As a novel communication pattern, non-reciprocal beams employ narrow-width beams to transmit signals and wide-width beams to receive, which can achieve fast beam alignment quickly. To fully understand the channel characterization, we investigate the mmWave propagation path loss (PL) over this special pattern. First, we present a beam-filtered power angular spectrum (PAS) simulation method based on the 3GPP. Specifically, the main lobe width-related beam gain is used to shape the generated PAS. On this basis, we consider two cases, i.e., perfect beam alignment and misalignment. For the first case, we propose a novel exponential decay PL model instead of the inversely proportional relationship. Furthermore, we verify our proposal based on the measured data of 28GHz and the results show that it yields a smaller fitting root mean square error (RMSE). Regarding the latter case, we find that the beam steering-based additional PL can be regarded as the superposition of a deterministic Gaussian function and a stochastic Gaussian noise. Our findings provide insightful references for the implementation of beamwidth-dependent nonreciprocal beam patterns.

Heterogeneous cellular networks (HCNs) constitute a necessary step in the evolution of cellular networks. In this paper, we apply the signal-to-interference ratio (SIR) meta distribution framework for a refined SIR performance analysis of HCNs, focusing on K-tier heterogeneous cellular networks based on the homogeneous independent Poisson point process (PPP) model, with range expansion bias (offloading bias) in each tier. Expressions for the b-th moment of the conditional success probability for both the entire network and each tier are derived, based on which the exact meta distributions and the beta approximations are evaluated and compared. Key performance metrics, including the mean success probability, the variance of the conditional success probability, the mean local delay, and the asymptotic SIR gains of each tier are obtained. The results show that the biases are detrimental to the overall mean success probability of the whole network and that the b-th moment curve of the conditional success probability of each tier can be tightly approximated by the horizontal shifted versions of the first moment curve of the single-tier PPP network. We also provide lower bounds for the region of the active probabilities of the base stations to keep the mean local delay of each tier finite.

The meta distribution of the signal-to-interference ratio (SIR) provides fine-grained information about the performance of individual links in a wireless network. This paper focuses on the analysis of the meta distribution of the SIR for both the cellular network uplink and downlink with fractional power control. For the uplink scenario, an approximation of the interfering user point process with a non-homogeneous Poisson point process is used. The moments of the meta distribution for both scenarios are calculated. Some bounds, the analytical expression, the mean local delay, and the beta approximation of the meta distribution are provided. The results give interesting insights into the effect of the power control in both the uplink and downlink. Detailed simulations show that the approximations made in the analysis are well justified.

Channel measurements are the precondition for the design of future high-speed railway (HSR) communication systems. Due to the measurement restriction and measurement efficiency issues of applying conventional channel sounders in HSR scenarios, railway network based channel sounding methods are becoming quite attractive. In this paper, we employ long term evolution (LTE) railway network to achieve HSR channel measurements. A novel LTE-based HSR channel sounding system is proposed to enable the collection of time-frequency-space channel data. Field measurements that consider both direct and relay coverage schemes are conducted on Beijing to Tianjin HSR in China. Measurement data are partitioned into singlelink case in which the common channel parameters can be derived and multi- link case in which the correlation between different links can be characterized. Measurement results cover path loss (PL), Ricean K-factor, delay spread, single-link and multi-link spatial correlation, which not only confirm the utility of the proposed system but also provide preliminary channel information available for the study of next generation HSR communication systems.

In this paper, we investigate maximum likelihood equalization (MLE) for a large-scale antenna (LSA) system with single-carrier (SC) modulation over Rician fading channels. Orthogonal frequency division multiplexing (OFDM) is usually used to deal with frequency selectivity of wireless channels. However, for a wireless system with large-scale antennas in a Rayleigh fading channel, by combining the received signals through a matched filter (MF), the frequency selective channel can be converted into a frequency flat channel. As a result, SC modulation can be used directly with a simple one-tap equalizer. In a Rician fading channel, however, the line-of-sight (LOS) path will cause mutliuser-interference (MUI), which cannot be mitigated through MF. As a result, the simple one-tap equalizer leads to an error-floor when the signal-to-noise ratio (SNR) is large. In this paper, MLE is used to improve system performance through multiuser detection. From both theoretical analysis and simulation results, the proposed approach can eliminate the error floor and outperform existing approach.

In this paper, a semi-empirical multiple-input multiple-output (MIMO) channel model is proposed for highspeed railway (HSR) viaduct scenarios. The proposed MIMO model is based on single-input single-output (SISO) wideband channel measurements under a viaduct on Zhengzhou-Xi'an HSR in China and a geometry-based stochastic model (GBSM) composed of a one-ring model and an elliptical model. Environment-related parameters in the GBSM are determined by the measured temporal fading characteristics such as K-factor and Doppler power spectral density (PSD). Close agreement is achieved between the model results and measured data. Finally, a deterministic simulation model is established to perform the analysis of the space-time correlation function, the space-Doppler PSD and the channel capacity. This model is more realistic and is particularly beneficial for the performance evaluation of MIMO systems in HSR environment.

Energy efficiency is becoming an increasingly important topic in green communications. In this paper, we study the energy-efficient utility-based resource allocation in an orthogonal frequency division multiple access (OFDMA) network with heterogeneous services. We propose energy-efficient utilities for various services describing the user satisfaction per energy consumption for transmission. An effective subcarrier and power allocation algorithm named energy-efficient utility-based algorithm (EEUBA) is proposed to maximize the energy-efficient utility of the system under quality-of-service (QoS) constraints of the QoS users. In the simulation, we compare the performance between the proposed algorithm with spectral efficient utility-based algorithms; and the results show that the proposed algorithm can bring improvements on energy-efficient utility as well as energy efficiency.

The increasing needs of mobile internet application services running on smartphone is driving the evolution of wireless communication networks, due to the diversity of traffic characteristics in addition to the rapid growth of data volumes. Differently from typical internet services like web browsing and FTP, the pervasive usage of always-on applications can lead to frequent User Equipment (UE) transitions between Radio Resource Control (RRC) states, and result in excessive signaling traffic that need to be accounted in network capacity planning. In this paper, we propose a novel traffic generation framework to obtain the traffic flows generated by a smartphone which is running heterogeneous applications including both typical applications which are selected on the basis of a proposed application level traffic growth forecast, and keep-alive messages from always-on applications. Using such a framework, the radio resource consumed by different types of application can be evaluated. We exemplify the use of the proposed traffic modeling with a case study of a year-by-year radio resource consumption of voice traffic and keep-alive messages in a realistic LTE (Long Term Evolution) network scenario.

Based on wideband radio channel measurements with a bandwidth of up to 50 MHz at 2.35 GHz in a U-shape cutting environment, we analyze the Ricean K-factor for high-speed railway communications. Three types of the K-factor, consisting of narrowband, wideband and delay K-factor, are extracted according to the measured channel responses by using the channel partitioning and combining method. Due to the rich reflecting and scattering components in the U-shape cutting scenario, the K-factor dramatically changes with the frequency. A distance-based statistical narrowband K-factor model covering the frequency variability is proposed. The channel bandwidth dependent property of the wideband K-factor is observed and then a bandwidth-based statistical wideband K-factor model is developed. Moreover, it is found that the K-factor just exists at the beginning of the delay bins in the deep U-shape cutting scenario. These results are provided for use in system design and channel modeling of high-speed railway communications.

A dynamic resource allocation algorithm is investigated for the orthogonal frequency division multiplexing access (OFMDA) system under the network architecture of High-Speed Railway (HSR). The mobile base station (MBS) on the top of the train forwards the signal received from the base station (BS) on the ground to the user equipments (UE) in the train. Due to the high mobility in the BS-MBS link, the inter-carrier interference (ICI) caused by the Doppler shift may degrade the system performance. In this paper, we aim to combat the influence of the ICI to improve the system capacity by means of the resource allocation, which includes subcarrier allocation, subcarrier pairing and power allocation. Simulation results demonstrate that the proposed resource allocation algorithm can improve the system performance dramatically.

The performance of high‐speed railway wireless communication systems is studied in the presence of co‐channel interference and imperfect channel estimation in the uplink. The authors derive exact closed‐form expressions for the outage probability and investigate the impact of fading severity. New explicit expressions are derived for both the level crossing rate and average outage duration for illustrating the impact of mobile speed and channel estimation errors on the achievable system performance. Our results are generalised and hence they subsume a range of previously reported results.

Iterative channel estimation (ICE) usually exploits soft information of unknown data symbols as references to improve estimation performance. This paper investigates ICE for orthogonal frequency division multiplexing (OFDM) over wireless channels. The optimum ICE is derived in terms of maximum a posteriori (MAP) criterion, which can be solved using fixed-point iteration (FPI). Furthermore, the derived MAP ICE is closely related to the well-known expectation-maximization (EM) estimation. We also demonstrate that the MAP ICE converges within only one step when the signal-to-noise ratio (SNR) is large through analysis and simulation results.

This paper investigates iterative channel estimation (ICE) for orthogonal frequency-division multiplexing (OFDM) with multiple transmit antennas. To improve performance of channel estimation, we exploit the soft information of unknown data symbols on both the expected transmit antenna and the interfering transmit antenna. Maximum a posteriori (MAP)-based ICE is derived and is implemented using the fixed-point iteration (FPI). For an OFDM system with multiple transmit antennas, the proposed MAP-based ICE suggests a harmonic-average-based soft symbol on the expected transmit antenna while an arithmetic-average-based soft symbol on the interfering transmit antennas. Similar to an OFDM system with a single transmit antenna, MAP-based ICE can achieve the Cramer-Rao bound (CRB) within only one iteration, when the signal-to-noise ratio (SNR) is large enough.

The Gallager's random coding error exponent for space-time block codes (STBC) over multiple-input multiple-output (MIMO) block-fading channels, with Gaussian input distribution, is investigated. Gallager's error exponent can be used to determine the required codeword length to achieve a prescribed error probability at a given rate below the channel capacity. We first provide new, analytical expressions for Gallager's exponent of STBC systems over η-μ fading channels. The Shannon capacity and cutoff rate, which can be directly derived from Gallager's exponent, are further examined. In order to get additional insights, a high signal-to-noise ratio analysis is pursued to investigate the effects of coherence time and codeword length on the error probability. For the sake of completeness, we provide the link to previous known results on Rayleigh and Nakagami-m fading channels.

In this paper, we analytically investigate the achievable rate of multiple-input single-output (MISO) channels in the presence of delay constraints. In particular, we focus on the so-called effective rate which was recently established as a suitable metric for assessing the impact of delay constraints on the overall performance of communication systems. Yet, most prior relevant works have considered only the typical cases of Rayleigh, Rician and Nakagami-m fading which allow for tractable manipulations. In this paper, we relax this assumption by considering MISO systems over η-μ fading channels. The η-μ distribution has been shown to provide very good fit to experimental data in various propagation environments. New, analytical expressions for the exact effective rate are derived. Moreover, we consider the asymptotically high and low signal-to-noise (SNR) regimes, for which tractable, closed-form effective rate expressions are presented. These results enable us to explicitly investigate the impact of system parameters on the effective rate of MISO η-μ fading channels.

In this paper, we present a novel indoor propagation model for use in a wireless LAN (WLAN) based fingerprinting localization system. This model is based on a derivation of the free space propagation model taking into account the penetration loss and geographic propagation factors in different regions of the indoor structure. The objective of the model is to reconstruct the collected sparse fingerprinting database, eliminating the workload in the offline data collection phase. In the online phase, weighted K-nearest neighbor (WKNN) is adopted to obtain the final location estimation. We have carried out various experiments in a real-world setup to show the performance improvement of the proposed algorithm. Results show that proposed propagation model obtains more accurate prediction of the received signal strength values than other traditional models, delivering a high localization accuracy of up to 1.4 meter.

For the design and performance evaluation of broadband wireless communication systems in High-Speed Railway (HSR) environments, it is of crucial importance to have accurate and realistic propagation channel model. Based on real measurement data in U-Shape Groove (USG) scenarios at 2.35 GHz on Zhengzhou-Xi'an (ZX) HSR in China, the channel fading characteristics such as path loss, shadowing, K factor, time dispersivity and Doppler effects are specialized. These technical guidelines will promote the development of the wireless communication system under HSR.

Keep-alive messages generated from always-on type applications on smartphones can lead to frequent transitions between Long Term Evolution (LTE) Radio Resource Control (RRC) states, pushing significant increase of signaling traffic. In this paper, we investigate the performance of signaling overhead caused by keep-alive messages based on LTE RRC state transition procedure for various RRC inactivity timer settings. We propose a series of metrics for evaluating the signaling load in terms of system resource consumption on data and control channels for both uplink and downlink. The results show that although the RRC signaling overhead make keep-alive messages transmission with low efficiency, it will not consume the system resource dramatically and overload LTE network. The results also show that proper inactivity timer setting will reduce the signaling overhead and improve the efficiency of keep-alive messages transmission.

This paper studies a novel broadband wireless channel sounding scheme for High-Speed Railway (HSR) scenarios. The proposed scheme employs the downlink signal of Long Term Evolution (LTE) as the excitation signal to acquire the channel impulse responses (CIR) based on the frequency domain method. Then, channel characteristics such as time delay spread, Doppler frequency feature, spatial correlation and directions of departure and arrival can be obtained by the post-processing algorithms. Finally, the verification is performed by comparing the predefined channel models with the derived results.

Fingerprinting localization techniques have been intensively studied in indoor WLAN environment. Artificial neural networks (ANN) based fingerprinting technique could potentially provide high accuracy and robust performance. However, it has the limitations of slow convergence, high complexity and large memory storage requirement, which are the bottlenecks of its wide application, especially in the case of a large-scale indoor environment and the terminal with limited computing capability and memory resources. In this paper, we firstly introduce affinity propagation (AP) clustering algorithm to reduce the computation cost and memory overhead, and then explore the properties of radio basis function (RBF) neural networks that may affect the accuracy of the proposed fingerprinting localization systems. We carry out various experiments in a real-world setup where multiple access points are present. The detailed comparison results reveal how the clustering algorithm and the neural networks affect the performance of the proposed algorithms.

In this paper, we analytically investigate Gallager's exponent for space-time block codes over multiple-input multiple-output block-fading channels with Gaussian input distribution. As a suitable metric of the fundamental tradeoff between communication reliability and information rate, Gallager's exponent can be used to determine the required codeword length to achieve a prescribed error probability at a given rate below the channel capacity. We assume that the receiver has full channel state information (CSI), while the transmitter has no CSI and performs equal power allocation across all transmit antennas. In the following, novel exact expressions for Gallager's exponent are derived for two well-known channel fading models, namely η-μ and κ-μ fading models. More importantly, the implications of fading parameters and channel coherence time on Gallager's exponent are investigated. In addition, we present new expressions for the Shannon capacity, cutoff rate and expurgated exponent for the above mentioned fading models, while in the high signal-to-noise ratio regime, simplified closed-form expressions are also derived. Finally, we highlight the fact that the presented analysis encompasses all previously known results on Nakagami-m, Rician, Rayleigh and Hoyt fading channels, as special cases.

With the increasing of physical-layer (PHY) data rate in modern wireless local area networks (WLANs) (e.g., 802.11n), the overhead of media access control (MAC) progressively degrades data throughput efficiency. This trend reflects a fundamental aspect of the current MAC protocol, which allocates the channel as a single resource at a time. This paper argues that, in a high data rate WLAN, the channel should be divided into separate subchannels whose width is commensurate with the PHY data rate and typical frame size. Multiple stations can then contend for and use subchannels simultaneously according to their traffic demands, thereby increasing overall efficiency. We introduce FICA, a fine-grained channel access method that embodies this approach to media access using two novel techniques. First, it proposes a new PHY architecture based on orthogonal frequency division multiplexing (OFDM) that retains orthogonality among subchannels while relying solely on the coordination mechanisms in existing WLAN, carrier sensing and broadcasting. Second, FICA employs a frequency-domain contention method that uses physical-layer Request to Send/Clear to Send (RTS/CTS) signaling and frequency domain backoff to efficiently coordinate subchannel access. We have implemented FICA, both MAC and PHY layers, using a software radio platform, and our experiments demonstrate the feasibility of the FICA design. Furthermore, our simulation results show FICA can improve the efficiency of WLANs from a few percent to 600% compared to existing 802.11.

We have developed a new cross-layer scheme, which can efficiently characterize the interactions across five layers. The optimization problem is formulated, so as to maximize the weighted sum utility, subject to constraints coupling different layers. We give a mathematical characterization of these layers and formulate a mixed integer nonlinear program (MINLP) problem. The optimization problem is non-deterministic polynomial-time hard (NP-hard). In this paper, we propose a greedy-based heuristics algorithm. Simulation results show that the proposed heuristic scheme can achieve system throughput very close to the upper bound of the optimal solution in the moderate-scale network, and higher than those of the simple cross-layer design (SCLD) scheme and the no CLD scheme in the large-scale network.

The majority of the location estimation error in wireless communication systems comes from the effect of non-line-of-sight (NLOS) propagation. NLOS identification and correction are the main techniques of mitigating the NLOS impact on positioning accuracy. In this paper, we propose a cooperative localization algorithm that combines the hybrid time of arrival (TOA) / angle of arrival (AOA) measurements of all identified Line-of-Sight (LOS) base station (BS) - mobile station (MS) links with the TOA measurements of MS-MS links. Different cost functions are described according to the NLOS detection results based on existing identification methods. A NLOS correction model is also presented when the destination MS to be located is completely in NLOS propagation, whereas some BS - cooperative MS links are in LOS conditions. Simulation results demonstrate that the proposed algorithm outperforms other existing hybrid localization techniques, and its accuracy increases with the number of LOS BS-MS links, as well as the NLOS detection accuracy.

The paper describes the measurement campaigns for the broadband channel properties under the high- speed condition, which have been carried out on Zhengzhou to Xi'an (ZX) High-Speed Railway and Beijing to Tianjin (BT) High-Speed Railway. WCDMA with the bandwidth of 3.84MHz is employed as the excitation signal that is transmitted from the base station along the railway and received by the TSMQ by ROHDE & SCHWARZ inside the train. Different scenarios including plain, U-shape cutting, station and hilly terrain are chosen in the measurements and the parameters about the channel multipath properties are extracted, analyzed and briefly reported here. These results are informative for the system designers in the future wireless communication of High-Speed Railway.

A timing synchronisation method for orthogonal frequency division multiplexing (OFDM) using improved cross-correlation (ICC) is proposed in this study. The proposed method is derived in terms of maximum-a-posteriori (MAP) criterion over an additive white Gaussian noise (AWGN) channel. In this way, the proposed ICC method is able to take into consideration the surrounded data signals, which is not considered in the conventional cross-correlation (CCC) method and thus the timing accuracy is improved accordingly. Compared to the CCC method, the ICC method only appends a correction term to the cross-correlator output, which can be easily implemented using an iterative method. Therefore the complexity of the proposed ICC method has no significant increase. Simulation results show that the proposed ICC method significantly outperforms the CCC based timing method.

The recent growing interest for indoor Location-Based Services (LBSs) has created a need for more accurate and real-time indoor positioning solutions. The sparse nature of location finding makes the theory of Compressive Sensing (CS) desirable for accurate indoor positioning using Received Signal Strength (RSS) from Wireless Local Area Network (WLAN) Access Points (APs). We propose an accurate RSS-based indoor positioning system using the theory of compressive sensing, which is a method to recover sparse signals from a small number of noisy measurements by solving an `1-minimization problem. Our location estimator consists of a coarse localizer, where the RSS is compared to a number of clusters to detect in which cluster the node is located, followed by a fine localization step, using the theory of compressive sensing, to further refine the location estimation. We have investigated different coarse localization schemes and AP selection approaches to increase the accuracy. We also show that the CS theory can be used to reconstruct the RSS radio map from measurements at only a small number of fingerprints, reducing the number of measurements significantly. We have implemented the proposed system on a WiFi-integrated mobile device and have evaluated the performance. Experimental results indicate that the proposed system leads to substantial improvement on localization accuracy and complexity over the widely used traditional fingerprinting methods.

This study deals with signal transmission and reception over a fast-fading wireless environment. Conventional methods usually consider the rapid change of channel to be harmful, which may decrease the performance of existing systems. There are also methods proposed to make use of the cause of degradation in existing systems – Doppler spread – to provide additional diversity, at the cost of folds increased complexity. In this study, the authors focus on exploiting the array gains provided by the fast-fading wireless channel multipath array gain (MAG) and Doppler array gain (DAG). The conceptions of MAG and DAG are straightforward extensions of the conception of array gain in multi-antenna systems. For methods which exploit multipath and Doppler diversities, complex signal processing is required at the receiver side, leading to a great increase in complexity. The MAG and DAG can be easily obtained using simple transmit waveform design. Therefore, no extra computational load is required. Both analytical and simulation results show that, with the same computational complexity, the proposed methods can significantly outperform the conventional ones.

In this paper, the performance of multi-level quadrature amplitude modulation (M-QAM) systems is studied analytically when Alamouti space-time transmit diversity (STTD) coding is used for transmission over Rayleigh fading channels. The effect of self-interference (interference from another simultaneously transmitted symbol in the STTD scheme for the same user) due to imperfect channel estimation is investigated. Based on the characteristic function method, a closed-form expression of the bit error rate (BER) is derived. Numerical results for 16/64-QAM show that, with the Alamouti STTD technique, the BER performance of the QAM system can be improved significantly. The effect of receive antenna diversity is also investigated. It is shown that high-order QAM constellations can be employed even in low signal to noise ratio (SNR) with the transmit diversity technique in conjunction with receive antenna diversity.

The low rank feature of location estimation in Wireless Sensor Networks (WSNs) makes it feasible to use nuclear norm minimization as an accurate and fast solution for low-dimensional embedding problems. In this paper, a novel localization algorithm for WSNs is proposed by using nuclear norm for rank minimization. We formulate the location finding problem from only a small fraction of random entries of Euclidean Distance Matrix (EDM) as a low-rank matrix recovery problem, subject to a set of linear equality constraints. We show that a measurement matrix using orthogonal projection obeys the RIP and thus, supports a sufficient condition for the recovery of the low-rank matrix with overwhelming probability. For simplicity, Singular Value Thresholding (SVT) algorithm, a standard convex optimization approach, is used for the nuclear norm minimization. Simulation results demonstrate that in a 100 m × 100 m area, for a small scale network with 100 nodes, only 20% of measurements is needed to achieve a 0.5 m localization error, while 3% needed to achieve a 0.05 m error for a comparatively large scale network with 1000 nodes.

Link evaluation is very important to system level simulation. Current algorithms for link evaluation show pretty good accuracy for wireless system with linear detections. However, when it comes to MIMO-OFDM system with ML Detection, problems still exists. This paper proposes an Extended Received Block Information Rate algorithm for link evaluation, which is deduced from the view of information and detecting theory. Accuracy and universality of this algorithm for MIMO-OFDM system with ML detection are highlighted. Simulation results show that, comparing to current algorithms for link evaluation, the proposed ERBIR algorithm obtains better accuracy and universality.

The sparse nature of location finding problem makes the theory of compressive sensing desirable for indoor positioning in Wireless Local Area Networks (WLANs). In this paper, we address the received signal strength (RSS)-based localization problem in WLANs using the theory of compressive sensing (CS), which offers accurate recovery of sparse signals from a small number of measurements by solving an ¿1-minimization problem. A pre-processing procedure of orthogonalization is used to induce incoherence needed in the CS theory. In order to mitigate the effects of RSS variations due to channel impediments, the proposed positioning system consists of two steps: coarse localization by exploiting affinity propagation, and fine localization by the CS theory. In the fine localization stage, access point selection problem is studied to further increase the accuracy. We implement the positioning system on a WiFi-integrated mobile device (HP iPAQ hx4700 with Windows Mobile 2003 Pocket PC) to evaluate the performance. Experimental results indicate that the proposed system leads to substantial improvements on localization accuracy and complexity over the widely used traditional fingerprinting methods.

Cooperative spectrum sensing scheme for Digital Multimedia Broadcasting-Terrestrial (DMB-T) system in China is investigated in this paper. There are three frame header modes defined in DMB-T Standard. For frame header mode 2, the only PN sequence is utilized to perform waveform-based spectrum sensing, and an improved synchronization algorithm is proposed. For frame header mode 1 and 3, extended pseudonoise (PN) sequences are proposed to be the local correlation sequences to perform waveform-based spectrum sensing. The performance of the proposed schemes is analyzed theoretically. Moreover, the performance of cooperative spectrum sensing schemes over the Rayleigh fading reporting channel is studied. When the probability of false alarm is 0.01 and the number of signal frame used is 1, it is shown that the probabilities of missed detection of the proposed schemes are much lower than that of the present PN correlation (PNC) and cyclic extension correlation (CEC) schemes. And the performance of the cooperative spectrum sensing is limited by both local detectors and the probability of reporting error.

In this paper, a novel multiple target localization approach is proposed by exploiting the compressive sensing theory, which indicates that sparse or compressible signals can be recovered from far fewer samples than that needed by the Nyquist sampling theorem. We formulate the multiple target locations as a sparse matrix in the discrete spatial domain. The proposed algorithm uses the received signal strengths (RSSs) to find the location of targets. Instead of recording all RSSs over the spatial grid to construct a radio map from targets, far fewer numbers of RSS measurements are collected, and a data pre-processing procedure is introduced. Then, the target locations can be recovered from these noisy measurements, only through an ¿1-minimization program. The proposed approach reduces the number of measurements in a logarithmic sense, while achieves a high level of localization accuracy. Analytical studies and simulations are provided to show the performance of the proposed approach on localization accuracy.

In this paper, a novel compressive sensing for manifold learning protocol (CSML) is proposed for localization in wireless sensor networks (WSNs). Intersensor communication costs are reduced significantly by applying the theory of compressive sensing, which indicates that sparse signals can be recovered from far fewer samples than that needed by the Nyquist sampling theorem. We represent the pair-wise distance measurement as a sparse matrix. Instead of sending full pair-wise measurement data to a central node, each sensor transmits only a small number of compressive measurements. And the full pair-wise distance matrix can be well reconstructed from these noisy compressive measurements in the central node, only through an ¿1-minimization algorithm. The proposed method reduces the overall communication bandwidth requirement per sensor such that it increases logarithmically with the number of sensors and linearly with the number of neighbors, while achieves high localization accuracy. CSML is especially suitable for manifold learning based localization algorithms. Simulation results demonstrate the performance of the proposed protocol on both the localization accuracy and the communication cost reduction.

The attractiveness of majority-logic decoding is its simple implementation. However, it provides a modest amount of coding gain. A modified Massey's majority-logic decoding algorithm is proposed to improve error-correcting performance. With hard-decision and soft-decision, the modified algorithm is applied to decode the (30,14) shortened Reed-Muller (RM) code in TETRA as well as syndrome algorithm, Massey's majority-logic algorithm, and Rudolph's majority-logic algorithm. Simulation results show that, the proposed modified algorithm can provide more coding gain than the original Massey's algorithm, the modified scheme has the best performance of error correction among four hard-decision schemes, and the Rudolph's scheme outperforms the other three schemes in the case of soft-decision.

A novel ESPRIT based decorrelating DOA estimation for CDMA frequency-selective fading channels is proposed. The proposed algorithm has the advantages that the DOAs of the multipath signals can be estimated independently and all the other resolved multipath signal interference is eliminated. Simulation results show that the proposed algorithm estimates the DOAs of multipath signals effectively and accurately.