SUMMARY: We propose a new algorithm, "interval hashing," which distinguishes identical k-mers arising from different repeat sequences, particularly in complex repeat arrays such as alpha satellite HORs. We implement this algorithm as a fork of minimap2, named mm2-ivh. In local assembly of alpha satellite HORs, mm2-ivh accurately reconstructs more haplotypes than assemblers using standard minimizers. AVAILABILITY AND IMPLEMENTATION: mm2-ivh is available under the MIT license at https://github.com/ocxtal/mm2-ivh and runs on common Unix-compatible systems.

As 5G networks continue to expand into critical infrastructure, ensuring secure and efficient user authentication has become more important than ever. The 5G-AKA protocol, standardized by 3 GPP in TS 33.501, is the cornerstone of authentication in current 5G deployments. It provides mutual authentication, user privacy, and key secrecy. However, despite its widespread adoption, 5G-AKA suffers from known limitations in both security and performance. While it primarily focuses on protecting privacy against passive attackers, recent studies have highlighted its vulnerabilities to active attacks. Furthermore, it relies on a sequence number-based mechanism to prevent replay attacks, requiring the user device and the core network to remain perfectly synchronized. This stateful design introduces operational complexity, frequent desynchronization issues, and additional communication overhead. More critically, 5G-AKA lacks Perfect Forward Secrecy (PFS), leaving past communications vulnerable if long-term keys are ever compromised- a growing concern in the age of sophisticated adversaries. In this paper, we propose an enhanced authentication protocol that builds on the design principles of 5G-AKA while addressing these fundamental shortcomings. First, we present a stateless version of the protocol that eliminates the reliance on sequence numbers, reducing communication complexity while remaining fully compatible with existing SIM cards and network infrastructure. We then extend this design to include PFS with only minimal cryptographic overhead. Both protocols are rigorously analyzed using ProVerif, showing that they meet all major security requirements, including resistance to both passive and active attacks, as well as those outlined by 3GPP and recent academic studies. We also prototype both protocols and evaluate their performance against 5G-AKA and 5G-AKA’ (USENIX’21). Our results show that the proposed protocols offer stronger security guarantees with only minor impact on computational costs, making them practical and forward-compatible solutions for 5G and beyond.

Trust evaluation and management schemes have been extensively employed in a bid to alleviate diverse insider attacks. These trust values are often ascertained by taking into consideration trust parameters to determine the honesty and reliability of a vehicle and evaluating a weighted sum of the said parameters. To achieve precision and to reflect a reasonable impact of these parameters, rational weight values are imperative. Accordingly, this research primarily emphasizes on the quantification of weights associated with the contributing trust attributes by proposing a novel trust management mechanism that utilizes contextual information in addition to employing relevant impacting quantities as weights to formulate trust evaluations. Moreover, the envisaged trust management model incorporates 1) attack resilience while constituting certain parameters and 2) an adaptive and flexible threshold to mitigate malevolent behaviors. The simulation results depict that the devised parameters and the formulated trust aggregation cater to the dynamic nature of vehicular networks demonstrating the rationality of the weights’ quantification, and the introduction of the adaptive threshold for misbehavior detection aligns well with the requirements of the ever-changing vehicular networks.

The emerging yet promising notion of trust amalgamated with the paradigm of the Internet of Vehicles (IoV) has been of significant interest for researchers in both industry and academia. Trust management models are being widely employed in diverse domains seeking to mitigate multifarious insider attacks where dishonest entities counterfeit or alter the messages from legitimate users, subsequently, endangering the lives of drivers, passengers, and vulnerable pedestrians. While vehicles form opinions towards the fellow network participants, numerous influencing attributes in reference to the interactions among the vehicles are aggregated to develop a final belief on a target vehicle. The significance of these trust impacting attributes is often depicted by manually assigning a weight to each parameter. The aim of this research is to address the challenges of quantification of the influencing trust attributes and the weights associated with these parameters, subsequently, quantifying the aggregated trust. Furthermore, the time-based behavior of the aggregated trust along with the contributing parameters is also analyzed in this paper to study the behavior of each vehicle and to identify suitable trust-based patterns for safety-critical and non-safety vehicular applications. Performance analysis demonstrates that the trust values computed via the envisaged trust model are lower than those calculated via the benchmark scheme.

In multi-user multiple input multiple output orthogonal frequency division multiplexing (MU- MIMO-OFDM) downlink system, it is important to have accurate channel state information (CSI) at the base station (BS) in order to minimize the inter-user interference (IUI). However when the channel changes rapidly, the available CSI at the BS can be outdated and this leads to the performance loss. The channel prediction algorithms can be used to predict the future CSI and compensate for the discrepancy between the estimated channel and the actual channel, and improve the performance of the overall system. In this paper, we propose to use recursive least square (RLS) algorithm to predict the CSI for the upcoming frame in MU-MIMO-OFDM downlink system. The simulation results show that RLS algorithm outperforms the other prediction algorithms such as normalized least mean square (NLMS) and the conventional linear extrapolation method. The simulation results are further validated with the measured channel results.

Distributed transmit beamforming (DTBF) is an efficient technique to increase the transmission coverage in a situation where distributed nodes have limited hardware capabilities such as transmit power or the number of equipped antennas. This scenario is quite typical in tactical communication systems. The DTBF precodes transmit signals based on feedback information. In practice, continuous channel phase information is quantized based on codebook to reduce feedback overhead. In this paper, we will analyze the effect of channel quantization in the DTBF and show a small number of bits are enough to encode channel feedback information to achieve comparable performance compared to the DTBF without channel quantization. We will also derive approximated probability density function of the received SNR, which is very useful to further derive the performance of the DTBF in terms of channel capacity, outage probability, and error rates.

BACKGROUND: The read length of single-molecule DNA sequencers is reaching 1 Mb. Popular alignment software tools widely used for analyzing such long reads often take advantage of single-instruction multiple-data (SIMD) operations to accelerate calculation of dynamic programming (DP) matrices in the Smith-Waterman-Gotoh (SWG) algorithm with a fixed alignment start position at the origin. Nonetheless, 16-bit or 32-bit integers are necessary for storing the values in a DP matrix when sequences to be aligned are long; this situation hampers the use of the full SIMD width of modern processors. RESULTS: We proposed a faster semi-global alignment algorithm, "difference recurrence relations," that runs more rapidly than the state-of-the-art algorithm by a factor of 2.1. Instead of calculating and storing all the values in a DP matrix directly, our algorithm computes and stores mainly the differences between the values of adjacent cells in the matrix. Although the SWG algorithm and our algorithm can output exactly the same result, our algorithm mainly involves 8-bit integer operations, enabling us to exploit the full width of SIMD operations (e.g., 32) on modern processors. We also developed a library, libgaba, so that developers can easily integrate our algorithm into alignment programs. CONCLUSIONS: Our novel algorithm and optimized library implementation will facilitate accelerating nucleotide long-read analysis algorithms that use pairwise alignment stages. The library is implemented in the C programming language and available at https://github.com/ocxtal/libgaba .

The performance of a coordinated multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system is limited by the presence of the local oscillator frequency mismatch, where each transmitter and receiver is driven by an independent local oscillator. This paper proposes a simple pilot assisted estimation of symbol-by-symbol carrier offset for every pair of the transmitter and the receiver to enable spatial multiplexing in a coordinated MIMO-OFDM system. The proposed method takes advantage of the characteristics of OFDM and the relative local oscillator stability assisted by the global positioning system receiver. The proposed method was implemented on an actual hardware platform demonstrating spectral efficiency improvement of four times using four transmitters and four receivers in 800MHz band.

In this paper, we propose clustered quantization techniques for multiuser multi-input/multi-output (MIMO) orthogonal frequency division multiplexing (OFDM) using constellation based codebooks. Constellation based codebooks provide scalability and efficient codeword search capability, which are key features for practical multiuser MIMO-OFDM systems with a large number of antennas. The proposed clustered quantization scheme quantizes consecutive subcarriers into a single codeword that minimizes aggregated quantization errors. We base our new clustering techniques on two constellation based quantization methods, namely equal-magnitude angular quantization (EMAQ) and squared-lattice angular quantization. New efficient codebook search algorithms are proposed for the clustered quantization. In addition, we propose new constellations to guarantee different users quantize channels into distinct codewords. One is a rotated M-PSK constellation suitable for randomly-distributed user scenarios, and the other is a random phase equal-magnitude (RPEM) constellation suitable for ill-conditioned user scenarios. Thus, full spatial multiplexing gain can be achievable even with small number of users. Finally, a near-sphere codeword search algorithm is proposed for the RPEM. In simulations, the proposed clustered quantization shows up to 50% higher throughput compared to conventional fixed-pilot channel quantization. Also, we show our new constellations for EMAQ improve throughput almost 35% compared to the standard EMAQ.

Channel matrix inversion, which requires significant hardware resource and computational power, is a very challenging problem in MIMO-OFDM systems. Casting the frequency-domain channel matrix into a polynomial matrix, interpolation-based matrix inversion provides a promising solution to this problem. In this paper, we propose novel algorithms for interpolation based matrix inversion, which require little prior information of the channel matrix and enable the use of simple low-complexity interpolators such as spline and low pass filter interpolators. By invoking the central limit theorem, we show that a Gaussian approximation function well characterizes the power of the polynomial coefficients. Some low-complexity and efficient schemes are then proposed to estimate the parameters of the Gaussian function. With these estimated parameters, we introduce phase shifted interpolation and propose two algorithms which can achieve good interpolation accuracy using general low-complexity interpolators. Simulation results show that up to 85% complexity saving can be achieved with small performance degradation.

Channel matrix inversion, which requires significant hardware resource and computational power, is a very challenging problem in MIMO-OFDM systems. Casting the frequency-domain channel matrix into a polynomial matrix, interpolation-based matrix inversion provides a promising solution to this problem. In this paper, by showing that the polynomial coefficients can be well approximated by a Gaussian function, we propose an efficient algorithm, which relaxes the requirement for knowing the maximum multipath delay spread and enables the use of simple low-complexity interpolators by introducing a phase shift term to the signal to be interpolated. Simulation results show that significant complexity saving can be achieved with little equalization performance degradation.

Multi-user multiple-input multiple-output (MU-MIMO) has a potential to realize cost effective high data rate internet access to the homes in rural areas. We propose the novel Ngara Access system where the central access point (AP) is equipped with a uniform circular array (UCA) installed on a high tower while each UT is equipped with a directional antenna free of clutter, providing predominantly line-of-sight (LoS) channel environment. Using a three dimensional geometric optics based channel model, we provide bit error probability simulation results which show that the spectral efficiency of the proposed system can be improved linearly as a function of the number of antenna elements at AP, without increasing the total transmitting power, provided a half wavelength antenna spacing is maintained and user groups of four or more are used to avoid ill-conditioned channel. Hardware demonstrators based on the proposed system have achieved the system spectral efficiency of 20 bits/s/Hz in an actual rural environment and of 67 bits/s/Hz in a laboratory environment at a lower UHF band.

In this paper, we consider a channel quantization problem that selects the best codeword representing a group of consecutive subcarriers (cluster) in multiuser MIMO-OFDM systems. The clustering is required to reduce the amount of feedback information in practical OFDM systems. Based on M-PSK based codebooks, we propose a new codeword search algorithm for the clustered MIMO-OFDM with complexity of O(2NT) compared to the complexity of O(MNT) for conventional exhaustive search, where NTdenotes the number of transmit antennas. Through simulations, the proposed clustered codeword selection scheme for the multiuser MIMO-OFDM shows up to 54% performance improvement in throughput compared with the conventional MIMO-OFDM system that performs the channel quantization only on predetermined pilot subcarriers.

Commonwealth Scientific and Industrial Research Organisation (CSIRO) has recently conducted a technology demonstration of a novel fixed wireless broadband access system in rural Australia. The system is based on multi-user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM). It demonstrated an uplink of six simultaneous users with distances ranging from 10 m to 8.5 km from a central tower, achieving 20 bits/s/Hz spectrum efficiency. This paper reports on the analysis of channel capacity and bit error probability simulation based on the measured MU-MIMO-OFDM channels obtained during the demonstration, and their comparison with the results based on channels simulated by a novel geometric optics based channel model suitable for MU-MIMO-OFDM in rural areas. Despite its simplicity, the model was found to predict channel capacity and bit error rate probability accurately for a typical MU-MIMO- OFDM deployment scenario.

In wireless dual-hop decode-and-forward (DF) relaying networks, multiple relay stations (RS) and users construct a DF broadcast channel (DFBC). Due to unpredictable decoding failure, scheduling in the DFBC should depend on not only channel qualities but also the availability of error-free data at individual RSs. Based on the reception qualities of RSs and channel quality information (CQI), we propose a new centralized scheduling scheme to maximize the sum rate of the DFBC. An exact closed-form expression for the sum rate is derived to analyze the new scheme. To further facilitate the analysis, the bounds of the sum rate are derived as a computationally effective alternative to the exact expression. Simulations demonstrate that the derived closed-form expression quantifies the proposed scheduling method accurately. It is also revealed that the analytical bounds are able to characterize the performance of the new scheduling method with acceptable accuracy.

In wireless dual-hop decode-and-forward (DF) relaying networks, multiple relay stations (RS) and users construct a multiple-in-multiple-out (MIMO) broadcast channel (BC). Due to unpredictable decoding failure, scheduling the transmission for the decode-and-forward broadcast channel (DFBC) should depend on not only channel qualities but also the availability of errorless data at individual RSs. Based on the reception qualities of RSs and channel quality information (CQI), we propose a new centralized scheduling scheme to maximize the sum rate of the DFBC. An exact closed-form expression for the sum rate is derived to analyze the new scheme. Simulations demonstrate that the derived closed-form expression is able to quantify the proposed scheduling method accurately. It is also revealed that extra cooperative diversity can be exploited by employing the increased number of RSs, thereby improving sum rate.

When multi-user multiple-input multiple-output (MU-MIMO) is applied to predominantly line-of-sight (LoS) environments, such as in the case of fixed wireless access in rural areas where a central access point (AP) equipped with an antenna array with NAPantenna elements serves NUTuser terminals (UTs) each equipped with a single antenna, the problem of ill-conditioned channels arises. This paper investigates the performance of zero-forcing preceding based MU-MIMO downlink when the AP is equipped with a uniform circular array (UCA) in an LoS environment. The performance is analyzed as a function of the spacing and the number of AP UCA antenna elements for NAP≥ NUT. The analysis reveals a complex yet orderly pattern of the performance nulls indicating different optimal antenna spacing for different number of antenna elements. The performance nulls can be largely eliminated by employing NAP≥ 2NUT.

This paper considers MIMO-OFDM transmission with low density parity check (LDPC) codes. We employ a low complexity minimum mean-square-error (MMSE) soft-interference-cancelation (SIC) based double iterative receiver (DIR). Results are presented for a real system implementation at 5.2 GHz. We achieve zero packet errors at 90% of the measured indoor locations, when transmitting at 600 Mbit/s, with 15 bit/s/Hz spectral efficiency and 26 dB signal-to-noise ratio. We show that the proposed receiver actually outperforms a list sphere detection (LSD) based single iterative receiver (SIR) at high coding rates, in practice. Investigations reveal that the LSDSIR is adversely affected by the non-Gaussian noise present at the receiver, while at the same time the MMSE-SIC-DIR is better able to handle transmitter noise present in the practical system.

We present a novel technique for the detection of spatially multiplexed transmitted symbols in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The method, termed Selective Detection, observes errors caused by a simple zero-forcing (ZF) on different OFDM sub-carriers, and selectively performs list sphere detection (LSD) on sub-carriers with larger errors. Compared with the full-complexity LSD, the proposed algorithms could significantly reduce the receiver complexity at a small signal-to-noise ratio (SNR) loss. For example, simulation results for a coded MIMO- OFDM system using four transmitters and four receivers with 16 quadrature amplitude modulation (16-QAM) and low density parity check (LDPC) coding show that more than 90% of SNR gain that can be achieved by the use of LSD over ZF can be achieved if only 20% of sub-carriers are intelligently selected for LSD.

This paper presents analysis of performance measurements from a MIMO-OFDM IEEE 802.11n hardware implementation at 5.2 GHz using four transmitters and four receivers. Two spatial multiplexing systems are compared; one which uses a zero-forcing (ZF) detector and the other a list sphere detector (LSD). We show that the measured results do not align with standard prediction based on simulation assuming uncorrelated receiver noise. We show that the discrepancy can be explained by the inclusion of transmitter noise into the channel model. This effect is not included in existing MIMO-OFDM channel models. The measured results from our hardware implementation show successful packet transmission at 600 Mb/s with 15 bits/s/Hz spectral efficiency at 73% coverage for ZF and 84% coverage for LSD with an average receiver signal to noise ratio (SNR) of 26 dB.

In this paper, the validity of P.1546, in short range (typically less than 20km) terrestrial environment is analysed by comparing its three versions (P.1546, P.1546-1, and P.1546-2) against simple models and against measurement results obtained by utilising the pilot signal of a commercial CDMA mobile network in rural Australia. The results show that the latest version on average underestimates the field strength by more than 10dB for typical Australian rural areas, however it improves the error standard deviation. The causes of these effects and the suggestions for further development of the Recommendation are discussed.

In this paper, the uncoded symbol error rate (SER) versus signal to noise ratio (SNR) curves of M-ary quadrature amplitude modulation (M-QAM) multiple-input multiple-output (MIMO) systems using zero-forcing (ZF) or maximum likelihood (ML) detection employing various numbers of antennas are given analytically and empirically. Using the given formulas, the designer of a MIMO system can easily analyse the tradeoff between using ZF or MLD, where ZF is computationally efficient but requires more receivers to achieve the same performance as MLD. An example is given, showing that, for an uncoded MIMO system using QPSK, 16QAM, or 64QAM, to achieve the same or better performance as MLD using 2, 3, and 4 antennas at each end, ZF requires at least 3, 5, and 7 receivers, respectively, at a specified average SER of 10-3

In this paper, the bit error rate (BER) and packet error rate (PER) performance of multiple-input multiple-output orthogonal frequency division multiplexing with bit interleaved coded modulation (MIMO-OFDM-BICM) systems using convolutional, Turbo, or low density parity check (LDPC) coding schemes are evaluated on MIMO-OFDM channels measured in various indoor environments. For a given average signal to noise ratio (SNR) per receiver, the performance of MIMO-OFDM-BICM in a line-of-sight (LoS) environment can vary significantly depending on the existence of scattering, while it is more uniformly distributed in a non-line-of-sight (NLoS) environment. We show that, due to bursty coded bit error characteristics of Turbo and LDPC coding, only marginal coding gain over convolutional coding is observed in terms of BER. However, when PER is compared, a 3 dB coding gain is achieved by the Turbo or LDPC code over the convolutional code.