We propose in this paper a novel hierarchical multi-grid orthogonal matching pursuit based angle estimation scheme. The proposed scheme accurately estimates the angles of departure (AoDs) and the angles of arrival (AoAs) of a point-to-point ultra massive multiple input multiple output (UM-MIMO) system, ensuring ultra-resolution estimation accuracy. Specifically, we define the on-grid error range in the conventional compressive sensing (CS) estimators and build high-resolution grids centered at the estimated discrete on-grid angles. The proposed scheme proceeds hierarchically through multiple levels to refine the angle estimations. Numerical simulations demonstrate the efficacy and superiority of the proposed scheme over recent state-of-the-art literature, where sub-millidegree angle estimation accuracy can be attained.

The terahertz (THz) spectrum, with its abundant available bandwidths, has garnered significant attention for its potential to advance wireless communications and enhance radar sensing capabilities, leading to improved data rates and spatial resolution, respectively. However, in indoor environments, the blockage or significant attenuation of THz waves due to the presence of humans and other obstructing materials poses a recognized challenge. Therefore, a line-of-sight (LoS) link is preferred though cannot be guaranteed in all situations. Nonetheless, this work explores the scattering properties of commonly encountered indoor objects, such as walls, for establishing a nonline-of-sight (N-LoS) link. An N-LoS testbed is employed to investigate both the communications and radar sensing capabilities through wall reflections. From a communications perspective, the recording of the transmit signal at varying incidence angles is presented. Additionally, radar imaging is demonstrated employing the syn-thetic aperture radar (SAR) technique, enabling the visualization of objects hidden from direct view.

This paper focuses on exploring the wideband beam split effect in the near-field region under the adoption of practical true time delay (TTD) elements. We formulate the design of the wideband hybrid analog precoder as a joint optimization problem taking into account the hardware limitations of TTDs. To tackle this non-convex problem, we propose a greedy beamfocusing (GB) approach with two stages utilizing the delta-delay-phase precoding (DDPP) architecture in the near-field. The proposed approach designs the hybrid precoder while accounting for TTDs' limitations in its first stage. In the second stage, this approach adapts the resulting time delay values of TTDs to enable operation of the DDPP architecture in the near-field region. Numerical simulations depict that the state-of-art beamfocusing schemes in the near-field can realize only low-resolution beamsteering under the adoption of practical TTDs. In contrast, our proposed beamfocusing approach can achieve continuous beamsteering with an average array gain over users higher than 0.9 at all angles.

The exploitation of the substantial bandwidths available in the terahertz (THz) band has recently attracted considerable interest. However, beam squint effect is a significant obstacle in the design of wideband hybrid beamformers. The beam squint effect causes the radiation beam to deviate from the desired direction, resulting in substantial gain losses and hindering the effective utilization of available bandwidths. Delay-phase precoding (DPP), a combination of true time delay (TTD) elements and phase shifters (PSs) in the analog domain, has emerged as a potential solution to overcome the beam squint effect and maintain practical system design. However, existing hybrid precoding schemes that assume infinite resolution and unbounded range TTDs, as well as infinite resolution PSs, impose a significant burden in terms of hardware complexity and power consumption. In this paper, we introduce the Delta-Delay-Phase Precoding (DDPP) architecture, which significantly reduces the required delay range of TTDs, outperforming existing state-of-the-art solutions in the literature. Importantly, the proposed architecture maintains consistently superior performance, even as the number of antenna elements increases, making it scalable for UM-MIMO systems. Additionally, we propose hardware-aware designs for the hybrid analog precoder to combat beam squint effect while complying with the hardware limitations of TTDs and PSs. We formulate the design of TTDs and PSs as a joint optimization problem subject to their finite-resolution constraints. To tackle this non-convex optimization problem, we propose an iterative precoding algorithm based on alternating minimization. Simulation results demonstrate the superiority of the proposed hybrid analog precoding schemes over recent literature works. Particularly, the proposed precoding schemes achieve near-optimal performance despite the hardware limitations of TTDs and PSs.

Beam squint becomes a real challenge for the conventional wideband hybrid beamformers in ultra massive multiple input multiple output (UM-MIMO) systems at Terahertz (THz) band, as it causes serious beam gain loss and, hence, impedes the full utilization of the huge vacant bandwidths at this band. With the aim of combating this effect, delay-phase precoding has emerged as an energy-efficient solution, in which a mixture of true time delay (TTD) elements and phase shifters (PSs) are proposed to convert phase-controlled analog precoding into delay-phase controlled analog precoding. Nevertheless, existing infinite-resolution and large-range TTD elements are impractical due to the hardware cost and power consumption. In this paper, we propose a joint iterative optimization of the TTD and PS values based on alternating minimization considering low-resolution and limited-range TTD elements. Simulation results reveal the supremacy and robustness of the proposed algorithm in dealing with the hardware limitations of TTDs.

In this study, the authors secure the mixed radio frequency/free space optical (FSO) relay‐aided interference aligned system using a proposed physical layer security algorithm. This algorithm reduces the quality of the received signal at the eavesdropper through two procedures. First, it minimises the data transmission power from the legitimate users and the relays. Second, it jams the eavesdropper by broadcasting artificial noise from the users and the relays. Therefore, a joint optimisation problem is formulated to degrade the received signal at the eavesdropper from the users and the relays and to maximise the jamming artificial noise power, which is solved using an iterative optimisation algorithm beside a semi‐definitive programming algorithm. Furthermore, the pre‐coding and decoding matrices of the users and the relay are designed to enable the legitimate users to cancel the artificial noise, while the eavesdropper is disabled from distinguishing the artificial noise from the real streams. Moreover, the security performance of the proposed algorithm is analysed, and the impact of the FSO link's state on the security performance is studied. The extensive simulation results show the efficiency of the proposed algorithm and illustrate the role of the FSO link's state on the security performance.

This paper proposes a novel physical layer security algorithm in interference alignment (IA) based multiuser communication system with a single amplify-and-forward (AF) relay in the coexistence of an eavesdropper that tries to hide its existence. Thus, the relay and the users cannot estimate the eavesdroppers channel state information (CSI). In the proposed algorithm, the users broadcasts artificial noise in the null of the relay at the multiple access (MAC) phase, and the relay jams the eavesdropper by broadcasting the artificial noise in the null of users at the broadcast (BC) phase. Therefore, the proposed algorithm is formulated as a joint optimization problem consisting of two semidefinite programming (SDP) problems aiming at maximizing the power of the artificial noise and preserving the quality- of-services (QoS) of the users. An iterative optimization algorithm is proposed to solve the joint problem. Extensive simulation results are provided to show the effectiveness of the proposed algorithm for IA based relaying networks.

Channel state information (CSI) acquisition is a crucial issue in downlink FDD-based massive multi-input multioutput (MIMO) networks, where the channel reciprocity is not applicable. Thus, users are expected to feedback the bestmatch quantized channels to serving transmitters. Hence, an extensively large size of the feedback overhead is needed, which is linearly scaled at each user with the number of transmit antennas at the base-station (BS). In turn, the uplink (UL) channel capacity may be consumed and the overall performance becomes fundamentally limited by the downlink (DL) channel quantization precision. An alternative CSI acquisition scheme is critically needed. In this paper, we propose a novel FDD massive MIMO system based on a spatial DL channel estimation scheme; it relies on the statistical spatial correlation of the UL and DL channel clusters, given an arbitrary frequency band gap between the UL and DL channels. A transformation matrix is constructed to precode the observed UL channel on the estimated dominant DL angles of departure. The proposed scheme significantly outperforms the recent state-of-the-art techniques, without the cost of user feedback overhead bits and prior knowledge of the channel statistics.

Using outdated channel state information (CSI) in an opportunistic relaying system (ORS) leads to wrong selection of the best relay, which substantially deteriorates its performance. In this paper, therefore, we propose a robust cooperative scheme coined opportunistic space-time coding (OSTC) to deal with the outdated CSI. A predefined number (i.e., N) of relays, instead of a single relay in ORS, are opportunistically selected from K cooperating relays. At the selected relays, N-dimensional orthogonal space-time coding is employed to encode the regenerated signals in a distributed manner. Then, N branches coded signals are simultaneously transmitted from the relays to the destination, followed by a simple maximum-likelihood decoding at the receiver. To evaluate its performance, the closed-form expressions of outage probability and ergodic capacity are derived, together with an asymptotic analysis that clarifies the achievable diversity. Analytical and numerical results reveal that a full diversity of K is reaped by the proposed scheme when the knowledge of CSI is perfect. In the presence of outdated CSI, where the diversity of ORS degrades to one, the diversity of N can be kept. Moreover, OSTC's capacity is remarkably higher than that of the existing schemes based on orthogonal transmission. From the perspective of multiplexing-diversity tradeoff, the proposed scheme is the best cooperative solution until now.

Antenna selection is a low cost solution to massive MIMO systems. There are two well-known design criteria of antenna selection in MIMO systems, i.e., maximizing MIMO capacity and maximizing post-processed Signal to Noise Ratio (SNR). This paper focuses on the latter one that can be achieved by selecting the largest Minimum Singular Value (MSV) of channel submatrices. A novel antenna selection is proposed by using the bidirectional Branch And Bound (BAB) searching algorithm to find the globally optimal channel submatrix with largest MSV. Simulation results demonstrate that, with both independent and identically distributed (i.i.d.) and sparse channels, the proposed method not only can achieve the same Bit Error Rate (BER) as the exhaustive search, but also has much lower complexity than the exhaustive search. Although the bidirectional BAB based antenna selection still has a high complexity, it can serve as a benchmark purpose for the future low complexity antenna selection design, especially when the exhaustive search is infeasible in massive MIMO systems, which is the main motivation of this paper.

In cognitive ratio (CR), spectrum sensing is a crucial technique aiming at exploiting spectrum white spaces. This sensing task is more difficult for multiple channels in wide bands. In this paper, we investigate spectrum sensing tasks for long-term evolution (LTE) networks in large frequency-bands. We propose an effective spectrum sensing scheme to detect LTE signals and classify the cell-identities transmitted in multi-channels in parallel. To prove the concept and validate the performance of the proposed scheme, a secondary LTE transmission in TV bands is modeled in our simulations. At the perspective of realistic scenarios, the identified information could be utilized for some functions such as the co-ordination among secondary networks or initial-cell-search procedures between secondary user-equipments and their serving base-stations in the secondary LTE transmission. The simulation results show that the detection and classification performance of the proposed scheme is close tightly to that in the case of a single channel. The scheme works well in multi-path fading environment with carrier frequency offset (CFO) and is tolerant to noise uncertainty.

In this paper, we investigate the resource management problem in orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) cognitive radio (CR) systems. We propose performing resource allocation based on interference alignment (IA) in order to improve the spectral efficiency of CR systems without affecting the quality of service of the primary system. IA plays a role in the proposed algorithm to enable the secondary users (SUs) to cooperate and share the available spectrum, which leads to a considerable increase in the spectral efficiency of CR systems. However, IA based spectrum sharing is restricted to a certain number of SUs per subcarrier in order to satisfy the IA feasibility conditions. Accordingly, the resource allocation problem is formulated as a mixed-integer optimization problem, which is considered an NP-hard problem. To reduce the computational complexity of the problem, a two-phases efficient sub-optimal algorithm is proposed. In the first phase, frequency-clustering is performed in order to satisfy the IA feasibility conditions, where each subcarrier is assigned to a feasible number of SUs. Whenever possible, frequency-clustering stage considers the fairness among the SUs. In the second stage, the available power is allocated among the subcarriers and SUs without violating the constraints that limit the maximum interference induced to the primary system. Simulation results show that IA with frequency-clustering achieves a significant sum rate increase compared to CR systems with orthogonal multiple access transmission techniques.

In this paper, the problem of resource allocation in overloaded orthogonal frequency division multiplexing (OFDM) based multiple-input multiple-output (MIMO) cognitive radio (CR) system is considered. The objective is to allocate the different subcarrier and distribute the available user power in order to maximize the CR system throughput. The interference induced to the primary system should not be harmful and hence, should not exceed the prescribed limit. Interference alignment (IA) technique is employed in order to achieve an efficient use of the available radio resources. Without affecting the quality of service of the primary system, IA enables the secondary users to share the available spectrum which increases the CR system degrees-of-freedom. Due to IA feasibility condition, the spectrum sharing with perfect IA is restricted to a certain number of user per subcarrier. Accordingly, the resource management problem is formulated as a mixed-integer optimization problem which is considered as an NP-hard problem. To reduce the computational complexity of the problem, a two-phase efficient sub-optimal algorithm is proposed. Frequency-clustering is performed in the first phase to the overcome IA feasibility conditions while the power is distributed among subcarriers in the second phase. Simulations show that IA technique achieves a significant sum-rate increase of CR systems compared with the traditional CR systems that use orthogonal multiple access transmission techniques.

In this paper, we propose a novel scheme coined opportunistic space-time coding (OSTC) to deal with the outdated channel state information (CSI) problem for opportunistic relay selection (ORS) systems. A pair of relays, instead of a single relay, is opportunistically selected in terms of the instantaneous CSIs. Alamouti scheme, a unique space-time code achieving both full-rate and full-diversity, is applied to encode the regenerated signals at this pair of relays. To evaluate the performance, a closed-form expression of outage probability is derived for OSTC. The analytical and simulated results reveal that a full diversity on the number of cooperating relays is achieved by OSTC when using perfect CSI. In the fast-fading channels, where the outdated CSI drastically degrades the performance of ORS and reduces its diversity order to 1 (i.e., no diversity), a cooperative diversity with an order of 2 can still be achieved by the proposed scheme. Most importantly, this performance gain comes without any sacrifice in the spectral efficiency, which is the drawback of Generalized Selection Combining schemes.

Up to now, a closed-form expression of the ergodic capacity for amplify-and-forward opportunistic relaying in the presence of outdated channel state information(CSI) is still not available in the literature. That is mainly due to the mathematical intractability in the conventional performance analysis through manipulations of probability density function (PDF). In this paper, therefore, we take advantage of a novel mathematical approach based on moment generating function (MGF) to evaluate the performance. MGF of the end-to-end signal-to-noise ratio for opportunistic relaying over independent and identically distributed Rayleigh channels with outdated CSI is given. Then, the closed-form expressions of ergodic capacity and outage probability are derived directly from MGF without any involvement of PDF. Finally, Monte-Carlo simulations are set up to corroborate the validity of the theoretical analysis.

Until now, the performance analysis of Generalized Selection Combining (GSC) applied to cooperative diversity networks in the presence of outdated channel state information (CSI) is still not available in the literature. In this paper, therefore, we derive closed-form expressions of the ergodic capacity and outage probability for amplify-and-forward GSC over independent and identically distributed Rayleigh channels. Monte-Carlo simulations are set up to corroborate the correctness of our theoretical analysis. The analytical and numerical results reveal that GSC is an effective way to combat the effect of outdated CSI. When using the perfect CSI, a full diversity on the number of all cooperating relays K is available. With the outdated CSI, where the performance of the conventional opportunistic relaying drastically degrades and its diversity order is limited to 1 (i.e., no diversity), a diversity order on the number of selected relays N can still be achieved. However, the performance gain on the diversity comes at the price of sacrifice in the spectral efficiency.

To combat the bottleneck effect in the relay channels, this paper proposes a simple power-control algorithm for decode-and-forward cooperative networks with opportunistic relay selection. Taking advantage of the existing channel state information, which is a by-product during the process of relay selection, an optimal power allocation factor can be easily figured out. This factor is quantized into a few control bits and then fed back to the source via the existing feedback channel, i.e., the flag packet. Using the channel capacity and outage probability as metrics, the theoretical analysis and Monte-Carlo simulation corroborate that such distributed power allocation between the source and the best relay can effectively boost the system performance. Most importantly, this performance gain comes at almost no price due to just reusing the existing CSI and flag packet.

In this paper, we propose a robust spectrum sensing scheme which can reliably detect signals in multiple channels within short observation time at the cost of low computational complexity. The scheme consists of two parts. The first part is the signal detection algorithm essentially based on the crosscorrelation of the feature sequence generated utilizing the signal's periodical pilot structure, which is further enhanced in terms of reducing sensitivity to clock mismatch and mitigating the noise uncertainty problem. The second part is the filter bank realized using the polyphase network (PPN) structure, which enables the simultaneous sensing of multiple wideband channels with low complexity which is favourable for the reduction of implementation cost and power consumption, especially for mobile terminals. In addition to the simulations for performance evaluation under practical conditions, the proposed spectrum sensing scheme is validated using the 8-channel wideband signal captured in UHF TV band. The visualized crosscorrelation values from both measurement and simulation are perfectly matched, which successfully confirms the effectiveness and feasibility of the proposed spectrum sensing scheme in real-world implementation.

Linear least squares (LLS) estimation is a suboptimum but low-complexity localization method based on measurements of location-related parameters. It has been proved that selection of the reference anchor influences the LLS localization accuracy. In addition, hybridization of different types of measurements can fix the deficiencies of one type of measurements. In this paper, we proposed a new reference selection criterion for the hybrid TOA/RSS LLS localization technique (called H-LLSRS), which considers both measured ranges and the information about their coarse variances. Moreover, we consider a general scenario that variances of range measurements are different, and derive a weighted LLS (WLLS) estimator for hybrid TOA/RSS localization according to the information about the accurate ranging variances and the correlations among the observations. Simulation results show that if the RSS-based ranging variances are considerably larger than the TOA-based ranging variances, the H-LLS-RS localization technique yields better accuracy than the conventional LLS localization techniques. Furthermore, reference selection has no effect on the accuracy of WLLS localization technique.

A new modulation scheme combing GMSK with direct-sequence spread spectrum (DSSS) and differential modulation is proposed in this paper, which is named DS-DGMSK. The demodulation can achieve BER performance comparable to DBPSK while the bandwidth efficiency and power efficiency are higher thanks to GMSK. By combining with spread spectrum and differential demodulation, the scheme is robust at low SINR and high moving speed without accurate carrier frequency recovery. It can be further enhanced by differential space-time modulation (DSTM) giving transmit diversity which further improves robustness. The proposed modulation is suitable for low-bitrate mobile data link which requires high robustness, low complexity and nonlinear power amplifier which is low-cost and less power-consuming.

This paper considers the existence of sidelobe emission in OFDM based rich-Femtocell systems. By modeling the interference from the arbitrary-distributed Femtocells as shot-noise process, the paper analyzes the effect of sidelobe interference on the system performance metrics such as transmission capacity (TC) and area spectral efficiency (ASE). The numerical results calculated for three different OFDM schemes show that, under the circumstance of very high Femto deployment intensity, the rigorous constraints on first-tier, namely the Macrocell outage probability and the reduction of first-tier ASE, prohibit the Femtocells from excessive subband access. Thus the out-of-band emissions contribute significantly to the system performance loss. Further analysis has shown that poor channel condition can even worsen the situation, making the existence of sidelobe interference not ignorable. Among the three schemes, OQAM-OFDM is proved to achieve the best performance. Although OQAM-OFDM has higher requirements of implementation, it is reasonable to be considered as one of the candidate transmission schemes for future Femtocell applications.

This paper introduces new joint estimation methods of multiple carrier frequency offsets (CFOs) and channel impulse responses (CIR) in application to multiuser orthogonal frequency division multiplexing (OFDM) systems. The estimators are derived from the optimal maximum-likelihood (ML) principle. Complexity reductions are achieved by exploiting the correlation properties of the training sequence (TS). The grid search algorithm is converted into a polynomial root finding procedure which leads to low-complexity closed-form estimators for moderate CFOs. Furthermore, iterative estimators for larger CFOs are proposed. Numerical results confirm that the performance degradation due to the approximations compared to the Cramer-Rao bound (CRB) is small and may be negligible in practice.

Orthogonal frequency division multiplexing (OFDM) signals are sensitive to the mismatching errors between the in-phase (I) and quadrature (Q) branches in the up and down-conversions. These mismatching errors including phase and amplitude mismatches make the signal constellation expand and rotate, which severely degrades the performance of OFDM systems. In this paper, a method of signal design for OFDM communication system is proposed in order to mitigate the impact of IQ mismatching errors. A simple quasi-symmetric conjugate (QSC) structure of signal in frequency domain designed at the transmitter side can completely remove the self-interference caused by IQ mismatching errors. At the receiver, the estimation and the compensation for IQ mismatch are not necessary. Analytic and simulation results can show the efficiency of QSC method in IQ mismatch mitigation compared to other techniques such as Adjacent Symbol Repetition (ASR), Adjacent Conjugate Symbol Repetition (ACSR), Symmetric Symbol Repetition (SSR), or Symmetric Conjugate Symbol Repetition (SCSR), respectively.

In order to coexist with existing legacy wireless systems, the transmit power spectral density (PSD) of ultra-wideband (UWB) impulse radio systems is limited. The coverage range of the UWB systems is then confined within a few meters. One possible way to achieve a greater coverage is a short-range multihop relaying strategy. This paper proposes a two-hop UWB relay system using multiple detect-and-forward relays, each of which is equipped with multiple antennas. Each multiple-antenna relay performs spatial diversity reception with partial-Rake scheme in the first hop, and decides whether or not to perform spatial transmit diversity with partial-pre-Rake scheme in the second hop. This leads not only to low complexity at the receiver, but also to reduced error propagation. Moreover, we derive the outage probability of the proposed relay system based on the IEEE 802.15.3a channel model. The effects of using multiple relay antennas, relays, and Rake/pre-Rake fingers on the outage performance are demonstrated. The tradeoffs among the numbers of relay antennas, relays, and Rake/pre-Rake fingers are also investigated. Numerical results show that it is best to use multiple relay antennas to improve the outage performance of the proposed system. Furthermore, in general, increasing the number of relays is more beneficial than increasing the number of Rake/pre-Rake fingers.

An antenna selection scheme for multi-input multi-output (MIMO) ultra-wide band (UWB) communication system with time reversal (TR) is investigated in this paper. The system exploits spatial multiplexing (SM) scheme to achieve high data rate. In order to cope with long delay spread of the UWB channel, time reversal technique is adopted. TR can mitigate not only the interference intersymbol (ISI) but also multi stream interference (MSI) caused by transmitting several data streams simultaneously. Antenna selection algorithm allows to reduce the number of transmit antenna by using the channel state information (CSI), which is already available for time reversal. Simulation results show that the algorithm can considerably improve the BER performance of the system when the number of diversity branch is not so large.

Non-line-of-sight propagation in wireless localization systems leads to a challenging problem for the estimation of a mobile position. A hybrid idea has been considered as a promising approach to increase estimation accuracy. Existing methods, however, are formulated using separate measurements, necessitating different observation quantities, e.g. received signal and received signal strength, thus making the parameter estimation cumbersome. In this paper, we propose a new hybrid wireless geolocation model requiring only one observation quantity, namely the received signal. The attenuation model for transmit power from base stations is explored herein to capture propagation features in the received signal model. Fortunately, it also provides a more realistic approach to wireless geolocation. To investigate geolocation accuracy, the Cramer-Rao bound (CRB) is derived for the estimation error of the mobile position. For any value of path loss exponent, the obtained result provides a generalized form of the CRB for the usual time delay case. In small cells, e.g. office building picocells, numerical examples illustrate that the accuracy of mobile position estimation exploring path loss is improved comparing with that provided by the usual time delay method.

The mobile position estimation using time-of-arrival (ToA) is considered for the wireless NLoS geolocation exploring a signal strength(SS) based on path loss. As exploited the path attenuation, a hybrid SS-ToA approach indicates a performance improvement compared with the usual ToA method. To realize this prospect, it calls for an estimator to determine the mobile position from the time delay. In this paper, we show that the use of line-of-sight (LoS) time delay provides the same performance as that given by using both the LoS and non-LoS (NLoS) time delays. We then propose least squares (LS), weighted least squares (WLS) and maximum likelihood (ML) to estimate the mobile position. Theoretical performance of the LS and WLS is analyzed. It reveals that for different LoS time delay error variances, the LS error variance is larger than the WLS error variance, which is equal to the Cramer-Rao bound (CRB). Numerical results illustrate that the time delay performance analysis is accurate when the time delay estimate is close to its true value, i.e. for small time delay error variance. For high SNR and large effective bandwidth, the LS cannot provide the performance compared with the CRB, whereas the WLS and ML are statistically efficient.

Ultra-wide-band (UWB) technology combined with multiple transmit and receive antennas (MIMO) is a viable way to achieve data rates of more than 1 Gb/s for wireless communications. UWB is typically applied to short-range and therefore mainly indoor communications in environments characterized usually by dense multipath propagation. For this type of environment, MIMO systems allow for a substantial increase of spectral efficiency by exploiting the inherent array gain and spatial multiplexing gain of the systems. In this paper, we provide a brief overview for UWB-MIMO wireless technology. The overview covers channel capacity, space-time coding (STC), and beamforming. It is shown that the spectral efficiency is increased logarithmically and linearly,respectively, for single transmit and multiple receive antennas (SIMO) and MIMO systems. For multiple transmit and single receive antenna (MISO) systems, a threshold for the data transmission rate exists such that the spatial multiplexing gain can be obtained if the data rate is lower than this threshold, but it is not beneficial to deploy multiple transmit antennas if the required data rate is higher than the threshold. Two STC schemes for UWB-MIMO are briefly discussed, and their performance comparison is presented. A discussion about antenna selection is also presented, and the performance comparison between antenna selection and equal gain combiner is provided showing the diversity gain for some scenarios. For the beamforming, it is shown that the optimal beamformer is obtained if all the weighting filters in each antenna branch are identical. About the optimal beamformer, it is found that the amplitude of the side lobe is independent of the ray incidence angle, and the amplitude of the main lobe is increased by a fold of the element number in the array. Three kinds of beam patterns are defined, and the beamwidth of the main lobe is given. Experimental results based on an offline testbed are provided to verify some analytical results presented in this paper. Since UWB-MIMO is still in its research infancy, the aim of this paper is to present some first results on spatial multiplexing, STC, and beamforming to illustrate the potential of UWB-MIMO.

In this paper, we present detect-and-forward relaying approaches for a coherent ultra-wideband (UWB) detection (specifically selective-Rake reception) system and for a noncoherent UWB detection (specifically differential transmittedreference, DTR) system in order to achieve greater coverage in multipath fading channels. Multiple-antenna relay system are also proposed to further enhance the overall system performance. The corresponding bit error rate (BER) performance is evaluated theoretically and via simulations. The effect of some design factors on this performance is investigated. Analytical and simulation results verify the performance improvement of the proposed relay systems over the direct transmission systems.

Usually, centralized channel state information (CSI) is assumed to exploit the multiuser diversity with a smart transmission scheduler. However, such centralized CSI can be impractical for a broadband wireless communication system with a large number of mobile users (MUs). In this paper, we propose a decentralized method to exploit the multiuser diversity in a single cell scenario with orthogonal frequency-division multiplexing (OFDM) based downlink. The central part of our approach is the channel-aware ALOHA-based OFDM subcarrier assignment. According to it, each MU measures the channel at all OFDM subcarriers and tries to obtain proper ones by sending a service-request packet through the corresponding orthogonal uplink subchannel. This packet is sent when the measured channel-fading level exceeds a predetermined threshold xi. The base station processes these request packets with a collision-reception model, and assigns the corresponding subcarrier(s) to the MU whose request packet has been successfully received. Two implementation algorithms are developed, by solving the problem of optimization of xi under different system configurations. Computer simulations show that in comparison with the standard round-robin method, the proposed algorithms offer a substantial data-rate improvement, especially when the correlation property of the OFDM subcarriers is properly exploited

The purpose of this paper is to account for estimating the MIMO channel parameters in the presence of stochastically correlated signals, spatial scattering and Ricean fading. A parametric framework based on the second-order statistic is developed herein. As manipulated a few of reduced parameterizations, we derive an explicit form of the array covariance matrix, an alternative expression of the Cramer-Rao bound (CRB), and two asymptotically efficient estimators. Numerical simulation is conducted to demonstrate the estimation possibility of three important parameters in wireless communication, such as the nominal direction, the angular spread and the generalized Rice factor. It appears that for a large number of temporal snapshots, the performance of both estimators can attain the CRB, while the asymptotic maximum likelihood estimator outperforms the weighted least squares criterion in non-asymptotic region.

Usually, centralized channel state information (CSI) is assumed to pursue the multiuser diversity with a smart transmission scheduler. However, such centralized CSI will be impractical for a broadband system with a huge number of mobile users. In this paper, by concentrating on an orthogonal frequency division multiplex (OFDM) based broadband wireless communication system, a decentralized method to pursue multiuser diversity is proposed. The key in our proposal is the channel-aware ALOHA based subcarrier assignment: Each mobile user measures the channel on all subcarriers and tries to capture particular ones, by transmitting a request packet with probability p on these subcarriers, when it believes that its channels are good enough (e.g., when the measured channel fading level exceeds a predetermined threshold /spl gamma/). Several implementation schemes are developed, by attacking the optimization of p and /spl gamma/ with objective functions based on the downlink sum throughput. Computer simulations show that in comparison with the round-robin scheme, the developed schemes offer quite distinct throughput benefit and some further throughput improvement can be obtained when the correlation among the subcarrier channel gains is exploited with a subcarrier merging technique.