterize the optimal wavefronts to achieve MRT. The optimal precoders reveal that the proposed channel modeling must be required to optimize near-field communications systems in the presence of obstacles, which, together with electromagnetic wave simulations, confirm that linear precoding with the proposed channel model achieves MRT under any blockage effect, and the optimal wavefront varies for each blockage situation.

This paper investigates the uplink transmission of cell-free massive MIMO with multiple central processing units (CPUs) interconnected to each other by capacity-limited backhaul links. Considering the unavoidable effect of quantization noise through backhaul links, we study two different signal detection approaches: two-stage detection based on local combining (TDLC) and centralized detection (CD). We then propose a distortion-aware clustering (DAC) for both detection schemes and a deterministic combining vector for TDLC. Simulation results prove that the proposed clustering outperforms the conventional proximity-based clustering (PC). Moreover, the results reveal that CD is not always the best choice, depending on the capacity of backhaul links connecting CPUs.

This paper investigates the beamforming design for an upper mid-band multi-user multiple-input single-output (MUMISO) system, aiming to mitigate interference from terrestrial base stations to satellites. The upper mid-band (7-24 GHz) is already utilized by several satellite services, necessitating the coexistence of emerging cellular systems with these existing satellite systems. As such, we propose a beamforming design with an angular radiated power constraint directed towards the sky angle region, effectively mitigating interference without requiring prior information about the satellites. Numerical results validate the efficacy of the proposed method in reducing interference. Moreover, we demonstrate that the proposed method can achieve sum spectral efficiency performance comparable to sum rate maximization approaches without such constraints.

We propose a quantum-assisted solution of the pilot assignment problem. In particular, we formulate a pilot assignment problem designed to minimize the interference from co-pilot user terminals as a binary optimization problem which can be solved via a quantum exhaustive search through the Grover adaptive search (GAS) algorithm. The performance of GAS in terms of query complexity is enhanced by introducing a modified initial state and an improved initial threshold using the upper bound for the minimum value of the objective function. Simulation results demonstrate that our proposed method can provide quadratic speedup compared to an exhaustive search performed by a classical computer, concretely demonstrating that quantum computers can be employed to solve optimally and efficiently the pilot assignment problem.

We propose a new quantum-assisted maximum likelihood detection (MLD) scheme for generalized spatial modulation (GSM) systems. To that end, we first present a novel MLD formulation for GSM, and then describe a corresponding novel method to prepare the initial state for an associated quantum-computing Grover adaptive search (GAS) algorithm. Simulation results are presented to show that our approach achieves optimal performance and reduces query complexity compared both to the classical MLD and to earlier quantum search methods, which do not achieve an advantage over classical MLD for some parameter settings.

This paper presents an analytical model for blockage loss in millimeter-wave (mmWave) systems using analog beam-forming. The proposed approach computes the average blockage loss by marginalizing the loss obtained from the conventional extended METIS model over all possible blocker positions. This averaging enables the derivation of closed-form expressions for both the upper and lower bounds of the average blockage loss. The analysis reveals a trade-off between array gain and blockage loss, indicating that there exists an optimal number of antenna elements that maximizes the received power under stochastic blockage conditions.

In this paper, we propose a new transmission scheme for grant-free non-orthogonal multiple access (GF-NOMA) based on orthogonal frequency division multiplexing (OFDM) in the presence of timing offsets. The proposed method utilizes differential phase-shift keying (DPSK) between subcarriers, eliminating the need for channel estimation and mitigating the degradation of data detection caused by timing offsets. Furthermore, the proposed method conducts active user detection based on the coordinate descent method, which offers a lower computational complexity compared to the conventional method based on the structured generalized approximate message passing (S-GAMP). Computer simulations demonstrate that the proposed method achieves a lower miss detection probability compared to S-GAMP and a lower bit error rate than the method using PSK.

The conventional receiver-initiated MAC (RI-MAC) protocol employed in energy-harvesting wireless sensor networks (WSNs) mandates a specific listening duration to identify communication partners, which consequently increases power consumption and impedes the development of ultralow-energy WSNs. To address these limitations, the novel zero excess node MAC (ZEN-MAC) protocol is introduced. This protocol strategically reduces idle listening time, which dominates the networks power consumption, through the implementation of low-power listening with multi-stage beacons and clear channel assessment. It further optimizes intermittent intervals based on the estimated power consumption of the network to enable distributed load control. These enhancements significantly reduce power consumption and help prevent node battery depletion, thereby improving both the reliability and efficiency of WSNs.

In this paper, we propose a novel low-complexity Bayesian receiver design to jointly perform channel, CFO, and data estimation from observations subject to different CFO among users in MU-MIMO-OFDM systems. ICI due to CFO significantly reduces channel estimation accuracy under frequency-selective fading environments, making reliable communications difficult. To tackle this difficulty, a JCCE algorithm is designed based on BP. Our method uses a BG distribution as the prior distribution of the channel coefficient to capture its delay-domain sparsity, and a GM distribution as the prior distribution of the phase shift due to CFO to perform parallel search for the allowable range of CFO defined in the 3GPP standard by the number of mixture components. The proposed algorithm can further improve the accuracy of channel, CFO, and data estimation by treating the tentatively detected data symbols as extra pilots. The efficacy of the proposed method is confirmed by numerical studies, which show that the proposed method not only significantly outperforms the SotA methods with much lower computational cost but also approaches the performance of an idealized Genie-aided scheme.

We consider the joint design of time-domain equalization and hybrid transmit and receive beamforming schemes, so as to combat frequency-selective fading and path loss effects in single-carrier (SC) multiple-input multiple-output (MIMO) communications systems. In particular, considering the linear equalization and hybrid beamforming matrices as variables, a minimum mean square error (MMSE) problem to minimize the bit error rate (BER) of SC-MIMO systems is formulated and solved via an accelerated matrix quadratic transform (QT) and manifold optimization. The relationship between mean square error (MSE) minimization via joint MMSE equalization and beamforming, and the minimization of average BER over all data streams is expressed analytically, which together with numerical results confirm that the proposed SC scheme outperforms the SC systems whose linear equalizer and beamformers are designed separately.

This paper studies an uplink grant-free non-orthogonal multiple access (GF-NOMA) system using low-density signature orthogonal frequency division multiplexing (LDS-OFDM), where each user transmits non-orthogonal pilots and data symbols that are mapped onto a small number of subcarriers determined by the LDS sequence. After an initial estimation based on pilot symbols, our proposed receiver utilizes the low-density signal structure to improve active user detection, channel estimation, and multi-user detection accuracy. To achieve this, a birth-death drift process is applied to model the information exchange between two estimation modules for pilot and data symbols, and a corresponding side information (SI) calculation and denoiser design are proposed for SI-aided multiple measurement vector approximate message passing (MMV-AMP). Moreover, the asymptotic performance of the proposed SI-aided MMV-AMP is analyzed based on state evolution. Numerical results confirm that the proposed method outperforms state-of-the-art methods and that it can perform predictions using the derived state evolution.

In this paper, we present a novel approach to analog beam selection in cell-free massive multi-input multi-output (CF-mMIMO) systems employing hybrid beamforming (BF) over millimeter-wave (mmWave) channels. In conventional CF-mMIMO systems with hybrid BF, an analog beam is selected by a central processing unit (CPU) from a predefined codebook. This selection is based on the received power at each access point (AP) and the fairness among user equipment (UE). However, this conventional method disregards the potential impact of interference and heavily relies on digital BF to mitigate it. Consequently, when utilizing low-complexity digital BF techniques such as maximum ratio transmission (MRT), the system's performance experiences degradation. Our proposed beam selection method takes into account both the received power and the interference power, effectively mitigating the influence of interference while maintaining an adequate level of received power. The numerical simulations validate the efficacy of our proposed approach.

This paper proposes a multi-hop communications system that utilizes digital beamforming to efficiently collect data packets from sensor nodes (SNs) via the intermittent receiver-driven data transmission (IRDT) protocol. By leveraging beamforming, this system enables more SNs to directly communicate with a concentrator, increasing the number of idle SNs in the network available as potential receivers and thus preventing the data packet convergence on specific SNs. Furthermore, the resulting non-concentrated distribution of data packets allows beamforming to effectively limit the number of SNs with data packets, significantly reducing the probability of packet collisions. Simulation results demonstrate that our proposed system significantly improves the packet delivery ratio.

This paper investigates beamforming design with multi-panel arrays for millimeter-wave (mmWave) communications in the presence of channel fluctuations due to user equipment (UE) movement and sudden path blockage. In current commercial mmWave systems, a sharp analog beam is designed to be aligned to a line-of-sight (LoS) path using all antenna elements (full array) to attain high array gain. Although this approach is effective for static channels, it may lead to frequent disconnections of the communication link in actual mmWave environment with temporal fluctuations. Therefore, this paper revisits the design of analog beamforming composed of multi-panel arrays and studies the effectiveness of multiple beams with wide directivity, which are aligned not only to the LoS path but also to non-line-of-sight (NLoS) paths. Computer simulations illustrate the limitations of conventional sharp directive beamforming focused solely on maximizing array gain, and reveal the effectiveness of the proposed multiple beam design with multi-panel array over practical mmWave channels.

We propose a novel joint channel tracking and data detection (JCTDD) scheme to combat the channel aging phenomenon typical of millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication systems in high-mobility scenarios. The contribution aims to significantly reduce the communication overhead required to estimate time-varying mmWave channels by leveraging a Bayesian message passing framework based on Gaussian approximation, to jointly perform channel tracking (CT) and data detection (DD). The proposed method can be interpreted as an extension of the Kalman filter-based two-stage tracking mechanism to a Bayesian bilinear inference (BBI)-based joint channel and data estimation (JCDE) framework, featuring the ability to predict future channel state information (CSI) from both reference and payload signals by using an auto-regressive (AR) model describing the time variability of mmWave channel as a state transition model in a bilinear inference algorithm. The resulting JCTDD scheme allows us to track the symbol-by-symbol time variation of channels without embedding additional pilots, leaving any added redundancy to be exploited for channel coding, dramatically improving system performance. The efficacy of the proposed method is confirmed by computer simulations, which show that the proposed method not only significantly outperforms the state-of-the-art (SotA) but also approaches the performance of an idealized Genie-aided scheme.

We propose a scheme for the concomitant design of hybrid beamforming and per-carrier transmit power allocation to mitigate the effect of random path blockages in coordinated multi-point (CoMP) systems using orthogonal frequency division multiplexing (OFDM) in millimeter-wave (mmWave) channels. In order to optimize both the beamformers and power allocation while dealing simultaneously with outage minimization and sum rate maximization (SRM) requirements, a regularized sum-of-outage minimization problem is formulated. The problem is then transformed into an empirical risk minimization (ERM) problem, solved via block stochastic learning and manifold optimization, with required learning rates derived and tuned to guarantee convergence. The method, which demands only a few radio frequency (RF) chains and relies only on knowledge of blockage probabilities, is shown via simulation results not only to outperform state-of-the-art (SotA) alternatives, but to actually achieve outage probabilities comparable to those a fully digital CoMP-SRM scheme with perfect knowledge of instantaneous blockages.

This paper proposes a self-calibration algorithm for a hybrid millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) channel estimation in the presence of array manifold errors composed of mutual coupling, antenna gain/phase errors, and antenna spacing errors due to hardware impairments. The proposed algorithm can jointly estimate angles of arrivals (AoAs), angles of departures (AoDs), path gains, and array manifold errors. The initial coarse estimates for AoAs, AoDs, and path gains are derived by a compressed sensing (CS) algorithm without prior knowledge of array manifold errors. Subsequently, AoAs, AoDs, path gains, and array manifold errors are updated based on corresponding maximum likelihood (ML) criteria. Numerical results demonstrate that the proposed algorithm has superior performance with low pilot overhead compared to conventional methods.

This paper proposes a scalable network-assisted full-duplex (NAFD) cell-free massive multiple-input multiple-output (CF-mMIMO) system that achieves high spectral efficiency (SE) while reducing the fronthaul load by forming clusters of access points (APs) exclusively for uplink and downlink based on user equipment (UE) requirements, respectively. Specifically, we propose AP clustering techniques based on convex optimization and Hungarian algorithm, along with downlink transmit power control suitable for proposed AP clustering. Numerical results demonstrate that our proposed approach achieves higher SE than conventional scalable TDD CF-mMIMO, NAFD CF-mMIMO and small cell with dynamic time division duplex (TDD), under fronthaul capacity limitations.

This paper investigates an efficient system for collecting packets from a large number of sensor nodes (SNs) using the intermittent receiver-driven data transmission (IRDT) protocol. In our proposed system, we deploy a packet aggregation station such as gateway (GW) equipped with digital beamforming, which employs beam sweeping during downlink beacon transmission to mitigate collisions of send request (SREQ) packets from SNs. Furthermore, we utilize multiple digital reception beams in parallel, allowing for the simultaneous decoding of multiple packets in uplink transmission and thereby improving the packet delivery ratio (PDR). Numerical results validate the effectiveness of our proposal.

We propose a hybrid beamforming for coordinated multi-point (CoMP) transmission using orthogonal frequency division multiplexing (OFDM) over millimeter-wave (mmWave) channels to combat random propagation path blockages. In particular, a sum-of-outage-probability minimization problem with manifold constraints is formulated, which designs the hybrid beamformers, the data rate allocation, and the power allocation over subcarriers jointly to meet the prescribed data rate requirement. A new block stochastic learning mechanism exploiting prior knowledge of the path blockages is also introduced to solve the problem efficiently. Numerical results confirm the effectiveness of the proposed approach in minimizing the outage probability of users according to their target rate. Furthermore, these results also show that the proposed hybrid CoMP transmission only with a few radio frequency (RF) chains and knowledge of blockage probabilities achieves comparable outage performance to a fully digital CoMP transmission alternative with perfect knowledge of instantaneous path blockages.

We propose a novel physical layer security scheme that exploits an optimization method as a one-way function. The proposed scheme builds on nonsquare differential multiple-input multiple-output (MIMO), which is capable of noncoherent detection even in massive MIMO scenarios and thus resilient against risky pilot insertion and pilot contamination attacks. In contrast to conventional nonsquare differential MIMO schemes, which require space-time projection matrices designed via highly complex, discrete, and combinatorial optimization, the proposed scheme utilizes projection matrices constructed via low-complexity continuous optimization designed to maximize the coding gain of the system. Furthermore, using a secret key generated from the true randomness nature of the wireless channel as an initial value, the proposed continuous optimization-based projection matrix construction method becomes a one-way function, making the proposed scheme a physical layer secure differential MIMO system. An attack algorithm to challenge the proposed scheme is also devised, which demonstrates that the security level achieved improves as the number of transmit antennas increases, even in an environment where the eavesdropper can perfectly estimate channel coefficients and experience asymptotically large signal-to-noise ratios.

We propose a novel joint channel and data estimation (JCDE) scheme to combat the rate limitation in fronthaul links of cell-free massive MIMO (CF-mMIMO) systems introduced by the use of analog-to-digital converters (ADCs) at access points (APs), which makes channel estimation and multi-user detection at the central AP (CAP) challenging. The latter problem is solved here via the new JCDE scheme which differs from state-of-the-art (SotA) alternatives due to two contributions. The first is the design and incorporation of de-quantization (DQ) step which relies only on scalar Gaussian approximation (SGA) assumptions in conformity with mild central limit theorem (CLT), in contrast to the much harder asymptotic conditions required by the classic bilinear generalized approximate message passing (BiGAMP) algorithm. The second is a modification of bilinear Gaussian belief propagation (BiGaBP), whereby quantized outputs are linearized via the Bussgang decomposition enabling tractable signal processing. The resulting DQ-aided JCDE method achieves both low-complexity and high-accuracy by exploiting both the spatial degrees of freedom (DoF) obtained from, and the observations at the CAP to compensate for the low-resolution distortion introduced by, the distributed APs. The efficacy of the proposed method over the SotA is confirmed via computer simulations.

We propose a new grant-free non-orthogonal multiple access (GF-NOMA) scheme, which makes full use both of the time and of the delay domains for further enhancement on low-latency and massive connectivity. The proposed GF-NOMA is based on a tailored signal model involving the delay-domain channel sparsity in conjunction with phase transition analyses for approximate message passing (AMP) algorithms. Moreover, the proposed design enables efficient and accurate estimation by appropriately designing message-passing rules. Simulation results are offered to demonstrate the superiority of the proposed GF-NOMA approach over the conventional scheme.

In this paper, we propose a novel joint activity and channel estimation (JACE) algorithm for grant-free extra large MIMO (XL-MIMO) systems subject to spatial non-stationarity phenomena by means of a Bayesian bilinear inference framework. In XL-MIMO systems, the signal from each user is visible only by a small portion of its antenna arrays, which are typically distributed over the surface of a certain structure. The sporadic user activity due to grant-free access, as well as the spatial non-stationarity, jointly imposes a challenging JACE problem involving a nested Bernoulli-Gaussian random variable. In order to address this issue, we decompose the latter into a bilinear inference problem of two independent random quantities, deriving novel message passing rules based on Gaussian approximation and bilinear inference. Performance evaluation via software simulations is offered to demonstrate the effectiveness of the proposed algorithm, which achieves the Genie-aided ideal estimation performance.

Grant-free non-orthogonal multiple access (GF-NOMA) systems suffer from the performance degradation of active user detection (AUD) due to carrier frequency offsets (CFOs) caused by imperfect frequency synchronization among users and a base station. Although a conventional method efficiently performs CFO estimation, AUD, and channel estimation (CE) by introducing extended pilot sequences based on discrete grids of the CFOs, the inevitable estimation error caused by off-grid CFOs significantly degrades the quality of the CE. This paper proposes a more accurate joint AUD and CE method by performing AUD and CFO estimation independently and iteratively. Computer simulations demonstrate that our proposed scheme can estimate the active users and the corresponding channel coefficients as accurately as the case with the perfect knowledge of the CFOs.

Extra large MIMO (XL-MIMO) systems are subject to spatial non-stationarity forming visibility regions (VRs), which leads to a sub-array-wise sparse structure of the channel matrix. When XL-MIMO systems operate in grant-free access mode, in which only a fraction of the potential users are active during a given time slot, it follows that the channel matrix possesses a doubly-sparse and user-specific structure such that the activity of each user and each sub-array can be jointly modeled by a nested Bernoulli-Gaussian distribution. This article considers the joint activity and channel estimation (JACE) problem in XL-MIMO systems subject to this so-defined spatial non-stationarity, tackling this challenging inference problem. Our main contributions are 1) to introduce the novel Bernoulli-Gaussian model to simultaneously capture the aforementioned two distinct structured sparsities, and 2) a new bilinear Bayesian inference algorithm capable of jointly estimating the associated channel coefficients, user activity patterns, sub-array activity patterns ($a.k.a$. spatial non-stationarity), boosted by expectation maximization (EM)-based auto-parameterization. In addition, to shed light on a realistic modeling of VRs, we also introduce a Matérn-cluster point process (MCPP)-based approach to imitate the clustered activity pattern due to spatial non-stationarity. The efficacy of the proposed bilinear JACE algorithm is confirmed by numerical simulations, which show that the proposed method not only significantly outperforms the state-of-the-art (SotA) but also can reach the performance of a genie-aided scheme over wide signal-to-noise-ratio (SNR) ranges, in both uniformly-random and MCPP-based sub-array activity scenarios.

We propose a novel joint activity, channel and data estimation (JACDE) scheme for multiple-input multiple-output (MIMO) systems. The contribution aims to allow significant overhead reduction of MIMO systems by enabling grant-free access, while maintaining moderate throughput per user. To that end, we extend the conventional MIMO transmission framework so as to incorporate activity detection capability without resorting to spreading informative data symbols, in contrast with related work which typically relies on signal spreading. Our method leverages a Bayesian message passing scheme based on Gaussian approximation, which jointly performs active user detection (AUD), channel estimation (CE), and multi-user detection (MUD), incorporating also a well-structured low-coherence pilot design based on frame theory, which mitigates pilot contamination, and finally complemented with a detector empowered by bilinear message passing. The efficacy of the resulting JACDE-based grant-free access scheme in the cell-free MIMO system setup compliant with fifth generation (5G) new radio (NR) orthogonal frequency-division multiplexing (OFDM) signaling is demonstrated by simulation results. The results are shown to outperform the current state-of-the-art and approach the performance of an idealized (genie-aided) scheme in which user activity and channel coefficients are perfectly known.

We consider a bidirectional in-band full-duplex (FD) multiple-input multiple-output (MIMO) system subject to imperfect channel state information (CSI), hardware distortion, and limited analog cancellation capability as well as the selfinterference (SI) power requirement at the receiver analog domain so as to avoid the saturation of low noise amplifier (LNA). A novel minimum mean square error (MMSE)-based joint design of digital precoder and combiner for SI cancellation is offered, which combines the well-known gradient projection method and non-monotonicity considered in recent machine-learning literature in order to tackle the non-convexity of the optimization problem formulated in this article. Simulation results illustrate the effectiveness of the proposed SI cancellation algorithm.

We started a new research project in the “advanced 5G” era that aims at accommodating various types of communications involving current and emerging services with different data flow-level quality requirements. In this paper, the objectives and the technical aspects of the research project are introduced. We propose an architecture based on a virtualized radio access network (vRAN) that enables adaptive control of equipment resources and location of functions in the vRAN environment in accordance with spatially and temporally changing communication demands. The seven planned research items that are essential for realizing the advanced 5G network are listed as follows: blockage prediction, new radio access technologies (RATs) and their implementations with software-defined radio (SDR), adaptive interference and resource control, integration of radio and fiber resource control, highly efficient access transmission control, adaptive placement of BS functions, and quality aware traffic pattern prediction.

We have recently proposed a massively concurrent non-orthogonal multiple access (MC-NOMA) scheme which, unlike other non-orthogonal multiple access (NOMA) schemes such as sparse-coded multiple access (SCMA) and pattern division multiple access (PDMA) that rely on sparsity, utilizes instead dense massively multiplexing with interference optimized via Frame Theory. Thanks to the properties of unit-norm tight frames (UNTFs) employed in the MC-NOMA scheme, all users can access all available resources at once but with the resulting interference collapsed and minimized, in a manner similar to that in sparsity-based NOMA. In this article we provide analytical evidence that MC-NOMA outperforms current NOMA schemes both in terms of sum-rate and spectral efficiency. To this end, we derive expressions for the achievable sum-rate and the spectral efficiency of MC-NOMA in a general context, and use the results to numerically validate the improvement potential of MC-NOMA schemes.

We address a bi-directional full-duplex (FD) multiple-input multiple-output (MIMO) system equipped with limited capability for analog self-interference cancellation (SIC) and subjected to hardware (HW) impairments and imperfect channel state information (CSI) at the nodes. We propose an alternating algorithm to minimize transmit (TX) power subject to quality of service (QoS) guarantees in such systems, where the signal to interference-plus-noise ratio (SINR) constraint is relaxed via a Fractional Programming (FP) approach so that optimal TX beamforming vectors can be obtained using standard convex optimization tools. Simulation results show that the proposed algorithm significantly reduces the required TX power while outperforms not only a conventional zero-forcing (ZF) scheme but also the State-of-the-Art (SotA) method in terms of outage probabilities of the prescribed SINRs.

In this paper, we investigate wireless-powered communication system (WPCS) with multiple frequency bands. When ambient RF signals can be used as an only energy source of wireless devices (WDs), a traditional signal-generator-based communication (SGC) might be demanding due to its high power consumption mainly because of RF-chain, so that backscatter communication (BC) has gained much attention recently. However, the bandwidth efficiency of BC is significantly limited, and thus BC is not always the best option for WPCSs. Thus, we analyze this trade-off by comparing their achievable capacity and show conditions in which the throughput of SGC is higher than BC when multiple frequency bands are available as an energy source and communication channel. Based on the analyses, we propose a hybrid approach with SGC and BC, which enables WDs to decide the best frequency band and communication method in a distributed manner.

We present a new Beamforming-based (BB) Multiple-Input Single-Output (MISO)- Non -orthogonal Multiple Access (NOMA) scheme for Power Domain NOMA (PD-NOMA), in which the total transmit power consumption is minimized subjected to prescribed signal-to-interference-plus-noise ratio (SINR) requirements for each user, and under the assumption that only imperfect channel state information (CSI) is available at the transmitter. To this end, the fractional programming (FP)-based quadratic transform is employed to reformulate the non-convex SINR constraint of the original problem into a tractable quadratic form, which contains an estimate of the CSI error vector as a parameter. Taking advantage of the fact that the zero duality gap holds for the non-convex quadratic problems, a closed-form expression for an estimate of the CSI error vector is derived, completing the formulation. Finally, a novel iterative algorithm based on both the herein derived CSI error vector and the semidefinite relaxation (SDR) technique is contributed, which is shown to capable of efficiently solving the constrained min-power problem. Simulation results are given which illustrate the effectiveness of the proposed algorithm, which is found to sacrifice only small quantities of transmit power in return for substantial increase in robustness against CSI imperfection.

State-constrained signal codes directly encode modulation signals using signal processing filters, the coefficients of which are constrained over the rings of formal power series. Although the performance of signal codes is defined by these signal filters, optimal filters must be found by brute-force search in terms of the symbol error rate because the asymptotic behavior with different filters has not been investigated. Moreover, the computational complexity of the conventional BCJR used in the decoder increases exponentially, as the number of output constellations increases. We hence propose a new class of state-constrained signal codes called repeat-accumulate signal codes (RASCs). To analyze the asymptotic behavior of these codes, we employ Monte Carlo density evolution (MC-DE). As a result, the optimum filters can be efficiently found for the given parameters of the encoder. We also introduce a low-complexity decoding algorithm for RASCs called the extended min-sum (EMS) decoder. The MC-DE analysis shows that the difference between the noise thresholds of RASC and the Shannon limit is within 0.8 dB. The simulation results moreover show that the EMS decoder can reduce the computational complexity to less than 25% of that of conventional decoder without degrading the performance by more than 1 dB.

In this paper, we propose a practical protocol named asynchronous dissemination protocol based on distributed coding (ADDC) as green and reliable information delivery protocol for sensor-to-vehicle communications. In ADDC, packets are shared among sensors and transmitted through Luby-Transform (LT) codes after the transmission of beacon signal and short-period reception to find new packet in the network. Numerical results show that ADDC achieves higher energy efficiency than the conventional cluster-based protocol.

This paper focuses on asynchronous receiver-initiated medium access control (MAC) protocol and improving the protocol to reliably work only with energy harvesting power supply. Our proposed protocol named energy-neutral receiver-initiated MAC (ENRI-MAC) enables every sensor to autonomously decide its own intermittent interval based on both the available energy from the energy harvester and the number of communicable sensors. To implement the protocol, we design a feasible circuit outputting power-good (PG) signal when the available energy from energy harvester exceeds the given threshold. We implement our protocol using Lazurite 920J which is an Arduino-compatible board and show that the device with the proposed protocol can operate even if harvested energy fluctuates.

In this paper, we propose an energy-neutral receiver-initiated medium access control (ENRI-MAC) protocol which enables every sensor to autonomously adapt its own duty cycle based on available energy from an attached harvester and the number of sensors in the coverage. This autonomous adaptation suppresses exhaustion of available energy and thus decreases the resulting packet loss rate. To realize the protocol, we further design a feasible circuit outputting power-good (PG) signal when available energy is abundant. We implement ENRI-MAC using Lazurite Sub-GHz which is an off-the-shelf Arduino-compatible board, and both computer simulations and experimental results confirm that ENRI-MAC has advantages over conventional receiver-driven MAC protocols.

Herein, we consider the problem of cooperative multi-access in the presence of overlapped coverage areas. Assuming a frameless ALOHA transmission scheme, we derive exact analytical throughput expressions for throughput in the aforementioned scenarios as a function of the frame length of the system and for arbitrary average numbers of users transmitting in each slot (target degree). After obtaining these original expressions, we then formulate a utility function whose maximization (obtained, e.g., through genetic algorithms) yields unequal and optimum target degrees to be employed by users in each group in order to maximize the peak throughput of the whole system while satisfying a given prescribed outage. A comparison of the resulting cooperative multiple base station (BS) multi-access scheme against optimized single-BS frameless ALOHA systems-which presume the perfect isolation of users at each BS and an equal optimum target degree for all users-indicates a significant gain in overall throughput, thereby revealing that a “multi-access diversity gain” can be reaped by allowing groups of users from different BSs to overlap.

In this paper, we propose a new cooperative protocol called multi- dimensional spatially-coupled repeat-accumulate coded cooperation (MD-SC-RA-CC), which is even more robust against burst errors over block Rayleigh fading channels. Our approach utilizes both time- and user-domain to transmit every packets over as many statistically independent channels as possible. To this end, we investigate the design of multi-dimensional spatially-coupled repeat-accumulate codes for MD-RA-CC, which has few short loops in the corresponding protograph. Numerical results confirm that our proposed MD-SC-RA-CC exhibits the superior decoding performance to conventional coded cooperation especially at high signal-to-noise power ratio (SNR) region.

We consider the relay selection problem in large-scale energy harvesting (EH) networks. It is known that if channel state information (CSI) is available at EH relays, a diversity order equal to the number of relays can be obtained, however, at the penalty of a feedback overhead (necessary to obtain accurate CSI) which is not suitable for energy-limited devices intended, e.g., for Internet-of-Things applications. In this paper, we therefore propose a new EH relay selection scheme which is based on the residual energy at each relay's battery, and on information on the distribution of the channels between relays and the destination. The method thus minimizes both the outage probability and the feedback cost. Where previous work relay selection based on channel distribution information consider only small-scale fading distribution, we employ a stochastic geometry approach to consider jointly the geometrical distribution (i.e., large-scale fading) and small-scale fading yielding a simple relay selection criterion that furthermore utilizes only rough information on the relay's location, i.e., an ordinal number from the destination. The outage probability of the proposed relay selection scheme is analytically derived, and the achievable diversity order of the proposed approach is investigated. Computer simulations confirm our theoretical analyses and show that our approach is robust against errors in the estimation of the distances between nodes.

This paper studies a decentralized power allocation for uplink random access of secondary users in cognitive network with successive interference cancellation. First, for the additive white Gaussian noise channel, we propose a novel algorithm, which enables to obtain discrete power levels and optimize the corresponding probabilities, iterating per-level from the lowest power level to the highest one. Under a fading environment, we further propose an opportunistic transmission protocol to reduce the interference temperature at the primary base station, by allocating powers only to the secondary users who will result in small interference. The proposed algorithms are verified via computer simulations.

In this paper, a new coded cooperation scheme called spatially coupled repeat-accumulate coded cooperation (SC-RA-CC) is proposed for multiple access channels (MAC) with a large number of users and one common destination. The proposed approach combines two advantages of repeat-accumulate (RA) codes and spatial coupling. RA codes show the superior decoding performance with the simple encoding and spatial coupling exhibits the so-called threshold saturation behavior; the threshold of coupled codes with sub-optimal belief propagation (BP) decoding asymptotically achieves the optimal maximum a posterior (MAP) decoding threshold. Our SC-RA-CC can be considered as the distributed version of spatially coupled repeat-accumulate codes which provide the higher spatial diversity and coding gain when both the number of users and the size of packets are limited. The performance of the proposed coded cooperation is analyzed via density evolution (DE). Numerical results confirm that SC-RA-CC can efficiently obtain even higher diversity and coding gain than both direct transmission and conventional adaptive network coded cooperation (ANCC).

Conventional Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) multi-hop transmission suffers severely from intra-flow interference (IFI) in dense traffic, due to the hidden terminal (HT) problem. We propose a non-CSMA/CA multi-hop transmission scheme with IFI-canceler (IFIC) that can efficiently relay packets under high traffic loads in fading environments. This interference cancellation technique employs adaptive equalization with a normalized least mean square (NLMS) algorithm for channel estimation and has good BER/PER performance under a wide range of SNR and SIR conditions. It is also capable of canceling multiple interference sources. A multi-hop packet transmission frame format dedicated to the IFIC proposal is designed. An analysis model is created that considers possible outage events in multi-hop traffic flows. Simulations of multi-hop transmission indicate that IFIC throughput under slow Rayleigh fading linearly increases with traffic load and is 3.5 times higher than that of current CSMA/CA systems at the highest normalized traffic load. When 2-branch maximal-ratio combining (MRC) reception is added after IC, the throughput is further improved to a level very close to the theoretical maximum for additive white Gaussian noise (AWGN) channels. We also assess the impact of maximum Doppler frequency, and show that the best performance is maintained if the frequency is less than 10 Hz and the performance under higher Doppler frequencies can be effectively improved by retransmission.

Multi-hop wireless ad hoc networks suffer from severe link error due to fading. In order to tailor multi-hop transmissions to fading environment and improve reliability, dynamic multi-hopping schemes have been proposed. In this paper, we theoretically analyze the end-to-end packet delivery rate performance of integrated dynamic multi-hopping (IDMH) scheme under the generalized fading model combining the effect of Rayleigh fading and log-normal shadowing, i.e., Suzuki fading model. Results show that packet delivery rate is remarkably improved by the IDMH scheme. Furthermore, numerical results via network simulator justify the accuracy of the theoretical analysis.

This paper reveals an impairment of well-known path-loss model generally assumed in conventional works with radio frequency (RF) energy harvesting. We will prove that, when RF energy harvesting is considered in a large-scale network, the summation of energy transferred to nodes in the network diverges while the radiated energy must be finite. Thus, we propose a new absorption function meeting this law and derive several expressions of average harvested energy based on the model. Furthermore, the effectiveness of RF energy harvesting with Poisson point process (PPP) network with a single transmitter is demonstrated.

In this paper, we propose a radio-frequency (RF) energy powered cooperative transmission using RF energy harvesting which scavenges the energy from ambient radio waves. The outage probability of this system is theoretically analyzed to show the advantageous region compared with the direct transmission without RF energy harvesting relay when amplify-and-forward (AF) and decode-and-forward (DF) relaying are employed. Moreover, if the source can get the information about the residual battery and decoding results of the relay, the source can recognize the availability of relay and resources. Thus, we propose feedback-aided cooperation with RF energy harvesting, which can exploit all the available resources in the network, and show that utilizing the explicit or implicit feedback information significantly improves the overall performance.

In this paper, we focus on a X channel; a system with two transmitters and two receivers each equipped with a single antenna, where independent messages need to be conveyed over channels from each transmitter to each receiver. A key concept of that arises in the context of the X channel is interference alignment (IA) that refers to an overlap of signal spaces occupied by undesired interference at each receiver while keeping desired signal spaces distinct. However, all the channel responses and the precise time synchronization are required at every transmitter and receiver to realize the IA, which are seriously demanding in practice. In this paper, we propose semi-blind IA (S-BIA) scheme exploiting frequency selectivity of wireless channels using orthogonal frequency division multiplexing (OFDM), which only requires channel responses corresponding to each transmitter. Numerical results confirm that proposed S-BIA can achieve the same degrees of freedom as conventional IA even in the presence of time synchronization errors.

In this paper, we propose a bandwidth efficient distributed network code, termed superimposed adaptive network coded cooperation (SANCC), for a network consisting of M users sending different information packets to a common destination through independent block fading channels. Different from conventional cooperative communications with half-duplex constraint, our proposed approach does not reduce the bandwidth efficiency with the aid of high order modulation while its encoding process is still performed by simple XOR operation similar to the conventional adaptive network coded cooperation (ANCC). In order to exploit the structure of the proposed approach, effective mapping and corresponding decoding are investigated. We further propose a modified encoding for SANCC to improve the inherent error floor behavior and analyze its performance based on extrinsic information transfer (EXIT) chart. Finally, the effectiveness of our proposed approach is confirmed via computer simulations.

In this paper, we propose a new simple relaying strategy based on bit-interleaved convolutionally coded star-quadrature amplitude modulation (QAM) along with coherent/noncoherent detection. Star-QAM is composed of multiple concentric circles of phase-shift keying (PSK). Exploiting this property, a hard limiter is used to enhance power amplifier (PA) efficiency at the relay. Moreover, we show that the proposed approach retains differential detectability, which results in a significant reduction of receiver complexity with robustness against phase ambiguity. By analyzing our proposed cooperation with coherent/noncoherent detection in terms of asymptotic pairwise error probability (PEP), we show that the full diversity order can be achieved on the condition that the minimum free distance of the convolutional codes is larger than the predetermined value specified by the number of available relays. Furthermore, the effectiveness of the proposed scheme in terms of PA efficiency is confirmed by comparing the statistical distributions of the corresponding instantaneous signal powers. All the theoretical results agree with those obtained by computer simulations.

In this paper, we propose a new cooperative wireless transmission in a scenario where the source salvages the energy during the relay's transmission considering the fact that the source does not need to retrieve the transmitted message. We also evaluate a direct wireless transmission with wireless energy transfer as a reference. We analyze the performance of these transmission techniques in terms of outage probability. Our analytical results reveal the advantage of energy salvage in combination with spatial diversity over the direct transmission even if the energy transfer efficiency is considerably low.

In this paper, we propose a new automatic repeat request (ARQ) scheme, named Go-Back-i-symbol (GBi) ARQ scheme, suitable to Meteor Burst Communications (MBC). The scheme realizes symbol-wise ARQ by using the Viterbi decoding algorithm for convolutional codes. We also propose a practical transmission protocol for applying the GBi-ARQ scheme to packet communications over time varying short burst channels such as meteor burst channels. Fundamental performances of the GBi-ARQ scheme in MBC are evaluated by computer simulations. Effectiveness of the GBi-ARQ scheme is shown by comparing the performance with that of a conventional block-wise ARQ scheme.

In this paper, we analyze the instantaneous power distributions of the transmitting signals at the relay in the non-regenerative and regenerative cooperation scenarios with linear modulation. We study the following four relay function scenarios: fixed gain amplify and forward (AF) relay, variable gain AF relay, estimate and forward (EF) relay, and decode and forward (DF) relay. The analytical results show that the transmitting signals from non-regenerative relaying tend to suffer from high peak power, which is even prohibitive when the power amplifier (PA) efficiency at the relay is of primary concern.

In this paper, we study the instantaneous power distributions of the transmitting signals at the relay in the non-regenerative and regenerative cooperation scenarios with linear modulation under the band-limited scenario. We study the following three relay function scenarios: fixed gain amplify and forward (AF) relay, variable gain AF relay, and decode and forward (DF) relay. Based on the analytical results, we reveal practical limitations of non-regenerative relays when the power amplifier (PA) efficiency is of primary concern.

Recently, collaborative (or cooperative) multi-hop transmissions have gained much attention since they can achieve highly reliable communication and longer life of each node simultaneously. While it is often assumed that each cluster in collaborative multi-hop transmissions has an identical number of nodes in the literature, this assumption is not reasonable since the sensor nodes are not uniformly distributed in practice. In this paper, we analyze the collaborative multi-hop transmission in non-uniformly distributed networks in terms of outage probability. Using analytical results, we provide a design guideline of the networks. We further show that the appropriately designed networks may potentially achieve the superior outage performance compared with conventional uniformly distributed networks.

This paper proposes a novel cooperative diversity protocol using multilevel coded (MLC) modulation, which aims at wireless networks composed of more than two cooperative nodes. If the time-division (TD) based cooperative diversity is applied to the case of multiple sources, its transmission efficiency decreases in proportion to the number of sources which results in the degradation of performance. Although several cooperative diversity protocols based on symbol superposition have been proposed to overcome this inherent degradation, most of them are designed for a two-node cooperation and their complexity increases exponentially with the number of cooperating nodes. To the contrary, the proposed MLC cooperation takes advantage of the simplicity of MLC structure and allows a flexible design, without exponential increase of overall complexity. We introduce two rate allocation design criteria, i.e., minimum outage probability and maximum transmission rate, and demonstrate the advantages of the MLC cooperation in terms of outage probability and frame error rate (FER) performance.

In this paper, we propose a dynamic coded cooperation using multiple turbo codes. Our proposed cooperation is able to provide the diversity gain efficiently without loss of bandwidth efficiency. Moreover, in our proposed scheme, the relay can dynamically determine if it should cooperate or not. Thus, we investigate a design of a simple power detection to estimate a precise duration of cooperation phase upon decoding information at the destination. Computer simulations show that our proposed approach is able to achieve a full diversity and superior frame error rate compared with the conventional coded cooperation based on turbo codes especially in low signal to noise ratio (SNR) regime.

In this paper, we propose a new ARQ scheme, named Go-Back-i-symbol (GBi) ARQ scheme which is suitable to Meteor Burst Communications (MBC). The scheme is based on the Viterbi decoding algorithm for convolutional codes and can achieve symbol-wise retransmission, so that it has high throughput performance for packet communication systems over time varying short burst channels such as MBC channels. We also propose a practical transmission protocol for applying the GBi-ARQ scheme to MBC systems. Comparing to a conventional block-wise ARQ scheme, the effectiveness of the proposed scheme is shown by computer simulations.

Multi-hop ad-hoc networks are promising candidates for next generation wireless communications. When using HARQ for multi-hop transmissions, each relay node has to decode received messages and request retransmission to its previous node when it detects errors. Thus, every relay node is required to spend extra power and time because of retransmissions and decodes for collaboration of transmission by the source node. We propose a new HARQ scheme that can reduce the load of the relay nodes but maintain high throughput. In this scheme, every relay node neither decodes the received messages nor requests retransmission to reduce the load. Only the destination node decodes messages by using LDPC codes. RC-LDPC codes, which are suitable for Type-II HARQ, are utilized in the proposed ARQ scheme. Throughput performance of the proposed scheme is evaluated to show its effectiveness.

We propose a novel cooperative diversity using multilevel coded modulation which can perform with arbitrary number of cooperative nodes. The proposed multilevel coded cooperation makes use of a signal superposition, which is one form of analog network coding techniques. Due to the ability and flexibility of a multilevel coded modulation, the proposed multilevel coded cooperation can outperform not only a time-division cooperative diversity but also a signal superposition cooperative diversity in the case where the number of cooperating nodes is more than two. Moreover, achievable outage probability and channel capacity are analyzed and two design criteria based on the analysis are proposed.

Multi-hop ad-hoc networks are promising candidates for next generation wireless communications. When using HARQ for multi-hop transmissions, each relay node has to decode received messages and request retransmission to its previous node when it detects errors. Thus, every relay node is required to spend extra power and time because of retransmissions and decodes for collaboration of transmission by the source node. We propose a new HARQ scheme that can reduce the load of the relay nodes but maintain high throughput. In this scheme, every relay node neither decodes the received messages nor requests retransmission to reduce the load. Only the destination node decodes messages by using LDPC codes. RC-LDPC codes, which are suitable for Type-II HARQ, are utilized in the proposed ARQ scheme. Throughput performance of the proposed scheme is evaluated to show its effectiveness.

In this paper, we propose a bandwidth efficient coded cooperation using rate compatible turbo codes. The design of rate compatible turbo codes for the proposed collaboration is investigated based on the analysis of pairwise error probability (PEP). Some numerical results show that the diversity gain can be achieved by using our proposed approach.

In this paper, the bit-interleaved convolutionally coded differential phase shift keying (DPSK) in combination with cyclic delay diversity (CDD) is theoretically analyzed in terms of pairwise error probability (PEP). We show that bit-interleaved coded DPSK with CDD can achieve full spatial and frequency diversity offered by the frequency selectivity of wireless channel conditioned that the minimum free distance dfreeof the convolutional code is larger than the target diversity order. The design criterion of the considered system is presented based on the analysis of diversity and coding gains. Finally, the theoretical results obtained in this paper are confirmed by computer simulations.

Cyclic delay diversity (CDD) exploits the principle of the orthogonal frequency division multiplexing (OFDM) that transforms the delay spread into the frequency selectivity. In order to investigate the performance of the CDD, OFDM in combination with bit-interleaved coded differential phase shift keying (DPSK) is theoretically analyzed in terms of pairwise error probability (PEP). We show that bit-interleaved coded DPSK with OFDM can achieve the full frequency diversity caused by the frequency selectivity of the wireless channel and that maximum diversity can be obtained with any kind of power delay profile (PDP), conditioned on the minimum free distance dfreeof the convolutional codes. Based on the above discussions, the bit- interleaved coded DPSK with CDD is studied. Finally, theoretical results are confirmed via computer simulations.

In order to alleviate development cost, many application-oriented wireless networks make use of the off-the- shelf wireless standards such as the Bluetooth, IEEE802.15.4 (Zigbee), and IEEE802.11, which are originally developed for personal area networks (PAN) and local area networks (LAN). Examples of such applications are medical monitoring and control. These applications do not require data rates as high as these standards, but instead they require higher reliability with lower latency. As a means to meet such requirements based on these standards, we propose an efficient error control technique named embedded forward error control technique (EFECT). This technique enables an additional forward error correction to the existing standards without any additional costs. Some design guidelines based on Reed-Solomon (RS) codes are proposed and, as a specific example, achievable gains by applying the EFECT are studied for the Bluetooth standard.

In order to alleviate development cost, many application-oriented wireless networks make use of the off-the- shelf wireless standards such as the Bluetooth, IEEE802.15.4 (Zigbee), and IEEE802.11, which are originally developed for personal area networks (PAN) and local area networks (LAN). Examples of such applications are medical monitoring and control. These applications do not require data rates as high as these standards, but instead they require higher reliability with lower latency. As a means to meet such requirements based on these standards, we propose an efficient error control technique named Embedded Forward Error Control Technique (EFECT). This technique enables an additional forward error correction to the existing standards without any additional costs. Some design guidelines based on Reed-Solomon (RS) codes and sphere packing bound are proposed and, as a specific example, achievable gains by applying the EFECT are studied for the Bluetooth standard.

In this paper, Tomlinson-Harashima precoding with differential detection for MIMO communications is proposed. It is shown that our proposed nonlinear preequalization with differential detection can achieve space division multiplexing and significant robustness compared with coherent detection even with carrier tracking error.

In this paper, we propose a low complexity bit-interleaved coded DAPSK in combination with cyclic delay diversity, which transmits delayed replicas of an orthogonal frequency division multiplexing (OFDM) signal in cyclic manner and thereby enjoys full diversity without loss of bandwidth efficiency. Here, the frequency diversity induced by delayed replicas can be exploited by a subsequent channel decoder. The performance of the proposed system is evaluated over frequency selective block Rayleigh fading channels. We also show that our proposed system is robust against the blockage effect caused by some obstacles.

In this paper, cognitive radio technology is considered, which has gained much attention around the world. The coexistence between decentralized cognitive radio and primary radio systems is focused. Specifically, by introducing two benchmarks, the network performance without and with cognitive radio technology with the function of detecting radio signals to avoid the primary radio system is studied. From these results, it is shown that cognitive radio can avoid interference. However, according to the condition, cognitive radio cannot get the opportunity of communication. Therefore, an additional function for the sake of avoiding an unavailable arbitrary spectrum band is proposed. Moreover, we show that cognitive radio technology cannot avoid the interference to primary systems whenever hidden primary terminals exist in the network.

In this paper, the performance of low-density parity-check (LDPC) codes with differential detection is studied over additive white Gaussian noise (AWGN) and Rayleigh fading channels with particular emphasis on the sensitivity of signal-to-noise ratio (SNR) parameters required for metric calculation. Two simple metrics are derived and compared. Computer simulation results demonstrate that an SNR mismatch has a considerable effect on the performance of LDPC codes, and optimal SNR mismatches are explored in terms of bit error rate performances. It is shown that in some cases a pessimistic SNR estimation can improve the overall performance.

We analyze the achievable performance of bit-interleaved coded differential amplitude and phase-shift keying (DAPSK) systems over frequency nonselective Rayleigh-fading channels with suboptimal differential detection assuming an ideal bit interleaving. The suboptimal differential detection in this work refers to the bit metric calculation based only on the difference between two consecutive symbols, in contrast to more complex maximum-likelihood (ML)-based differential detection, which makes use of all the observed consecutive symbols for its metric calculation in channel decoding. As benchmarks of coded system performance, we analyze the average mutual information (AMI) and cutoff rate of this system. Exact probability density functions of the suboptimal differential detector outputs are derived for this purpose. Comparative studies suggest that the performance loss of the suboptimal approach is in fact noticeable. Therefore, we also develop a low-complexity receiver structure in the framework of suboptimal differential detection that can approach the performance of ML-based system by suitably incorporating the amplitude statistics of received symbols. The theoretical framework developed in this paper is also confirmed by simulations using convolutional and turbo codes.

We analyze the achievable performance of the coded differential amplitude and phase shift keying (DAPSK) over a frequency non-selective Rayleigh fading channel with ideal bit interleaving. The bit metrics based on the exact probability density of detector output and the average mutual information of the system with conventional differential detection are derived and compared with that of multiple-symbol differential detection (MSDD). It is shown that by suitably incorporating the amplitude statistics of transmitted signals into bit metrics, the performance of conventional DAPSK can be significantly improved without increasing complexity. Theoretical framework developed above is also justified by the comparative simulation results using convolutional and turbo codes.