Tokens are fundamental processing units of generative AI (GenAI) and large language models (LLMs), and token communication (TC) is essential for enabling remote AI-generate content (AIGC) and wireless LLM applications. Unlike traditional bits, each of which is independently treated, the semantics of each token depends on its surrounding context tokens. This inter-token dependency makes TC vulnerable to outage channels, where the loss of a single token can significantly distort the original message semantics. Motivated by this, this paper focuses on optimizing token packetization to maximize the average token similarity (ATS) between the original and received token messages under outage channels. Due to inter-token dependency, this token grouping problem is combinatorial, with complexity growing exponentially with message length. To address this, we propose a novel framework of semantic packet aggregation with lookahead search (SemPA-Look), built on two core ideas. First, it introduces the residual semantic score (RSS) as a token-level surrogate for the message-level ATS, allowing robust semantic preservation even when a certain token packet is lost. Second, instead of full search, SemPA-Look applies a lookahead search-inspired algorithm that samples intra-packet token candidates without replacement (fixed depth), conditioned on inter-packet token candidates sampled with replacement (fixed width), thereby achieving linear complexity. Experiments on a remote AIGC task with the MS-COCO dataset (text captioned images) demonstrate that SemPA-Look achieves high ATS and LPIPS scores comparable to exhaustive search, while reducing computational complexity by up to 40$\times$. Compared to other linear-complexity algorithms such as the genetic algorithm (GA), SemPA-Look achieves 10$\times$ lower complexity, demonstrating its practicality for remote AIGC and other TC applications.

Text-based communication is expected to be prevalent in 6G applications such as wireless AI-generated content (AIGC). Motivated by this, this paper addresses the challenges of transmitting text prompts over erasure channels for a text-to-image AIGC task by developing the semantic segmentation and repeated transmission (SMART) algorithm. SMART groups words in text prompts into packets, prioritizing the task-specific significance of semantics within these packets, and optimizes the number of repeated transmissions. Simulation results show that SMART achieves higher similarities in received texts and generated images compared to a character-level packetization baseline, while reducing computing latency by orders of magnitude compared to an exhaustive search baseline.

Cell-free multiple-input-multiple-output (MIMO) is poised to enable scalable next-generation cellular networks. To this end, it is crucial to optimize the cell-free MIMO link configuration, including user associations, data stream allocation, and beamforming (BF). However, the scalability of link configuration optimization is significantly challenged as signaling and computational costs increase with the number of base stations (BSs) and user equipments (UEs). To address this scalability issue, this paper proposes a distributed multi-agent deep reinforcement learning (MADRL)-based cell-free MIMO link configuration framework that leverages interference approximation to minimize signaling overhead required for channel state information (CSI) exchange. Our proposed framework reduces the solution search space suitable for distributed MADRL, by decomposing the original sum rate maximization problem into BS-specific tasks. Simulation results show that our proposed method achieves scalability, as the sum rate increases with the number of BSs and UEs.

Integrated localization and communication (ILC) will be a key enabler for providing accurate location information and high data rate in next generation networks. This paper proposes a transmission frame structure and a soft information (SI)-based localization algorithm for position-assisted communications. The proposed ILC achieves improved localization accuracy and enhanced communication rate simultaneously by accounting for the statistical characteristics of the wireless environment. Results in 3rd Generation Partnership Project (3GPP) industrial scenarios show that the SI-based localization algorithm can achieve decimeter-level accuracy. Moreover, the position-assisted communication enhances the achievable rate, especially in scenarios with high mobility.

In this paper, we study a wirelessly-powered communication network (WPCN) composed of several wireless devices (WDs) which rely on an energy access point (EAP) for their supply of energy which is used to transfer data to a data access point (DAP). While the dominant focus of the literature in this area has been on frame-based data rate optimization, it has been known that this approach is greedy and only optimal in additive white Gaussian noise (AWGN) channels. Hence, in this work, we propose an online algorithm that, based on the current state of the batteries and channels, adaptively calculates the transmission time and power allocations to maximize the long-term performance of this system in fading channels. In order to accomplish such a goal, we employ the Twin Delayed DDPG (TD3) approach, which is a deep reinforcement learning (DRL) technique designed for continuous state and action spaces. Additionally, we use the multi-task learning (MTL) techniques to train a DRL agent that creates a composite policy capable of dynamically optimizing not just one specific WPCN configuration, but a continuum of WPCN problems, which we call a composite environment. Each of these environments has different parameters such as WDs’ distances to the DAP and EAP, batteries’ size, rectifying antenna (rectenna) energy harvesting (EH) model linearity, as well as different uplink (UL) and downlink (DL) channel specular components. Simulation results confirm that the TD3 algorithm can easily learn to achieve a much higher common throughput compared to the traditional optimization schemes.

In this paper, we design a network utilizing a wirelessly-powered relay (WPR) to simultaneously receive power and information from an access point (AP) and forward the information to a distant wireless device (WD) that cannot receive information directly from the AP. The WPR is equipped with a finite battery and a data buffer and using the saved energy re-transmits the AP’s data to the WD in a decode-and-forward (DF) manner. The objective is to completely deliver a variable-sized data packet to the WD while minimizing the total energy consumption of the AP within a defined time frame composed of multiple slots. Using deep reinforcement learning (DRL) methods, we devise an algorithm to train a proximal policy optimization (PPO) agent that optimizes the time and power allocation as well as data transfer rates of the AP and WPR in this problem. The simulation results show that the proposed approach can efficiently optimize the network to guarantee delivering the complete data packet. Moreover, the energy consumption of the proposed technique is much lower than the optimal greedy algorithm which occasionally fails to deliver the data packet due to deep channel fades.

Integrated sensing and communication (ISAC) is a promising technology for next-generation communication systems, allowing concurrent data communication and positioning. However, in the presence of blockages, ISAC does not guarantee accurate positioning due to the lack of echo signals from targets. To address this issue, we study a downlink ISAC system with an unmanned aerial vehicle (UAV) relay that decode-and-forward data signals while securing blockage-free paths. In this UAV-assisted downlink ISAC system, we aim to maximize the sum rate while ensuring a target positioning accuracy by optimizing transmit power allocation. With moving target objects in a three-dimensional (3D) environment, this optimization problem becomes non-trivial due to complicated object positioning state transitions. To relax this complexity, we derive an approximated state transition model of 3D object and thereby formulate a strictly convex optimization problem that guarantees a unique power allocation solution. Numerical results corroborate that the proposed power allocation outperforms the baseline with feedback-based beam training in terms of the achievable sum rate.

In this paper, we propose a new beamforming design method to address the effect of beam squint in Terahertz communication. Conventional schemes for mitigating the beam squint have encountered challenges, such as high power consumption due to additional complex hardware or impractical computational complexity. To overcome the limitations, we propose a new analog beamforming technique, which does not require not only a high computational complexity but also additional hardware. Specifically, our proposed scheme performs analog beamforming at symmetrically shifted frequencies using a variable ϵ to create a robust wide beamformer in frequency domain, thereby minimizing the distortion of the array gain throughout the entire bandwidth. Furthermore, the value of ϵ is expressed in a closed form based on the lower bound of achievable spectral efficiency. Our simulation results show that the proposed scheme outperforms conventional hybrid beamformer and other techniques to deal with the beam squint.

Integrated localization and communication (ILC) at millimeter wave (mmWave MMWAVEinit) frequencies will be a key enabler for providing accurate location information and high data rate communication in beyond fifth generation (B5G) networks. This paper proposes a transmission frame structure and a soft information (SI)-based localization algorithm for position-assisted communications. In accordance with B5G specifications, we consider multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) networks. Theoretical limits are also derived to serve both as performance benchmark and as input for algorithm design. The proposed method enables cooperative ILC with improved localization accuracy and enhanced communication rate simultaneously. In particular, position-assisted communication at mmWave MMWAVEinit frequencies is explored accounting for the statistical characteristics of the wireless environment. Localization accuracy and communication rate are quantified in 3rd Generation Partnership Project (3GPP) network scenarios. Results show that the SI-based localization algorithm achieves decimeter-level accuracy, approaching the theoretical limit. Moreover, the position-assisted communication can provide higher communication rate with reduced overhead compared to existing techniques, especially in scenarios with high mobility.

Multi-numerology systems are considered to be promising communication frameworks in 5G new radio (NR) due to their flexibility. However, inter-numerology interference (inter-NI) degrades the quality of communication systems. Hence, techniques for mitigating inter-NI are needed to support multiple numerologies. In particular, the effect of the inter-NI should be considered in channel estimation process. We propose a pilot design which requires relatively short training overhead and mitigates the inter-NI. We stress that inter-NI does not exist in most cases when the proposed pilot signal is used. With taking account of the special case where inter-NI exists, we develop the channel estimation algorithm based on inter-NI cancellation. In addition, we analyze the effect of inter-NI cancellation algorithm which not only eliminates interference but also reduces the variance of noise. The simulation results verify that the performance of channel estimation with the proposed pilot signal is better than the quality of estimation with the case where user equipments transmit their pilot signals in a time division manner.

In this paper, we consider an intelligent reflecting surface (IRS)-aided wireless power transfer (WPT) system in multipath channel environments. The IRS can configure a favorable wireless propagation environment for the WPT by shifting the phases of the incident signals using passive reflecting elements. To improve energy transfer performance using the IRS, a joint design of the transmitter and the IRS is crucial. In this paper, we maximize harvested energy at an energy receiver with a non-linear energy harvester (EH) by jointly optimizing the transmit waveform and the IRS reflection coefficients. We first formulate an optimization problem for the system as non-convex due to the coupling of the optimization variables. To handle the non-convexity of the problem, we adopt an assumption based on the non-linear energy conversion characteristic of the EH and propose the suboptimal solution. As a result, a time-reversal (TR) waveform and reflection coefficients obtained by singular value decomposition (SVD) are derived as the solution. Furthermore, a performance analysis and simulation results are provided to verify the effectiveness of the proposed system showing considerable enhancement on harvested energy over the non IRS-aided system.

In this article, orthogonal frequency-division multiplexing (OFDM)-based downlink simultaneous wireless information and power transfer (SWIPT) is considered in the Internet of Things (IoT) wireless interference network, where one hybrid access point (HAP) performs both wireless power transfer (WPT) and wireless information transfer (WIT) to energy harvesting (EH) and information decoding (ID) nodes while multiple coexisting energy access points (EAPs) carry energy to EH nodes. As the transmission methodology for interference avoidance, we improve and refine the subcarrier separation (SS), which allocates the dedicated energy subcarrier set orthogonal to the information subcarrier set. Based on the modified SS, to enhance the harvested energy while minimizing the number of dedicated energy subcarriers, we design the cooperative WPT with transmit diversity and adopt the time-division multiple access scheme for multiple EH nodes. The optimal joint subcarrier, node, and power allocation problem is formulated based on the proposed transmission strategies to maximize the achievable sum rate for given energy requirement with a practical nonlinear EH model for low-power IoT nodes. However, it is difficult to obtain the global optimal solution due to the nonconvexity of the problem, so we investigate the cooperative resource allocation scheme. First, to solve the subcarrier allocation and node selection jointly, two basic methods for maximizing energy and minimizing rate loss are designed, and the additional scheme considering both energy requirement and rate-loss minimization is proposed by introducing a weighting factor for balancing the total transmit power into WPT and WIT. Then, the optimal power allocation on the allocated subcarriers and selected nodes is performed with the split transmit power. Simulation results show that the proposed schemes achieve superior rate–energy (R-E) region to conventional schemes. Our study provides useful insights on how to transmit signals for improving performance in IoT interference networks with SWIPT.

This article studies a multiuser multiple-input-single-output (MU-MISO) Internet-of-Things (IoT) network powered by wireless power transfer (WPT). The network consists of one hybrid data-and-energy access point (HAP) having multiple antennas and several single-antenna IoT nodes. The HAP coordinates energy/information transfer to/from the nodes in the downlink (DL)/uplink (UL) using frequency-division duplexing (FDD). On the one hand, in order for WPT to effectively harness the potential of multiple antennas, it requires such techniques as energy beamforming (EB). On the other hand, efficient EB can only be achieved if channel state information (CSI) is available to the transmitter, which, in FDD systems, can be accomplished through UL feedback. Therefore, the UL channel frames are split into two phases in our scheme: 1) the CSI feedback phase during which the IoT nodes feed CSI back to the HAP and 2) the wireless information transmission (WIT) phase where the HAP performs WIT. To ensure rate fairness among the IoT nodes, we maximize the minimum expected WIT data rate among the nodes. This problem is nonconvex and thus difficult to solve optimally. To tackle this challenge, we decouple the original optimization problem into tractable subproblems and solve them in an alternative manner. Finally, we analyze the behavior of this system when the number of HAP antennas increases. Simulation results corroborate the accuracy of our analysis.

This article considers a one-way decode-and-forward (DF) relay-based Internet-of-Things (IoT) network consisting of a source, a relay, and a destination in wireless energy harvesting (EH) and information transmission (IT) using the time switching-based relaying (TSR) protocol. The one-way DF relay network using the TSR protocol consists of some time slots. This article proposes the time allocation scheme for maximizing the achievable data rate under the total block time constraint. It is assumed that the relay is considered the IoT device used for long periods of time without battery replacement and it is equipped with both nonrechargeable and rechargeable batteries. Based on the supplied power by the nonrechargeable battery, the proposed scheme determines whether or not to harvest energy and operates two alternate time allocation schemes. Since the proposed scheme is based on the closed-form expressions, it provides low complexity. Numerical results show that the achievable data rate of the proposed time allocation scheme is greater than that of the fixed time allocation scheme.

The high power consumption of analog-to-digital converters (ADCs) with high resolution is a bottleneck in the high data rate communication systems. 1-bit ADC system is considered a key communication system resolving the issue. Recently, 1-bit ADC system with time-oversampling has been studied because the additional information leads to increase in the achievable rate. A variety of studies have been carried out to enhance the data rate of the system with 1-bit ADC and time-oversampling assuming the channel is known. On one side, the channel estimation in a such system is a challenging issue. We design the pilot sequence and maximum likelihood (ML) estimator to evaluate the channel phase which is a critical parameter in 1-bit ADC system. By taking account of the distribution of channel power gain in flat Rayleigh fading channel indirectly, the estimator operates in the absence of channel power gain information, which is hard to obtain due to the nonlinearity of 1-bit ADC. The simulation results demonstrate the effectiveness of the proposed scheme in terms of mean squared error (MSE) with reasonably short pilot sequence. Specifically, the MSE performance does not show error floor regardless of the prior knowledge of the channel power gain at the receiver.

Wireless communication in millimeter wave frequency provides a high data rate using a wide bandwidth. However, the large array antenna is necessary to overcome the high path loss, which may result in the high feedback overhead and hardware complexity. Moreover, the characteristics of frequency selective channel should be considered due to the wide bandwidth. To deal with these problems, we propose the orthogonal frequency division modulation (OFDM)-based hybrid beamforming (HBF) scheme with limited feedback. While the conventional OFDM-based HBF schemes are based on minimizing the sum of the Frobenius norm of the differences between digital BF (DBF) and HBF as simple extension of the narrowband systems, our approach is based on the achievable sum rate maximization of all the subcarriers. In particualr, we derive a design criterion to jointly optimize the HBF matrices of the transmitter and receiver. Specifically, we propose a HBF method which designs subchannel gain product based orthogonal matching pursuit. Through this, an analog BF algorithm considering both the transitter and receiver is proposed, while the baseband BF is based on the conventional digital precoding scheme. Simulation results show that the proposed HBF scheme outperforms the conventional ones. Notably, the results show that the proposed HBF scheme is robust to channel estimation error.

A major bottleneck in millimeter wave hybrid beamforming (BF) system is the limited number of radio frequency (RF) chains at the base station (BS). For example, when the number of users is large, the joint user scheduling and BF design is needed under the hardware constraint. Fortunately, if multiple RF chains are available at both BS and users, the system performance can significantly be improved by multi-mode transmission, which assigns different numbers of streams to the users. However, the optimal multi-mode scheme may require high feedback-feedforward overhead and complexity. Furthermore, since the mmWave BF system operates in a large bandwidth, the wideband channel should be considered. To tackle this problem, we propose the single-carrier (SC) hybrid BF scheme based on the limited feedback information. We maximize the weighted sum rate by adopting the multi-mode transmission based on the RF beam alignment. The proposed SC hybrid BF scheme outperforms the existing orthogonal frequency division multiplexing (OFDM)-based hybrid BF schemes. From the analysis, we find that full spatial multiplexing gain is guaranteed if we scale the number of RF chains at the BS as smaller than the square root of the number of antennas in a large number of users regime.

In this paper, we compare I/Q imbalance compensation schemes for massive multi-input multi-output (MIMO) system in presence of I/Q imbalance at both transmitter and receiver. Transceiver I/Q imbalance can be compensated jointly by the base station or separately by both base station and user terminals. We show that the achievable sum rate of self-compensation scheme which compensates its I/Q imbalance separately is severely deteriorated in presence of channel estimation error and the I/Q imbalance parameter estimation error. In contrast, the achievable sum rate of the joint compensation scheme with RZF precoding in the base station shows robust performance against channel estimation error and the I/Q imbalance parameter estimation error.

In this paper, we propose a method for designing an optimal filter for QAM-FBMC system in the presence of the residual CFO. We model the QAM-FBMC system with residual CFO, and describe the optimization conditions for the prototype filter design. By using these criteria, we formulate the prototype filter design problem for the QAM-FBMC system with the residual CFO, and present the designed filter coefficients. Finally, simulation results show the performance comparison of the proposed prototype filters, and we confirm that the designed filters have the performances of the design intents.

Millimeter wave (mmWave) wireless communication systems suffer from high path loss compared to conventional cellular communication systems. Angle of arrival (AoA) of received signal is prerequisite for beamforming technique to overcome high path loss in mmWave communications. Considering mobile environments, conventional beam estimation methods with large overhead are unacceptable for rapidly varying AoA. Therefore, beam tracking algorithm with low complexity corresponding to rapidly varying AoA is required. This paper studies on beam tracking algorithm for mmWave MIMO systems in mobile environments. We define the AoA model, and propose beam tracking algorithm using auxiliary beam pair (ABP) and extended Kalman filter (EKF). The simulation results show that proposed algorithm has better beam tracking performance than the existing methods in low signal to noise ratio (SNR) region.

With demand for high speed wireless communication system in 5G, using 1-bit analog-to-digital converter (ADC) at the receiver is considered to be a promising architecture. Several studies have been proposed to maximize the achievable data rate employing time-oversampling with 1-bit ADC. However, there remains problems on the minimally required oversampling factor in general case and how to design the communication system practically. This paper provides the minimum oversampling factor for pulse amplitude modulation (PAM) in additive white Gaussian noise channel and proposes the mapper- demapper architecture. The mapper converts symbols into predefined classes, and constructs the unique symbol sequence based on state machine. For demapper algorithm, the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm is implemented. Simulation results demonstrate that the proposed algorithms work well in terms of symbol-error-rate and detecting failure probability at high signal-to-noise ratio region.

In this paper, we propose a CRC-aided soft-output (CASO) detection for uplink multi-user multiple-input multiple-output systems with one-bit ADCs to improve the error rate while maintaining low latency. After CRC checking, the CASO detection constructs a refined subcode of a spatial-domain code by exploiting successfully decoded messages from the previous iteration. Based on the refined subcode, more reliable soft messages can be extracted to utilize in the rest decoding process. Since multiple messages can be successfully canceled with the aid of CRC checking, the CASO detection can prevent error propagation and suppress increment of latency. Simulation results demonstrate that the CASO detection can provide improved error rate compared to the conventional detections though increment of latency is insignificant for high SNR.

As millimeter wave (mmWave) beamforming (BF) system can increase the areal capacity in ultra-dense network (UDN), a joint design of user association and hybrid BF is challenging due to the high feedback overhead and complicated interference management where many communication nodes use large antenna arrays. In addition, the wireless backhaul should be incorporated because it allows a flexible design, while the wired backhaul is difficult to be installed as the number of small base stations increases. To integrate the wireless backhaul and access, the time resource partitioning between the backhaul and access transmissions is needed, which affects the network performance combined with the user association and BF design. In this regard, this paper deals with the joint problem of the time resource allocation, user association, and BF design to maximize the weighted sum rate. Then a two-stage design approach is proposed based on the limited channel feedback to reduce the complexity and overhead. Simulation results show that the proposed limited feedback hybrid BF scheme outperforms the baseline schemes. In addition, we find that the maximum spatial multiplexing gain can be achieved if the number of antennas of each node increases with an order of larger than the square of the number of RF chains. At the same time, the multi-node diversity gain can be obtained in mmWave UDN, which depends on the path loss exponent of line-of-sight.

This paper considers a single-antenna wireless- powered communication network (WPCN) over a flat- fading channel. We show that, by using our probabilistic harvest-and-transmit (PHAT) strategy, which requires the knowledge of instantaneous full channel state information (CSI) and fading probability distribution, the ergodic throughput of this system may be greatly increased relative to that achieved by the harvest-then- transmit (HTT) protocol. To do so, instead of dividing every frame to the uplink (UL) and downlink (DL), the channel is allocated to the UL wireless information transmission (WIT) and DL wireless power transfer (WPT) based on the estimated channel power gain. In other words, based on the fading probability distribution, we will derive some thresholds that determine the association of a frame to the DL WPT or UL WIT. More specifically, if the channel gain falls below or goes over these thresholds, the channel will be allocated to WPT or WIT. Simulation results verify the performance of our proposed scheme.

Simultaneous wireless information and power transfer (SWIPT) is a promising technology to transmit both power and information for diverse internet of things (IoT) devices. Indoor communication suffers from the inter symbol interference (ISI) due to multipath propagation, and thus the signal transmission deteriorates achievable rate. Time-reversal (TR) achieves the high received signal power and the signal-to-interference plus noise ratio (SINR) gain compared to the direct transmission (DT) in the multipath channel. We propose to use the multiple antennas at the transmitter based on TR SWIPT systems in the indoor multipath channel and derive the rate-energy (R-E) region performance numerically. The power gain obtained from multi-input single-output (MISO) TR-based SWIPT increases as the number of transmit antennas and the sampling frequency increases. Moreover, the achievable rate gain also improves as the number of transmit antennas increases. The proposed scheme is shown suitable to improve the achievable rate and the harvesting energy for SWIPT system in the indoor multipath channel.

In this work, we propose a link adaptation scheme called truncated channel inversion (TCI) as an effective power allocation strategy for block adaptive modulation, coding, and spatial mode (AMCS). Since water-filling based power allocation is no longer optimal to minimize bit error rate (BER) in block modulation system, block AMCS is considered as a practical link adaptation scheme. We first investigate the BER bound for multiuser multiple-input multiple-output bit-interleaved coded orthogonal frequency division multiplexing (MU-MIMO BIC-OFDM), and the optimal power allocation solution that minimizes the bound is derived. By showing that the solution from the BER minimization and the result from TCI are equal, we verify the suitability of TCI for MU-MIMO BIC-OFDM system with block modulation. Then, we propose a block AMCS algorithm that integrates TCI, and selects the optimal MCS and the corresponding power allocation which maximize the throughput under a packet error rate (PER) constraint. Improved transmission performance of the proposed algorithm is verified through simulation results.

We propose a full-duplex (FD) multiuser multiple-input multiple-output (MU-MIMO) precoding scheme to support the data transmission and self-interference (SI) cancellation simultaneously, by using the transceiver structure. In order to increase the dimensionality at the transmitter, the FD precoding scheme makes use of auxiliary paths, which have constant gains. The FD precoder design takes advantage of the increased dimensionality by jointly preprocessing the transmit signals for an effective trade-off between the forward channel beamforming and the SI suppression. From the numerical result, it can be shown that the proposed FD precoder improves the average sum rate of conventional FD network by setting the proper gains of auxiliary paths to deal with SI.

The carrier frequency offset (CFO) on the orthogonal frequency division multiplexing (OFDM) and offset-QAM-filter-bank based multi-carrier (FBMC) have been well studied. However, the impact of the CFO on the QAM-FBMC systems is complicated because of an unavoidable interferences from non-orthogonal prototype filters. In this paper, we analyze the impact of the CFO on the QAM-FBMC systems, and propose the method of the CFO estimation. By the analysis of the CFO, the CFO is separated to the integer part and fractional part. For the integer part estimation, we propose the pilot design to guarantee the relative high power at pilot subcarrier location in up-sampled frequency domain. For the fractional part estimation, we formulate the inner product equation between two preamble symbols, and suggest the approximated estimation for lack of the channel information. Simulation results show the performance of the CFO estimation in AWGN and pedestrian channel, and also show that the proposed approximated estimation works well with a slight performance degradation.

Identifying different floors in multistory buildings is a very important task for precise indoor localization in industrial and commercial applications. The accuracy from existing studies is rather low, especially in multistory buildings with irregular structures such as hollow areas, which is common in various industrial and commercial sites. As a better solution, this paper proposes a hybrid floor identification (HYFI) algorithm, which exploits wireless access point (AP) distribution and barometric pressure information. It first extracts the distribution probability of APs scanned in different floors from offline training fingerprints and adopts Bayesian classification to accurately identify floor in well-partitioned zones without hollow areas. The floor information obtained from wireless AP distribution is then used to initialize and calibrate barometric pressure-based floor identification to compensate variable environmental effects. Extensive experiments confirm that the HYFI approach significantly outperforms purely wireless fingerprinting-based or purely barometric pressure-based floor identification approaches. In our field tests in multistory facilities with irregular hollow areas, it can identify the floor level with more than 96.1% accuracy.

The digital-analog hybrid beamforming technique with a number of antennas is necessary for the millimeter wave (mmWave) communications to overcome both high complexity of large array system and high path loss of mmWave signals. Since the hybrid beamforming system has multiple radio-frequency (RF) chains, the simultaneous transmission is possible which is known as the space division multiple access (SDMA). However, we cannot apply the digital precoding schemes to the hybrid beamforming system due to the hardware constraints of RF beamforming matrix. In this paper, we propose a joint scheduling and hybrid beamforming system with partial side information. Then we provide the achievable sum rate upper bound and the scaling law of the asymptotic sum rate. It is shown that our system can take advantage of the same multi-user diversity gain with the digital system. Interestingly, the proposed hybrid system outperforms the digital system in the low SNR regime which is suitable for mmWave channel.

We consider the full-duplex (FD) two-way amplify-and-forward relay system with imperfect cancellation of loopback self-interference (SI) and investigate joint design of relay and receive beamforming for minimizing the mean square error (MSE) under a relay transmit power constraint. Due to loopback channel estimation error and limitation of analog-to-digital converter, the loopback SI cannot be completely canceled. Multiple antennas at the relay can help loopback SI suppression, but beamforming is required to balance between the residual SI suppression and the desired signal transmission. Moreover, the relay beamforming matrix should be updated every time slot, because the residual SI in the previous time slot is amplified by the current beamforming matrix and added to the received signals from the two sources in the current time slot. We derive the optimally balanced relay beamforming and receive beamforming matrices in closed form based on minimum MSE, taking into account the propagation of the residual loopback SI from the first to the current time slot. We also propose beamforming design using only the channels of the $m$ latest time slots, not from the first time slot. Based on our numerical results, we also identify when FD is beneficial and propose selection between FD and half-duplex according to signal-to-noise ratio and interference-to-noise ratio.

Millimeter wave (mmWave) experiences a high path-loss in free space. To overcome this weakness, antenna array is used to obtain a high beamforming gain. However, due to high complexity of digital beamforming systems, the hybrid structure consisting of baseband and analog precoder has been proposed. We consider the well known block diagonalization (BD) precoding for transmission technique. Because of the practical constraints such as channel estimation error, the limited number of radio frequency (RF) chains and the quantized analog phase shifters, the BD precoder cannot provide accurate interference-free effective channel. In this paper, we propose the extended BD precoding method which extends the null space of interference channels to reduce the effect of practical constraints. Simulation results show that the proposed method provides much improved sum rate and error performances than original BD precoder.

This paper proposes minimum mean square error (MMSE)-based amplify-and-forward (AF) relay amplifying matrices under perfectly and imperfectly known channel state information by imposing a constraint on the transmit power of the relays. The main objective of this paper is to determine optimal relay amplifying matrices with and without channel uncertainty under the transmit power constraint at the relays. Additionally, by using the derived optimal relay amplifying matrices, it is proven that the better BER performance is observed when power is constrained at the relays during data transmission, compared to the no-power constraint case in [6]. Finally, simulation results show that the MMSE cost function values with and without channel uncertainty are always less than the number of sources and destinations (M), regardless of the number of relays (N).

We consider a two-phase cooperative transmission strategy in cognitive femtocell networks, where a femto-base station (BS) employs cooperative relaying to increase throughput of a macro-mobile station (MS) at cell edge in reward for the access of the spectrum allocated to the macro-MS. Under this strategy, we formulate optimization problem to maximize the femto-MS rate while satisfying the rate requirement of macro-MS and illustrate the optimal policy: optimal time duration and power allocation. In addition, we analytically derive the critical cooperation region where a femto-BS can always achieve the rate requirement of the macro-MS, which is expressed in terms of distances between femto-BS and macro-MS and between macro-BS and femto-BS. The simulation results show the derived cooperation regions for different β and confirm rate gain of the cooperation strategy.

Millimeter wave (mmWave) signals experience a significant path-loss in free space. To overcome this weakness, a large number of antennas are needed to obtain a high beamforming gain. Although a large number of antennas can be implemented in small area due to the short wavelength, the digital beamforming techniques cannot be implemented easily due to the high complexity of hardwares. To solve this problem, the hybrid beamforming systems which have smaller number of radio frequency (RF) chains are proposed in the literature. Although the hybrid beamforming systems may achieve the spectral efficiencies of the digital beamforming systems closely, the spectral efficiency cannot be monotonically increase along with the number of data streams due to the limited scattering in mmWave channel. In this paper, we provide a guide for the design of mmWave hybrid beamforming systems. We find the optimal number of streams, and present the spectral efficiency achievable region in which the system guarantees the reliable communications with the lowest cost.

This paper addresses optimum nondiagonal and diagonal amplifying relay matrices for the amplify- and-forward (AF) wireless relay networks. Single- input multiple-output (SIMO) nondistributed and distributed relaying system strategies with the relay power constraint are applied, based on the signal-to-noise ratio (SNR) criterion. By adopting the optimum amplifying relay matrices derived, the SNRs at the destinations are analytically and numerically investigated in order to evaluate the proposed system. In particular, using the SNR values, it can be predicted which scheme would yield a better system performance than the others.

Two different two-way amplify-and-forward (AF) wireless relay systems with transmit power constraints at the relay(s) are studied: one- relay system with multiple N antennas between two sources, and multiple N-relay system with one antenna per relay between two sources. The iterative and explicit relay amplifying matrices (or vectors) with perfect cancelation of self- interference under channel uncertainty are determined based on the minimum mean square error (MMSE) criterion. Both iterative and explicit relay amplifying matrices are numerically investigated through the simulation. Simulation results show that the gain of diversity order with channel uncertainty can occur as N increases, while the loss of diversity order can occur as channel estimation error powers increase.

This paper proposes amplify-and-forward (AF) relay strategies for two-way wireless distributed relay networks consisting of two sources with a single antenna per source and multiple N relays with a single antenna per relay. The objective of this paper is to determine optimal relay amplifying matrices (or vectors) under global and local power constraints at the relays based on the minimum mean square error (MMSE) criterion with/without the perfect cancelation of self-interference. With the derived optimal relay amplifying vectors, performances of the proposed two-way AF distributed relay system are investigated by presenting average bit error rate (BER), average MMSE behavior, and the sum of the achievable rate.

This paper presents optimum relay amplifying matrices (or vectors) using the minimum mean square error (MMSE), maximum signal-to-noise ratio (SNR), zero-forcing (ZF), and matched-filter (MF) criteria for an amplify-and-forward (AF) wireless distributed relay network with a one-source-one-destination pair and iV-relay under the global power constraint (GPC) at the relays in a channel uncertainty (CU) environment. In addition, the local power constraint (LPC) at the relays is also considered for the MMSE criterion. With the derived optimum amplifying relay matrices, cost function and SNR behaviors, achievable rate, and relay selection scheme in the CU environment will be investigated theoretically and evaluated numerically.

IEEE 802.11ac is a next generation wireless local area network (WLAN) standard employing multi-user multiple-input multiple-output (MU-MIMO) scheme for the first time. Since precoding and user selection schemes influence the performance of MU-MIMO transmission, accurate channel state information (CSI) is required to select users and obtain precoding matrix. In this paper, we evaluate the performance of linear precoding schemes such as channel inversion (CI) and block diagonalization (BD) with limited CSI by using compressed feedback. We also describe the greedy user selection metrics and linear precoding schemes of low complexity. Our results compare the achievable sum-rate between the user selection metrics and provide the packet error rate (PER) performance under the realistic channel models.

This study proposes an optimal time allocation scheme for two‐way relay channel (TWRC) using the physical‐layer network coding (PNC). In other words, this study analytically determines the optimal transmit time durations for the first and the second time slot, which maximise the achievable sum rate under a sum time constraint for a given squared magnitude of the channel coefficients and transmit power values. Numerical results show that the achievable sum rate for the proposed optimal time allocation is greater than or equal to that for equal time allocation.

An aggregate medium access control (MAC) service data unit (A-MSDU) contains multiple subframes with a single sequence number. Hence, it has a major drawback in environments with high error rates because if any subframes are corrupted, then the entire A-MSDU will be lost. In addition, performance of the A-MSDU depends strongly on the choice of parameters, such as frame size, modulation level, coding rate, and spatial mode. In this paper, a novel link-adaptation mechanism, dubbed physical (PHY)supported frame aggregation (PSFA), is proposed over IEEE 802.11 networks, and its performance is analyzed. The proposed PSFA technique is based on a cross-layer interaction that enables joint optimization of various parameters between the PHY and MAC layers. This paper derives a new packet error rate (PER) expression for convolutionally coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems as an example. Then, this PER expression is used to efficiently estimate the link quality, given the channel conditions and system parameters, and most importantly, it is able to facilitate a parametric study of the cross-layer interaction. In the proposed PSFA algorithm, we present a rule for selecting the parameters so that MAC throughput is maximized. It is shown analytically and verified using Monte Carlo simulations that this choice of parameters can improve throughput performance significantly and also ensure quality of service (QoS) requirements compared to existing conventional algorithms.

This paper presents a closed form of an optimal cooperative amplify-and-forward (AF) relay amplifying matrix for a distributed relay network of M-source-M-destination pairs and N relays, called a cooperative distributed AF relay network. The objective of this paper is to derive closed forms of minimum mean square error (MMSE)-based and zero-forcing (ZF)-based optimal AF relay amplifying matrices for the cooperative distributed AF relay network under the transmitter power constraint (TPC) at the relays, the receiver power constraint (RPC) at the destinations, and the no-power constraint (NPC) condition. Additionally, by substituting the derived optimum AF relay amplifying matrices into the original cost functions (CFs), the behavior of the optimum CFs and the total optimum signal component power (SCP) at the destinations are compared to each other for different cases. Finally, using the MMSE criterion, a novel relay selection scheme is proposed for the cooperative distributed AF relay network.

This paper proposes a cooperative wireless relay network consisting of a one-source-one-destination node pair and N relay nodes in three wireless communication environments, i.e., jamming, node geometry, and channel uncertainty. The main objective of this paper is to analytically derive the optimal cooperative amplify-and-forward (AF) wireless relay matrix under three conditions with the relay power constraint based on the minimum mean square error (MMSE) criterion. Using the derived amplifying relay matrix, the MMSE cost function and achievable rate will be investigated numerically and analytically.

A cooperative amplify-and-forward (AF) wireless relay scheme consisting of M sources, N relays, and L destinations all equipped with a single antenna is studied in this paper. The main objective is to design jointly and iteratively the closed-form of minimum mean square error (MMSE)-based source precode and relay amplifying matrices under a jamming environment with transmit power constraints and aggregate power constraints. With the derived optimal source precode and relay amplifying matrices, the jamming influence on system performance with both transmit and aggregate power constraints is examined numerically by using Monte-Carlo simulations.

This paper studies amplify-and-forward (AF) relay strategies for two-way wireless relay networks consisting of two sources with a single antenna and multiple relays with a single antenna. The closed form of relay amplifying matrices (vectors) with the perfect cancelation of self-interference under both no channel uncertainty and channel uncertainty is presented based on the minimum mean square error (MMSE) criterion. With the derived optimal relay amplifying matrices, the MMSE cost function behavior, the relay power usage, and the sum of the achievable rate are analyzed. Additionally, a filter for each destination will be provided to remove the influences of noises at the receivers.

An amplify-and-forward (AF) relay network has been studied extensively, but a closed form of an optimal AF relaying matrix is not available yet for the distributed AF relay network with the destination power constraint (DPC) and the following adverse environments: (a) partial-band noise jamming (PBNJ), (b) node geometry (NG), and (c) channel uncertainty (CU). Hence, this paper presents a closed form of an optimum AF relaying matrix consisting of a one-source-one-destination pair and N relay nodes under such adverse PBNJ, NG, CU, and DPC environments, based on the minimum mean square error (MMSE). By adopting the optimal relay amplifying matrix, the MMSE cost function behaviors are analytically and numerically studied.

This paper studies both cooperative and noncooperative amplify-and-forward (AF) wireless relay strategies with power constraints at the source and at the relays. The main objective is to design jointly and iteratively the closed form of a source scaling factor and a relay amplifying matrix, based on the minimum mean square error (MMSE) criterion under the conditions of both no-channel and channel phase misalignments. With the derived optimal source scaling factors and relay amplifying matrices, impacts on the system performance of both no-channel and channel phase misalignment are investigated by presenting the bit error rate and cost function behavior. Finally, this paper presents the iterative algorithm to solve the constrained Lagrangian optimization problem with a low computational complexity.

This paper addresses a more practical relay network consisting of a mobile source, multiple distributed mobile amplify-and-forward (AF) relays, and a mobile destination node. It considers an appropriate channel model between nodes, which is a cascaded Rayleigh fading channel. The objective of this paper is to determine an optimum AF relay vector (or matrix) using the minimum mean square error (MMSE) criteria for these distributed AF relay networks. The effects of jamming and imperfect channel state information (ICSI) on network performance are included in the analysis. Additionally, by substituting the derived amplifying relay vectors into the MMSE cost functions, it can be predicted which case will yield a better BER performance.

This paper presents both cooperative and noncooperative amplify-and-forward (AF) relay networks consisting of a one-source-one-destination pair and N-relays under receiver power constraint (RPC) at the destination. The optimal AF relay amplifying matrices for the relays by minimizing the mean square error are analytically derived. This paper also shows that the performance of the optimum cooperative relay network is identical to that of the optimum noncooperative network, as long as the same receiver power constraint is applied. The purpose of the RPC is to reduce the interference level for users located in neighboring cells. Finally, using the derived optimal relay amplifying matrices, the achievable rate, the pairwise error probability, and the outage probability are investigated.

This paper proposes amplify-and-forward (AF) relay matrices for a one-source-one-destination pair and cooperative distributed N relay nodes under three adverse wireless relay communication environments: (1) broadband noise jamming (BNJ), (2) node geometry (NG), and (3) channel uncertainty (CU). The main objective of this paper is to analytically derive the minimum mean square error (MMSE)-based optimal relay amplifying matrix. Another objective of this paper is to analyze the MMSE cost function, relay power usage, and signal component power of the received signal at the destination using the derived optimal relay amplifying matrix. Finally, the impacts on these three wireless communication environments for the wireless relay networks will be observed by presenting bit error rate (BER) performance.

This paper assumes a practical channel model, called a cascaded Rayleigh fading channel, for a noncooperative distributed mobile relay network, which consists of one mobile source and one mobile destination, and multiple mobile amplify-and-forward (AF) relays. Then, an optimum AF relay amplifying vector (or matrix) is analytically designed using the minimum mean square error (MMSE) criteria and uses it for an efficient mobile relay selection. Power is intentionally not constrained. Instead, this paper presents a scaling factor scheme to meet a target signal-to-noise ratio (SNRTGT) at the destination. This SNRTGTstrategy can implicitly embrace the power constraint problems and be a more practical implementation.

This paper proposes an optimal power allocation method for two-way decode-and-forward (DF) relay networks when transmit power values at source nodes are the same. In this paper we consider the multiple access (MAC) capacity for DF relaying scheme. Using case studies, it analytically determines the optimal power values for the two source nodes and one relay node. The achievable sum rate is maximized under a sum power constraint for given squared magnitude of the channel coefficients. Finally, numerical results show that the achievable sum rate for proposed optimum power allocation is greater than or equal to that for equal power allocation.

Inter-carrier interference (ICI) and multiuser interference (MUI) occur in an uplink orthogonal frequency division multiple access system if a channel between a mobile user and a base station is rapidly time-varying. To reduce the ICI and MUI, this letter proposes a subcarrier allocation method. The key idea is to allocate a high-speed user's subcarrier near a low-speed user's one. Then, a wide Doppler spread of a high-speed user can be spilled over a low-speed user's subcarrier band with insignificant influence, and the signal-to-interference-plus-noise ratio (SINR) at each high-speed user's subcarrier can be maximized. This can provide a significant performance improvement of multiuser detection in an uplink-OFDMA.

In this paper, we introduce a bit-interleaved binary space-time code (B-STC) for a coded multiple-input multiple-output (MIMO) system to obtain an additional diversity gain over the full-rate spatial multiplexing (SM) transmission. By applying the B-STC scheme, codeword bits from each stream are transmitted effectively through N_t or (N_t - 1) layers in N_r x N_t MIMO systems. At the receiver, the iterative decoding is performed. The extrinsic information provided by the soft-in/soft-out (SISO) decoder is applied as an improved priori information after the B-STC decoding at the next iteration. Since a priori information can be extracted from multiple layers independently by the B-STC scheme, codeword bits have an improved diversity gain of (N_t - 1). In order to verify the proposed scheme, we derive the asymptotic bit error probability, which can be achieved after convergence of the iterative decoder. Because the proposed B-STC scheme is a binary code for coded MIMO systems, different types of channel codes and various space-time codes can be also concatenated.

In a multiple-input multiple-output (MIMO) system of a large number of antennas, the requirement of an analog to digital converter (ADC) in each antenna string causes high implementation cost and excessive signal processing. Hence, a hybrid beamforming has been proposed in the literature as a solution. However, still quantization errors introduced at the analog beamformer part can lead to performance degradation. This paper is to present a quantization error reduction scheme for a hybrid beamformer in a 2 by 2 MIMO system. The key idea is to sacrifice the data rate from a full rate to a half rate, estimate all user data in a digital baseband, and then restore the received signal at each antenna string. By using the restored received signal and the residual (which is calculated in the estimator), quantization error can be reduced. Simulation results verify that the proposed scheme can improve the bit error rate performance with a resolution of smaller number of bits.

Visible light communication (VLC) is a short range optical wireless communication using the light emitting diode (LED) lights, which can provide both illumination and communication. In this paper, we characterize the indoor multi-path dispersion for VLC and propose multiple pulse position modulation (MPPM) as a power efficient modulation. Due to the reflections in indoor environment, equalization process is essential to mitigate inter-symbol interference (ISI). Frequency domain equalizer (FDE) is implemented to reduce computational complexity. We evaluate communication performance in terms of bit error rate (BER) and the spectral efficiency. Simulation results show that the proposed system yields a comparable BER performance to other equalization systems with lower complexity.

Demands for high throughput and stable service quality are increasing. Frame aggregation mechanisms in IEEE 802.11n wireless local area networks (WLANs) can provide improved throughput, but the effect of A-MSDU decreases significantly in error-prone channels. Therefore, adaptive frame size estimation (FSE) depending on the channel condition is required to maintain the improved throughput. In this paper, we proposed frame error rate (FER) based FSE scheme in error-prone and time-varying channel such as a high-stressed network. A tight FER bound is derived to obtain instantaneous link condition, and extended Kalman filter (EKF) is used to estimate frame size optimally for next transmission with current channel information. Our simulation results show that the proposed FSE scheme improves the throughput two times higher than a nonadaptation approach in high-stressed network condition.

This paper describes the exploitation of physical layer confidence in bits (SoftPHY) in order to improve the rate selection in a bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system. Instead of relying on a measured instantaneous bit error rate (I-BER) from received packets, we built a closed-form I-BER expression that gives accurate and simple functional mapping between the instantaneous channel state and the selected set of modulation level and coding rate. The accuracy of the rate selection and the enhancement of the proposed scheme are confirmed through Monte-Carlo simulations.

This paper studies minimum mean square error (MMSE)-based full-duplex relay processing matrices and source/destination beamforming vectors under perfect channel state information by imposing constraints on the transmit power of source, relay, both, separately, and in various combinations. The main contribution of this paper is the derivation of a set of relay processing and source/destination beamforming vectors under diverse conditions of transmit power constraints on the source and relay. By comparing the bit error rate (BER) performance of each case, an efficient design of a full-duplex amplify-and-forward relay system is presented.

This paper considers an amplify-and-forward (AF) relay scheme for M-source-M-destination pairs and N relay nodes. Cooperative minimum mean square error (MMSE) strategies for wireless relay networks under both a jamming environment and channel uncertainty with received power constraints at the destination nodes are studied. The main contribution of this paper is the derivation of the MMSE-based amplifying relay matrices (ARMs) under both a jamming environment and channel uncertainty. With the proposed ARMs, the system performance under study is evaluated by observing bit error rate (BER) using Monte Carlo simulations. In addition, it is proven that the proposed ARM is the global optimal ARM.

As channel time-variation increases, orthogonality among subcarriers in an orthogonal frequency division multiplexing (OFDM) symbol can be destroyed because of the relatively long symbol period, whereupon intercarrier interference (ICI) appears, and hence an irreducible error floor occurs. It was shown recently that grouping pilot tones into a number of equally spaced clusters can yield better channel estimation against the doubly selective channel than placing each pilot tone in an equally spaced manner. However, a random pilot sequence was used in the literature, and an optimal sequence has not yet been studied. This paper presents how to optimize the clustered pilot sequence. First, this paper (a) proves the existence of an optimum pilot sequence and (b) suggests a guideline for finding an optimum sequence. Second, this paper shows that an optimum sequence is independent of the signal-to-noise ratio and Doppler rate, and the sequence is generally optimum for any channels. Third, this paper verifies through analysis and simulation that the coded-OFDM system with an optimized cluster pilot sequence can yield a smaller mean square channel estimation error and lower bit error rate than the system with an equidistance pilot or a random cluster pilot under a rapidly time-varying channel.

In this paper, we introduce a simple bit-interleaved binary space-time code (B-STC) for a coded multi-input multi-output (MIMO) system to obtain an increase in information rate, where two transmit and two receive antennas are used. We derive a probability density function (pdf) of log-likelihood ratio (LLR) for the B-STC decoder output and approximate it with the pdf of MIMO detector output having the degraded SNR. The average bit error probability at the i-th iteration is represented in terms of moment generating function with differently distributed SNRs. Although the iterative decoder in the B-STC structure increases the computational complexity, the number of iterations i is not large (i≤3). Because the proposed B-STC scheme is a binary code for MIMO systems, different types of channel codes and various space-time codes can be concatenated. To achieve near-capacity performance on MIMO channels, an iterative receiver structure with a soft interference cancellation scheme can be also adopted as an outer iteration. And the proposed scheme can be extended to arbitrary number of transmit and receive antennas.

An inter-carrier interference (ICI) occurs in an orthogonal frequency division multiplexing (OFDM) system when a channel is rapidly time-varying. The proposed scheme employs a polynomial cancellation code (PCC) to suppress this ICI, and uses a linear complex field (LCF) code as a transmit-diversity technique to make the transmission rate compatible up to {nT} / {(nT+1)}, where nTis the number of transmit antennas used. The conventional orthogonal code (OC), such as the Alamouti code, with accompanying PCC cannot achieve this rate. Both analysis and simulation results verify that the proposed scheme can achieve higher channel capacity as well as lower bit error rate (BER) than the other schemes in rapidly time-varying channels, even with a linear receiver and inaccurate channel estimation.

This paper introduces a new link adaptation (LA) approach called the adaptive modulation, coding, and spatial mode (AMCS) scheme for multiple-input multiple-output bit-interleaved coded orthogonal frequency division multiplexing (MIMO BIC-OFDM) systems. The AMCS technique can provide both minimal performance degradation and significant throughput gain by controlling the spatial streams. With this technique, we can derive a simple and accurate closed-form expression of an instantaneous bit error rate (I-BER). Based on the I-BER, the proposed AMCS scheme chooses an appropriate modulation, coding, and spatial mode (MCS) type that improves the system performance while satisfying the quality of service (QoS) requirement. A simplified MCS type search method is also proposed, which allows the receiver to effectively select a MCS type and then send it back to the transmitter by using only a small amount of information bits. The simulation results confirm the superiority of the proposed AMCS approach over conventional LA schemes in trading high-throughput for reduced complexity.

The instantaneous bit error rate (I-BER) is a direct representation of system performance given a particular channel realization. The I-BER knowledge enables wireless system to combat fading channel impairments by properly adapting transmission parameters. In this paper, we derive the I-BER for a bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system. In high signal-to-noise ratio (SNR) regions, under the assumption that an erroneous symbol contains only one bit error, a codeword pairwise error probability (PEP) is approximated by a symbol PEP. The above assumption is used again to evaluate the symbol PEP for an arbitrary QAM with Gray labeling. Compared with a previously obtained result, the new I-BER expression provides a tighter upper bound for convolutional coded BIC-OFDM systems. We also discuss a practical use of the I-BER in a link adaptation process.

An exact form of symbol error rate (SER) is derived for zero-forcing decision feedback equalization (ZF-DFE) on fast fading channels. We present an error propagation framework in ZF-DFE, which is dependent on the length of multipath and the size of M-ary quadrature amplitude modulation (M-QAM). By applying the concepts of “error event” and “state” on this framework, we can evaluate the error probability considering the error propagation. Compared with the previously obtained results, our approach gives an accurate SER expression for Gray-mapped M-QAM on L-tap multipath fading channels. The simulation results are provided to verify the accuracy of the new error rate expression.

In this paper, we propose a method to mitigate the interferences for single carrier frequency domain equalizer (SC-FDE) without cyclic prefix (CP). SC-FDE systems suffer from the interferences when CP is appended insufficiently. Inter block interference (IBI) is introduced by the previous block, and inter symbols interference (ISI) is also generated by imperfection of the circulant channel matrix. The proposed method can effectively restore the channel matrix to be circulant, but the interference is also increased. Thus, some method, to make a compromise between compensating ISI and increasing the interference, is needed and is that the criterion is adopted to maximize the signal to interference plus noise ratio in this paper. However, the improvement of the performance is limited since the interferences are not removed. To overcome it, the interferences are cancelled using iterative MMSE receiver structures. The performance of the system outperforms that of conventional CP reconstruction method, and it is verified by computer simulations.

In this paper, we deal with user scheduling algorithms for a codebook based precoding of a multiuser multiple-input multiple-output (MIMO) downlink system considered in IEEE 802.16m and 3rd Generation Partnership Project Long-Term Evolution (3GPP LTE) standardization. We especially focus on per-user unitary rate control (PU2RC) and semi-orthogonal user selection schemes. Also, we examine the disadvantage of the codebook based precoding with these schemes - a loss of sum-capacity when the codebook size is larger than the number of total users who request the communication service to a base station. Finally, we propose two user scheduling algorithms to improve the sum-capacity when the number of total users is smaller than the codebook size. First, we introduce feedback information retransmission algorithm in which each user sends a new codeword again depending on a request of the base station. Second, we address the adaptive feedback algorithm where users transmit one or two codeword indices called preferred matrix index (PMI) depending on their channel condition. The improvement of the sum-capacity is verified through the simulation.

This paper proposes a new inter-carrier interference (ICI) cancelling scheme for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) in time and frequency selective fading channels. Based on the ICI distributions, we try to extend the conventional MIMO detection schemes. Nevertheless this extension increases the computational complexity significantly whereas the performance gain is not satisfactory. To improve the capability of ICI cancellation, we employ successive interference cancellation (SIC) method not in MIMO detection but in ICI cancellation. However, the processing delay time due to the SIC in OFDM will grow according to the increase of the number of subcarriers. To overcome this effect, we propose a modified SIC (MSIC) that can reduce the processing delay dramatically at the expense of some performance degradation. In simulation, we show the expense is so small that it can be ignored in severe time-selective channels.

This paper introduces an efficient multiple-decision-feedback (MDF) detection for space time block code (STBC) over time-selective fading channels. The MDF detection performs several decision-feedback (DF) detections for the most probable points obtained by a log-likelihood ratio (LLR) based bit flipping scheme. Simulation results show that, with reasonable complexity, the MDF detection provides near maximum likelihood (ML) performance by achieving the considerable SNR gain, compared with the existing DF detections.

While multiple-input multiple-output (MIMO) system gives many advantages to wireless communication, the complexity of multiple RF chains gives a burden to the system. Antenna selection is introduced as a technique to reduce the burden. On the transmit antenna selection scheme, the exhaustive search for optimal antenna set quickly becomes impractical as adopting more antennas. To reduce complexity for searching, we propose an efficient transmit antenna selection method. We first make a threshold for optimal antenna set by using Poincare separation theorem. Instead of exhaustive search, we select a transmit antenna subset that exceeds the threshold. On the exponentially correlated channel of array antennas, we give an order to search for reducing complexity further. We search from the most remotely located antenna subset which in generally less correlated to the closely located antennas which is more correlated. Finally, we show the BER performance and tradeoff relation between performance and complexity by Monte-Carlo simulations.

In this letter, we introduce an analytical expression to the coded bit error rate (BER) of a MIMO system with a linear minimum mean square error (MMSE) receiver. We derive the moment generating function (MGF) of the SINR for arbitrary antenna configurations from the cumulative density function of SINR.We show that the moment generating function of the SINR at the MMSE detector output can be used to estimate the BER performance of a coded MIMO system. The analysis is simple and gives an accurate BER estimation at a high SNR. Based on the analytical and simulated results, the diversity order is dependent on the antenna configuration and the free distance of the convolutional code. Finally, we compare the analytical expression with simulated results for validation.

This paper describes parameters design of multiuser OFDM on doubly selective fading channels. It is well-known that OFDM is vulnerable to time selectivity due to the extension of symbol period, generating inter-carrier interference (ICI). In this paper, we first derive the closed form of signal to interference plus noise ratio (SINR) for single user OFDM with a linear time-varying model. In multiuser case, we propose several design criteria depending on the channel environments. We also discuss an effect of subcarrier allocation on the parameters optimization in multiuser access systems.

In 1974, BCJR algorithm[l] was invented for maximum a posteriori (MAP) decoding of error correcting codes defined on trellises. In this paper, we apply BCJR algorithm to the detector for coded multiple-input multiple-output (MIMO) system to achieve high detection performance. With known channel information, coded MIMO detector can compute log- likelihood ratio (LLR) on the channel trellis by BCJR algorithm. We also propose a simple BCJR algorithm with computational cost reduction. Simulation results show that BCJR algorithm achieves higher performance than maximum likelihood (ML), and there is negligible performance difference between proposed simple method and conventional BCJR algorithm.

This paper proposes two efficient decision-feedback (DF) detection schemes for space time transmit diversity (STTD) over time-selective fading channels. The existing DF detection causes error propagation when the first symbol is not detected correctly. However, the proposed detection schemes provide two candidates for the first symbol and choose a better candidate according to a channel gain or an average log-likelihood ratio (LLR) based selection rule. Simulation results show that the proposed detection schemes reduce error propagation and yield significant signal-to-noise ratio (SNR) gain with slightly increased complexity, compared to existing DF detection scheme.

This paper investigates the effects of antenna correlations on spatial diversity and multiuser diversity. Using an upper bound on achievable capacity from order statistic theory, we quantify the interactions between spatial correlation, spatial diversity and multiuser diversity. Our theoretical analysis and simulation results demonstrate a positive influence of spatial correlations on achievable capacity of spatial diversity techniques combined with multiuser diversity, while it has been known that spatial diversity limits a multiuser diversity gain without spatial correlation.

This paper considers the uncoded multiple-input multiple-output (MIMO) system with linear minimum mean square error (MMSE) detection under ideal fast fading. The distribution of SINR at the output of the MMSE detection is derived for a small number of transmit and receive antennas. We present new approximation for the Gaussian Q-function driven by numerical simulation. Based on the SINR distribution and new approximation for Q-function, we analyze the performance of linear MMSE detection under ideal fast fading environment. By comparing the analytical results and Monte Carlo simulated results, we validate the analytical results.

Six Sigma has been adopted by many software development organizations to identify problems in software projects and processes, find optimal solutions for the identified problems, and quantitatively improve the development processes so as to achieve organizations' business goals. A Six Sigma framework for software process improvements is needed to provide a standard process and analysis tools for Six Sigma project executions, and also provide a platform for collaborations with other process improvement approaches, such as PSP/TSP and CMM/CMMI. However, few frameworks have been proposed to support Six Sigma project executions. Most of Six Sigma projects for software process improvements have been performed in an ad-hoc way. In this paper, we propose a framework to support Six Sigma projects for continuous process improvements for software developments. Based on this framework, we implemented a web-based tool, called SSPMT integrated with a software project management tool and a PSP supporting tool. The suggested framework and SSPMT is beneficial in initiating and executing Six Sigma projects, facilitating data collection and data analyses by Six Sigma toolkits, and standardizing the Six Sigma project execution process so as to achieve Six Sigma project goals and of organizations' business goals.

This paper presents a new double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) scheme using the zero-forcing decision-feedback (ZF-DF) detector. To improve the diversity gain of streams in the lower Alamouti's STTD unit, the proposed system adopts frequency-repetition method. Analytical results verify that the proposed system can obtain the fourth order diversity gain, whereas the conventional DSTTD-OFDM system produces the second order diversity gain. We also suggest open-loop power allocation to minimize lower performance bound. Simulation results show that the proposed system outperforms the conventional DSTTD-OFDM system with the ZF-DF detector by about 3.7 dB at the bit error rate (BER) of 10 4. The open-loop power allocation provides additional 1.0 dB performance improvement.

In the multiple-antenna broadcast channel, each user is not allowed to cooperate with other users, so the efficient and well-designed preceding scheme to reduce other users' interferences is required. Recently, the use of lattice basis reduction(LR) has been shown to be a very effective method for preceding in multiuser multiple antenna systems. Lattice basis reduction helps to reduce the average transmitted energy by modifying the region which includes the constellation points. Even though the LR precoding method achieves a full diversity order, the performance loss caused by quantization error still remains. In this paper, we propose a simple precoding technique to reduce the quantization error. The proposed scheme establishes a lattice list to provide more candidates for transmission power reduction based on the analysis of the patterns of the error. Simulation results show that the proposed scheme achieves the BER performance as good as that of more complex precedents (such as the vector perturbation using sphere-encoding) with significant saving in complexity.remains.

Open-loop full-diversity full-rate (FDFR) code can achieve both high data rate and good reliability at the expense of significantly increased decoding complexity. To mitigate the decoding complexity, low-complexity FDFR code was designed for closed-loop system, combining the preceding and constellation rotation with channel state information (CSI) at the transmitter. Since conventional closed loop FDFR encoding procedure is similar to that of open loop FDFR code, however, it suffers from latency problem due to multiple-symbol-periods encoding and decoding process. Also, the rotation matrix is fixed irrespective of temporal channel response. In this paper, we propose simple FDFR scheme which performs single-symbol- period encoding and decoding procedure. Moreover, we improve error performance of closed-loop FDFR code by exploiting a adaptive rotation matrix corresponding to temporal channel state, especially the singular values of channel. The adaptive rotation matrix construction aims at maximizing the minimum Euclidean distance among received signals. Simulation results support the validity of the proposed FDFR scheme.

We introduce and analyze an enhanced cooperative diversity system where the source, relay, and destination are equipped with single antenna, respectively. A time-division multiple-access (TDMA) based cooperative protocol is considered. This protocol has full data rate because the source transmits two symbols during two time slots. However, the protocol does not obtain full diversity gain, because each column of effective channel matrix has a different distribution. We propose the constellation rotation scheme to solve the problem. Also, we analyze the diversity gain of the proposed system with the maximum-likelihood (ML) receiver by deriving the pairwise error probability (PEP). The analysis proves that the system applying the constellation rotation scheme achieves a full diversity. Also, we verify the superiority of the proposed scheme from the simulations.

High spectral efficiency and the reliability can be achieved by multiple transmit/receive antennas. As a such system, double space-time transmit diversity (DSTTD) is introduced. Furthermore, an antenna shuffling using partial channel feedback can additionally improve performance of the DSTTD system. However, the multiple antennas and the amount of feedback overhead are serious burden to system in terms of complexity and cost. In this paper, we consider hybrid space time code (STBC) with three transmit antennas. By deriving the error performance of hybrid STBC with zero-forcing decision feedback (ZF-DF) detector, it is demonstrated that hybrid STBC has almost the same performance of the DSTTD system. Then, we apply an antenna subset selection scheme to hybrid STBC. Though this scheme needs the fewer number of transmit antennas and the smaller amount of feedback overhead than those of antenna shuffling, it can provide comparable error performance of antenna shuffling. Especially, on selecting transmit antennas, we propose an efficient transmit antenna selection rule for ZF-DF detector.

OFDM can significantly reduce the receiver complexity by using one-tap equalizer in frequency selective channels, and it can be enhanced the capacity and diversity by using cooperative scheme. However, high data rate transmission with OFDM requires the channel state information (CSI), and therefore OFDM channel estimation for cooperative communication can be a challenging problem. In this paper, we investigate the OFDM channel estimation suitable for the amply-and-forward (AF) cooperative channel. Cramer-Rao lower bound (CRB) of the estimation is derived, and optimal preamble conditions that minimize the CRB with several power constraints are proposed. Moreover, minimum variance unbiased (MVU) estimator that achieves the CRB is introduced for the cooperative channel. Simulations with analytical results confirm the performance of our methods.

Near maximum-likelihood(ML) detections with reduced complexity are promising techniques for coded multiple- input multiple-output (MIMO) systems. Particularly, the QRM- MLD algorithm is often considered in practical applications since it can easily control receiver's complexity. However, it provides inaccurate log likelihood ratio (LLR) values due to the limited number of candidate symbol vectors. To overcome the problem, this paper presents an efficient LLR computation algorithm. The proposed algorithm calculates approximate LLR values calculated at every stage instead of computing LLR values only at the last stage. At each stage, the proposed algorithm updates approximate LLR values to reflect their reliability on the LLR value. Simulation results show that the proposed algorithm can obtain better performance than conventional LLR calculation scheme especially when low order modulation is employed, or the number of considering candidate vectors is small.

This paper presents a new vertical Bell labs layered space-time (V-BLAST) transmission scheme for developing reduced-complexity receiver. It can significantly alleviate the receiver complexity in sense of tree searching of the QRD-M algorithm. The new V-BLAST system is designed by two criteria: minimum performance loss and maximum complexity reduction. In a 4 times 4 V-BLAST system with 16 bps/Hz, the former can lessen about 51% metric computations with 1.0 dB performance degradation, compared with the conventional V-BLAST system with the QRD-M algorithm. The latter can achieve approximately 65% complexity reduction at the expense of 3.0 dB performance penalty.

This paper presents a new double space-time transmit diversity (DSTTD) transceiver exploiting the special structure of the channel matrix. This accounts for accomplishing very low complexity maximum-likelihood (ML) detector. First, the proposed ML detector requires significantly fewer computations than that of the Schnorr-Euchner sphere decoding (SE-SD) algorithm in respective of both the worst-case and the average complexity. Moreover, the complexity of the proposed ML detector is further reduced with sacrificing slight performance loss, provided that the proposed DSTTD transmitter is used.

Using a variable scaling factor (VSF), a modified enhanced max-log-maximum a posteriori (EMLMAP) algorithm is proposed to improve the performance of the conventional EMLMAP algorithm which uses a fixed SF. The VSF, maximising the mutual information exchanged between component decoders in a turbo decoder, is adaptively varied with a priori information of each component decoder. For a large size of interleaver, it is shown that the proposed algorithm improves the bit error rate performance and speed of decoding convergence of the conventional EMLMAP algorithm. The improved speed of the decoding convergence reduces the average number of iterations and results in low-power implementations of a turbo decoder.

We investigate closed-form bit error rate (BER) expressions for the double space-time transmit diversity (DSTTD) system with a zero-forcing decision-feedback (ZF-DF) detector. We show that the lower Alamouti's STTD unit can obtain the second order diversity gain. However, the upper one cannot guarantee the fourth order diversity due to the effect of error propagation. For example, it simply gives 3.5 dB signal-to-noise ratio (SNR) advantage over the lower one at the bit error rate (BER) of 10-3. Under the same environment, overall BER performance also suffers from 5.6 dB performance degradation over a maximum likelihood (ML) detector.

In this paper, we investigate and propose the detection techniques for spatially layered multiple-input multiple-output (MIMO) multi-carrier code division multiple access (MC-CDMA) systems. First, we propose a noise-predictive linear detector. It has the same bit error rate (BER) performance as symbol-level detector and reduces the complexity significantly when the system load is almost full. We also propose a partial minimum mean square error (MMSE)-ordered successive interference cancellation (OSIC) based on multi-user detection, which first detects the most powerful interfering data symbols transmitted through the determined transmit antenna and then cancels their contribution from the received signal by the multiplexed data symbol vector. The nulling and cancelling processes between the user data symbols from the same transmit antenna are not performed. The proposed algorithms are verified by computer simulation

Lattice reduction (LR) has been recently used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection schemes. In this paper, we propose the LR aided scheme based on the augmented channel matrix and develop the method that corrects the errors occurred in the quantization step. Numerical simulations show that the proposed LR scheme exhibits improved performance and a slight increase in complexity. Moreover, if we combine the conventional LR aided scheme with the quantization error correction, then bit error ratio (BER) performance is improved with trivial complexity increase at high SNR.

Orthogonal frequency division multiplexing (OFDM) can significantly reduce a receiver complexity using one-tap frequency domain equalizer in a frequency-selective fading channel. However, the channel variation due to high mobility gives a time-selectivity in one OFDM symbol. As a result, each OFDM subcarrier experiences inter-carrier interference (ICI) that makes the equalization process very complicate. We propose a low complexity ICI cancellation method that takes advantage of the ICI power distribution. Instead of computing the inversion of the whole channel frequency response (CFR) matrix, we split the matrix into several small sub-matrices that contain significant channel information and perform a linear minimum mean squared error (LMMSE) equalization. We also propose an efficient successive interference cancellation (SIC) method that can effectively utilize a time diversity resulting from the mobility. Simulation results show that the performance improvements is remarkable even though the sub-matrix size is much smaller than that of the whole CFR matrix while taking high computational efficiency.

We present two ordered successive interference cancellation (OSIC) schemes using the QR decomposition for the double space-time transmit diversity (DSTTD) system. These are designed by zero-forcing (ZF) and minimum-mean-squared error (MMSE) criteria. The computational complexity is significantly reduced by utilizing special structure of the channel matrix. These schemes require fewer computations than previously known OSIC schemes. Especially the ZF-OSIC-QR achieves approximately 8% lower computational efforts than the two-stage linear ZF detection with 2.4 dB performance advantage at the bit error rate (BER) of 10-4.

We propose efficient iterative interference cancellation algorithms for the vertical Bell Laboratories layered space-time (V-BLAST) system. Proposed schemes consist of conventional successive interference cancellation based on the QR decomposition (SIC-QR) and diversity combining techniques such as maximal-ratio combining or selection combining. We develop upper bounds of the SIC-QR and proposed schemes. Significant performance improvement is obtained by increasing diversity order of each stream and alleviating the effect of error propagation. In particular the proposed schemes can accomplish significant performance advantage over the ordered SIC (OSIC) in small numbers of antennas system. In addition, we compare the complexity of proposed schemes with the SIC-QR and previously reported OSIC algorithms. Proposed schemes require slightly increased complexity, when compared to the SIC-QR. It is also shown that additional computations could be reduced by controlling iteration numbers.

We present new trellis codes based on multiple-pulse-position modulation (MPPM) for wireless infrared communication. We assume that the receiver uses maximum-likelihood sequence detection to mitigate the effects of channel dispersion, which we model using a first-order lowpass filter. Compared to trellis codes based on PPM, the new codes are less sensitive to multipath dispersion and offer better power efficiency when the desired bit rate is large, compared with the channel bandwidth. For example, when the bit rate equals the bandwidth, trellis-coded (17 2)-MPPM requires 1.4 dB less optical power than trellis-coded 16-PPM having the same constraint length.

We propose a new coarse frequency offset estimation algorithm in orthogonal frequency-division multiplexing systems, which performs robust operation in the presence of a symbol timing offset within an allowed range. The effect of a symbol timing offset on estimating a coarse frequency offset is analyzed, and the coherence phase bandwidth according to the allowed symbol timing offset is introduced. The proposed algorithm adapts the concept of the coherence phase bandwidth for the purpose of weakening the effect of the symbol timing offset.

A new coarse frequency offset estimation algorithm is proposed which performs robust operation in the presence of a symbol timing offset in an allowed range. The effect of a symbol timing offset on estimating a coarse frequency offset is analyzed and the coherence phase bandwidth according to the allowed symbol timing offset is introduced. In addition, a new technique for performing the coarse frequency estimation using the coherence phase bandwidth is described. Simulation results show that the proposed algorithm estimates a coarse frequency offset well under both AWGN and multipath channels even in the presence of the symbol timing offset within an allowed range.

We design new trellis codes based on multiple pulse-position modulation (MPPM) that offer high power efficiency. We randomly search for the optimal code that produces the trellis code with the largest minimum Euclidean distance. To verify our results, we derive an approximation for the minimum distance. We combine partial-response precoding with parallel decision-feedback detection to equalize and to decode the trellis codes. The performance of the proposed scheme is compared to linear equalization, decision feedback equalization, parallel decision-feedback detection, and super-state maximum-likelihood sequence detection. Together, the proposed trellis codes and precoding schemes are an effective solution to the signaling design problem, especially in the face of severe multipath dispersion.

We propose a partial-response precoding scheme for combatting intersymbol interference that is compatible with trellis codes based on multiple-pulse position modulation. The scheme reduces the span of intersymbol interference from a possibly infinite number to two baud periods, significantly reducing the complexity of the receiver equalizer. Numerical results show that, in terms of performance and complexity, the proposed scheme compares favorably to conventional linear equalization, block decision-feedback equalization, and superstate maximum-likelihood sequence detection.

Although multiple pulse-position modulation performs well on ideal channels, its performance on multipath channels is degraded significantly. In an attempt to quantify the inherent penalty due to multipath dispersion, we evaluate upper bounds for the error probability of each modulation scheme in the presence of intersymbol interference, considering both an unequalized receiver and the optimal maximum-likelihood sequence detection receiver. We also present upper and lower bounds of the channel capacity for multiple pulse-position modulation and its variants, PPM and overlapping PPM. Numerical results show that the PPM-based schemes are significantly more sensitive to multipath dispersion than is on-off keying.