Channel knowledge map (CKM) has been envisioned as a promising technology to achieve environment-aware communications for future sixth-generation (6G) wireless networks. The angle of departure (AoD) and the angle of arrival (AoA) are crucial parameters of CKM widely used for location-specific applications. Conventional stochastic methods of char-acterization fail to correlate the AoD and AoA with location-specific transmission environments. In this paper, we propose to utilize the CKM technology to characterize the location-specific AoD and AoA, by constructing the AoD and AoA map based on sparse measurement data. We further leverage the data-driven deep machine learning (DML) technique to obtain the AoD and AoA for locations without measurements. Simulation results show that the proposed method can construct both the AoD and the AoA maps with high fidelity to the true map. Moreover, Method II which predicts AoDs and AoAs sequentially achieves better performance than the independent prediction in Method I.

Radio environment map (REM) is a database repository widely adopted for applications such as spectrum sensing, interference management and network planning for wireless networks. However, conventional REM construction requires measurement-capable devices (MCDs) to upload location-based measurements, which exposes the privacy of users. In this paper, we propose a new method to construct the REM utilizing federated learning (FL) to preserve user privacy. In this method, multiple mobile MCDs collect the signal strength measurements in parallel and store the measurements locally. FL is then used to train a shared deep machine learning (DML) model for multiple MCDs collectively. In addition, we pre-process the location information and apply power adjustment to the measurements, either to increase the dynamic range of the input data to the FL or decrease the dynamic range of the measurements. The performance of the proposed FL-based method is evaluated in terms of the colormaps, heatmaps and cumulative distribution function (CDF) of estimation errors. The colormaps show that the power adjustment greatly improves the performance of the FL-based REM. The heatmaps show that smaller estimation errors can be achieved with more participating MCDs. The simulation results also show that the proposed FL-based method achieves better performance than the distance-based method and the nearest-neighbor-based (NN-based) method, in terms of estimation errors.

Timely identification of outliers occurring in key performance indicators (KPIs) of mobile cellular networks is crucial for prompt action to unexpected events. The KPIs of cellular networks typically exhibit seasonality and trend effects and these make the detection of outliers challenging. In this paper, an online unsupervised deep machine learning (DML) algorithm for outlier detection for time series with seasonality and trend is proposed. The proposed algorithm utilizes a neural network based on a temporal convolution network (TCN) and an autoencoder (AE) to reconstruct a time series that captures the normal behavior of the input data and then the reconstruction errors between the input and reconstructed time series at the output of the TCN-AE network are used for outlier detection. To train the TCN-AE network to learn the normal behavior of the input time series, we propose a two-step training process to overcome the presence of outliers in the training data. In addition, a novel loss function specially designed to address the seasonality and trend effects of the time series is proposed. Furthermore, a pre-processing technique is used to combat the adverse trend effect which might cause false alarms in outlier detection. The performance of the proposed TCN-AE-based outlier detection algorithm is evaluated using synthetic time series, Yahoo Webscope dataset and real time series of KPIs of mobile cellular networks. The results show that the proposed TCN-AE-based outlier detection algorithm achieves better detection accuracy in terms of F-score than other DML-based algorithms such as long short-term memory (LSTM)-AE-based algorithm and the convolutional neural network (CNN) based algorithm.

The posterior Cramέr Rao lower bound (PCRLB) has recently been proposed as an effective selection criteria for sensor resource management in large, geographically distributed sensor networks. Existing algorithms (in particular the decentralized approaches with no central fusion centre) designed for computing the PCRLB are based on raw observations resulting in significant communication overhead from the sensor nodes to the associated local processing nodes. The paper derives distributive computational techniques for determining the PCRLB for quantized sensor networks configured using decentralized architectures. We refer to the distributed computation of the PCRLB as dPCRLB. The main contribution of the paper is extending the dPCRLB algorithm [1] to quantized observations that leads to significant savings in the communication overhead over its counterparts that use raw observations. In our Monte Carlo simulations, we show that the proposed dPCRLB closely follows the centralized bound based on quantized observations. As expected, there is potential performance loss with quantization as is illustrated by the difference between the dPCRLBs computed using raw and quantized observations. The drop in the estimator's performance is, however, compensated for with an increase in the number of quantization levels associated with the observation quantizer.

Existing localization approaches developed using acoustic vector sensor (AVS) signals normally assume that the sources are static and the number of sources is known. In this paper, a novel approach is developed to estimate the 2-D direction of arrival (DOA) of an unknown and time-varying number of acoustic sources using a single AVS. A random finite set (RFS) is employed to characterize the randomness of the state process, i.e., the dynamics of source motion and the number of active sources. Also the measurement processes are modeled by RFS since we allow the AVS report undesired events by sending an empty set other than received signals under regular cases. We further employ particle filtering to approximate the posterior DOA distributions. The performance of the proposed approach is demonstrated by simulated experiments.

This paper presents a novel encoding scheme based on the residue number systems for folding ADC to enable highly efficient hardware implementation of high speed, high resolution ADC. The input analog signal is folded by multiple groups of zero-crossing based folding circuits of different folding factors corresponding to the moduli used for their implementation. Each group of folding circuits in turn contains multiple parallel zero-crossing based folding circuits of same folding factor, but with their outputs phase shifted with respect to one another such that their collective output bits pattern form a residue of the modulus of the group. Multiple groups of folding circuits with different moduli that are relatively prime to each other are then combined in parallel. When taken together, their digital outputs form residue digits of a relatively prime moduli set that allows unique representation of the input signal magnitude over a dynamic range that is equal to the product of the moduli used in the different groups in the ADC.

The general problem addressed in this paper is tracking the 2-D direction of arrival (DOA) of an acoustic source signal by using a single acoustic vector sensor (AVS). A Bayesian framework and its particle filtering implementation are introduced to adapt to the underwater ambient noise environment, in which both the interference and background noise exist. Several innovations are explored here: 1) a particle filtering based acoustic source tracking algorithm for AVS is developed; and 2) by using a multi-modality likelihood model to model the source detection and false alarm separately, the algorithm is able to alleviate the effect due to noise and interference. Particularly, by employing additional acoustic information, the proposed approach is able to track the 2-D DOA by using a single AVS. The performance of proposed approach is fully investigated under different simulated ambient noisy environments. Experiment results show that the proposed algorithm outperforms the traditional Capon beamforming approach and is able to lock on the 2-D DOA of the source even in a very challenging environment.

A novel number theoretic transform called Inverse Gray Robust Symmetrical Number System (IGRSNS) is proposed for error control coding in this paper. IGRSNS is obtained by modifying Robust Symmetrical Number System (RSNS) that was proposed earlier, using Inverse Gray code property. Due to ambiguities present in each residue, RSNS has a short dynamic range (DR) compared to that in other number systems. The short DR of RSNS enables it to be effectively used for error detection without the addition of any redundant modulus as in Redundant Residue Number System. Although RSNS has a large redundant range, its detection ability is not optimal due to the Gray code property associated with it. In an attempt to overcome this limitation, we have proposed Inverse Gray coding to be combined with RSNS in increasing its effectiveness in error detection. The resulting IGRSNS thus inherits properties of both RSNS and Gray code. Analysis and simulations show that IGRSNS has a near-optimal error detection ability. The potential of IGRSNS for error correction is also investigated. Further, a novel error correction algorithm using one redundant modulus is proposed. Simulations show that the proposed algorithm performs well under all cases of single bit errors.

In this paper, a preprocessing architecture for folding Analog-to-Digital converter (ADC) based on a new number system called Robust Folding Number System (RFNS) is presented. The RFNS is developed from robust symmetrical number system (RSNS) that was proposed by Pace et al. The enhanced Dynamic Range (DR) of RFNS due to the introduction of the folding bit results in higher ADC resolution. The Symmetrical Residues (SRs) that are obtained in the intermediate step during processing of analog signals are converted to equivalent residues by simple mapping. This results in a conversion architecture that is less complex compared to that proposed in.

The main application of Cognitive Radio (CR) is for the broadband wireless access in the rural areas which demand adequate data rate and multi user support. IEEE 802.22, the first standard evolved for CR suggests Orthogonal Frequency Division Multiple Access (OFDMA) as the physical layer technique. In this paper wavelet packet based multi carrier multiple access scheme is proposed which can be an equally promising candidate for high data rate multi user CR applications. The performance of the proposed system is evaluated using standard wavelet bases and is compared with OFDMA.

Layered space-time block spread CDMA (LST BSCDMA) has been previously proposed as an alternative to conventional CDMA systems for high-rate mobile communications. This paper proposes two approaches to obtain channel state information (CSI) for LST BS-CDMA system. The basic approach suffers from high computational complexity and poor performance in systems with high order of transmitter diversity due to inter-layer interference (ILI). The second approach reduces computation complexity and eliminates ILI, making it suitable for systems with higher order of transmitter diversity. The detailed simulation studies show that the highly accurate CSI obtained using the improved technique leads to considerable superior performance.

In this paper, a new architecture to compute 1-D Discrete Wavelet Transform (DWT) based on Folding Number System (FNS) is introduced. Numbers for FNS are extracted directly from analog input without any forward converter like in the Residue Number System (RNS) based DWT. The large Dynamic Range makes the FNS DWT more efficient than those implemented using RNS systems. The proposed 1D DWT architecture makes use of the relation between the coefficients of the low-pass and high-pass decomposition filters for orthogonal wavelets families to compute the transform with minimum numbers of modular multipliers. These multipliers are based on pipelined Look-Up Tables (LUT). A 6-tap Daubechies analysis filter bank is synthesized at a structural level using VHDL. FLEX10K devices of Altera are used in the simulation of DWT using binary arithmetic, RNS and FNS to evaluate its performance. Simulations show a significant throughput improvement is achieved in the proposed FNS DWT architecture when {2k- 1.2k,2k+ 1} moduli set is used.

In an ideal Software Radio, digitization of the received signal occurs immediately after receive antenna to enable channelization to be performed in the discrete time domain. However, this vision is still far from reality due to limitations of current analog to digital converter performance. In this paper, a novel number system called the Folding Number System (FNS) is proposed for use in Software Radio. We implement sample rate conversion immediately after the receive antenna using this number system thus providing an efficient solution to the above problem. By decomposing the input analog signal into separate channels in parallel, symmetrical residues are obtained with reduced number of comparators. These residues together with the folding information are processed in parallel in the FNS domain. The FNS has the same computational complexity as that in Residue Number System but the need for the intermediate steps such conversion of the analog data into binary and subsequently into residues is absent.

This paper presents a novel robust number theoretic transform called inverse gray robust symmetrical number system (IGRSNS) and proposes its application for CDMA systems. The transceiver structure for three moduli IGRSNS-CDMA with one redundant modulus is proposed. The proposed system is simulated for different values of moduli sets under various channel conditions. Simulation results show that the BER performance of IGRSNS-CDMA outperforms that of RNS-CDMA under all circumstances.

The paper describes information theoretic capacity of orthogonal pulse based modulation schemes for time hopping ultra wideband (TH-UWB) systems over a multiple access and multipath fading channel. Orthogonal pulse based modulation schemes such as pulse shape modulation (PSM), biorthogonal PSM (BPSM) and a combination of orthogonal pulse position modulation (OPPM) and BPSM have been proposed for reducing inter symbol interference (ISI) and multiple access interference (MAI) as well as for improving system performance. System capacity of TH-UWB systems can be increased by employing these modulations for higher level modulation schemes. The capacity of OPPM-BPSM outperforms PSM and BPSM schemes over a multipath fading channel. The complete mathematical analysis and theoretical simulation results are provided in detail.

One of the major issues in cognitive radio is obtaining an adaptive transmitting waveform based on environmental measurements. An efficient Radio frequency (RF) carrier waveform generation based on approximate prolate spheroidal wave function and bandpass filters is proposed in this paper. Bandpass filters are designed using interpolation and masking technique which gives a sharp cut off at lower order. The bit error performance of the waveform is evaluated. The proposed system will be useful in accessing TV spectrum and has good spectral utilization efficiency.

The transmitted reference (TR) receiver provides a good alternative to the good-yet-expensive RAKE receiver for ultra wideband impulse radio (UWB-IR). TR receiver is however inefficient due to the necessity in transmitting a reference prior to the data symbol. In this paper, the performance of TR receiver is investigated under high data rate transmission and compared to that of RAKE receiver. It is shown that the performance of basic TR is worse than a fractionally spaced selective RAKE receiver. A simple selective TR transceiver is then proposed to improve the performance of TR under ISI. It is shown that the proposed approach achieves almost similar performance to that of selective RAKE receiver while still maintains the simplicity of TR.

This paper studies two MIMO architectures for single-carrier CDMA system employing block spreading, namely Layered Space-Time Block Spread CDMA (LST BS-CDMA) and Space-Time Coded Block Spread CDMA (STC BS-CDMA). It is shown that under low mobility conditions, the proposed systems are virtually free from Multiple User Interference (MUI) and the block processing technique used leads to considerable reduction in the overall processing complexity. Extensive simulation was performed to study the impact of the spreading factor and Doppler frequency on the proposed systems. A new parameter called channel coherence ratio (CCR) is introduced as a key parameter in determining the performance of MIMO BS-CDMA.

This paper proposes a novel method for constructing ultra wide band (UWB) pulses based on a linear combination of Gaussian pulses. These pulses while meeting FCC power spectral density (PSD) mask requirements insure negligible interference with narrow band (NB) systems using flexible interference avoidance property they possess. Improved performance is achieved when errors due to imperfect synchronization exist between the transmitter and receiver (timing jitter). The coefficients of pulses designed can be generated using simple delay elements and amplifiers. The performance of these pulses in multipath channel such as channel model 1 (CM1) with timing jitter is evaluated by simulation and is found to be better than that of other designs.

We discuss the following problem: how to guarantee privacy of a circuit if an adversary can eavesdrop on its wires, where the functionality of the circuit is assumed public and the adversary attempts to discover information regarding the computation, namely, input, intermediate results and output. We present a solution by introducing a private stateful circuit that securely (against probing attacks) computes the same function as the original circuit does. This is achieved with a reasonable increase in circuit size and depth.

This paper describes a combined modulation scheme for time hopping ultra wideband (TH-UWB) radio systems based on biphase shift keying (BPSK), orthogonal pulse position modulation (OPPM) and pulse shape modulation (BPSM). A set of M = 2ksymbols are constructed by using L = 22lorthogonal pulse positions and N = 22k-l-1biorthogonal pulses, where k and l are nonnegative integers such that 0 ≤ l ≤ k - 1. The selection of number of pulse positions and pulses depend on the system performance and the availability of orthogonal pulses with estimable auto-correlation properties. The proposed scheme achieves higher data rate by introducing more number of orthogonal pulses in the same pulse repetition interval. It also reduces the system complexity by half by introducing antipodal version of orthogonal pulses. The proposed transmission scheme is analyzed through computer simulations in the presence of multipath channel.

This paper describes a combined modulation scheme for time hopping ultra wideband (TH-UWB) radio systems using on-off keying (OOK) and pulse shape modulation (PSM). For this scheme, a set of orthogonal pulses is used to represent bits in a symbol. These orthogonal pulses are transmitted simultaneously in the same time slot resulting in a composite pulse. By assigning different subset of orthogonal pulses for each user, multi-user interference can be reduced considerably. The proposed transmission scheme can achieve higher data rate by using fewer pulses and can use fewer number of receiver correlators than those used in PSM. Due to the presence of OOK, the proposed scheme requires minimum energy and is applicable for energy constrained UWB systems. The bit-error-rate (BER) performance of the proposed transmission scheme is analyzed both mathematically and through computer simulations in additive white Gaussian noise (AWGN) channel and modified IEEE 802.15.3a S-V UWB multipath channel model. The present paper also compares the proposed scheme with existing PSM and its combined modulation schemes.

Peak to average power ratio (PAPR) is one of the key parameters for efficient power amplification in multicarrier systems. Practical implementation difficulties and the performance constraints are two major limiting factors for many of the methods suggested for PAPR reduction. It is in this context, this paper suggests a simplified approach for PAPR reduction of multicarrier CDMA systems based on efficient coding of optimal binary phase sequences. Using this method, the side information related to phase values for PAPR reduction are spread using dedicated spread code and add with other user data before transmitting through channel. The overheads required for the proposed method is very minimal and the system performance is robust against channel estimation errors.

This paper describes a combined modulation scheme for time hopping ultra wideband (TH-UWB) radio systems based on orthogonal pulse position modulation (OPPM) and bi-orthogonal pulse shape modulation (BPSM). A set of M=2ksymbols are constructed by using L = 2lorthogonal pulse positions and N = 2k-l-1biorthogonal pulses, where k > 1 and l are nonnegative integers such that 0 les l les k-1. The selection of the number of pulse positions and pulses depends on the system performance and the availability of orthogonal pulses with estimable auto-correlation properties. This scheme allows an increase in the number of bits per symbol and consequently, reduces the duration of the pulse repetition interval which is obtain by increasing the number of orthogonal pulses. The proposed scheme achieves higher data rate by using a large number of orthogonal pulses in the same pulse repetition interval. It also reduces the system complexity by half by introducing antipodal version of orthogonal pulses. The proposed transmission scheme is analyzed through computer simulations in a multipath channel using two sets of orthogonal pulses.

Space-time coded block spread CDMA (STC BS-CDMA) was previously proposed to enhance the advantages offered by CDMA system with block processing. However, STC BS-CDMA suffers from long decoding delay and large single block transmission time which makes it unsuitable for communication systems delivering delay-critical applications and poor performance in systems with high mobility conditions. This paper proposes space-frequency coded BS-CDMA (SFC BS-CDMA) which performs space-frequency coding instead of space-time encoding. This reduces the decoding delay significantly and transmission time of a single block, making it an attractive alternative in delay-critical communication systems. This paper also compares the two MIMO BS-CDMA systems and provides extensive simulation results.

Impulse radio system has an ultra wide bandwidth, which makes it a viable solution for short range high data rate system. With the introduction of the FCC UWB spectral mask, numerous works have produced pulse shapes whose spectrum closely fits the FCC spectral mask. Such pulse shapes have better energy per bandwidth ratio and thus perform better against noise. This paper shows that aside from the energy, there are other factors that also affect the performance under high speed indoor channel. The authors also show a simple yet efficient pulse shape hopping (PSH) method to improve the performance of the system, by exploiting orthogonal pulses.

In this paper, a novel receive antenna subset selection technique is proposed for multiple input multiple output spatial multiplexing (MIMO-SM) systems with linear minimum mean square error (MMSE) receivers in the presence of unknown co-channel interference. This antenna selection technique is directly implemented based on training sample sequence by utilizing backward greedy algorithm (BGA) under the least squares (LS) criterion. In the case of practical implementation. Diagonal loading (DL) technique is incorporated into the selection process to insure robustness of antenna selection given limited training sample support. Simulation results show that the proposed antenna selection technique is able to retain the diversity order of a full complexity system in the presence of unknown multiple access interference (MAI)

In this paper, tap selection based Minimum Mean Square Error (MMSE) equalization technique is discussed for Ultra Wideband (UWB) systems in the presence of Inter Symbol Interference (ISI) and Multiple Access Interference (MAI). A novel tap selection technique based on Matching Pursuit (MP) algorithm is proposed. Given finite training sample support, Diagonal Loading (DL) technique is incorporated into MP algorithm to insure the robustness of tap selection. Moreover, a fast heuristic MP based tap selection technique is developed to facilitate the tradeoff between equalization performance and computational complexity. Simulation results show that the proposed tap selection based equalizer outperforms the RAKE receiver and the conventional MMSE equalizer significantly given the same amount of training symbols.

In this paper, a novel receive antenna selection technique is proposed for Multiple Input Multiple Output (MIMO) spatial multiplexing systems with linear receivers in the presence of unknown interference. This antenna selection technique is directly implemented based on training sample sequence under the Least Squares (LS) criterion. Simulation results show that the proposed antenna selection technique is able to retain the diversity benefit of full complexity system in the presence of unknown Multiple Access Interference (MAI), without the need for explicit channel estimation. In addition, practical implementation with manageable complexity is made possible by extending the fast Backward Greedy Algorithm (BGA) into the proposed antenna selection algorithm.

This paper proposes three different channel estimation techniques for layered space-time block spread CDMA (LST BS-CDMA) systems, using different pilot patterns. The first technique applies the normal channel estimation method for VBLAST systems on each subcarrier. The second technique constructs time-domain sequences that give a set of nulls at predefined frequency and interpolates those nulled tones to obtain the full frequency response of the channel. The third technique improves on the second technique and eliminates the need for knowledge of the channel delay spread. The LST BS-CDMA system is simulated and its performance is compared when the three different channel estimation technique is used

In this paper, diagonally loaded linear Minimum Mean Square Error (MMSE) equalization technique is proposed for Ultra Wideband (UWB) multipath channel in the presence of Inter Symbol Interference (ISI) and Multiple Access Interference (MAI). In the case of practical implementation under limited training sample support, the optimal solution for linear least squares problems is the Minimum Norm (MN) solution. But it suffers from performance degradation when the sample covariance matrices are ill-conditioned. Diagonal Loading (DL) technique is incorporated into MN solution and shown to achieve significant performance improvement when the amount of training symbols is comparable with the number of taps utilized by the equalizer. Moreover, a rank-reduced Multistage Wiener Filter (MWF) with DL is proposed for UWB multipath channel equalization which requires large number of taps. It is shown to converge to the MN solution with much reduced computational complexity.

This paper proposes a space-time coding architecture for single-carrier block spread CDMA systems. The proposed scheme employs a novel block spreading and despreading operation, which lead to significant reduction in the receiver complexity. The performance of the system is enhanced through space-time coding transmission. Extensive simulation studies are carried out and the performance of the proposed system is compared against conventional CDMA systems.

The computational complexity of linear phase finite impulse response (LPFIR) filters used in the channelizer of a wideband receiver is dominated by the number of adders (subtracters) employed in the multipliers. Common subexpression elimination (CSE) is a well-known technique for minimizing the number of adders in LPFIR filters. An improved CSE method is proposed in this paper, which is used to implement the channel filters of a filter bank channelizer (FBC). In the FBC, each modulated bandpass filter extract one channel from the input wideband signal. The reduction in number of adders is obtained by eliminating redundant multiplications of common subexpressions that exist among the channel filters of the FBC with the input signal. Design example of the channel filters employed in the digital advanced mobile phone system (D-AMPS) show that the proposed method offers considerable reduction in the number of full adders when compared with conventional CSE methods.

The flexibility of a software-defined radio (SRR) depends on its capability to operate in multi-standard wireless communication environments. The most computationally intensive part of wideband receivers is the channelizer, which extracts multiple narrowband signals from adjacent frequency hands. In an SDR receiver, the compatibility of the channelizer with different communication standards is guaranteed by its reconfigurability. This paper presents an efficient channelizer that has a reconfigurable architecture based on quadrature mirror filter bank (QMF) trees. We show that the channelizer can he efficiently implemented using common subexpression based filter structures. An example of dual-mode global system for mobile communication (GSM)/personal digital cellular (PDC) channelizer is discussed to illustrate the proposed design methodology.

The Residue Number System (RNS) offers unlimited opportunities for high performance arithmetic provided efficient forward and reverse converters could be constructed for the moduli set at hand. All forward conversion proposals to date, require some form of Read Only Memory (ROM) along with computational elements like Full Adders (FA). In this paper, we show that by formulating the forward conversion problem in terms of modular exponentiation and addition, we can achieve memory free conversion. We generalize our solution such that bit serial and bit parallel implementations can be derived by simply varying a parameter, namely, multiplexers. Apart from this formulation itself, the paper makes two other contributions. Firstly, it demonstrates an entirely new set of converters that use no look up. Secondly, we show how conversion complexity can be reduced significantly by sharing circuitry over several forward converters.

High data rates in wireless radio environments are becoming common. Current system designs are inadequate to meet the speed requirements that are anticipated in the newer services. The computational complexities in the subsystems increase in direct proportion. We propose alternative multiply accumulate units for the pulse shaping filters that use a new representation for their coefficients. Consequently, these new structures are fast, efficient and consume less power. The filters proposed take into account constraints, such as, intersymbol interference, response characteristics etc. in their design methodology.

It is known that quadrature mirror filters (QMFs) designed using the algorithm in Lim and Yang (1993) suffer from passband anomaly under certain conditions. A modification to this algorithm was proposed in Goh et al. (1996) to overcome this anomaly. However, this design is not a general solution for different stopband edge frequencies. In this paper, we propose a more robust technique to design QMFs, by modifying the frequency domain approach proposed in Lim and Yang with a better initial guess filter obtained by frequency sampling design. The QMF designed employing the proposed technique overcomes the passband anomaly and has excellent frequency response characteristics that are considerably better than those obtained using earlier methods.