1,720,969 research outputs found
Network Diversity Multiple Access with Imperfect Channel State Information at the Transmitter Side
No full textRTUWO Advances in Wireless and Optical Communications 2016 (RTUWO2016). 3 to 4, Nov, 2016. Riga, Latvia.Network diversity multiple access (NDMA) is the family of algorithms with the highest potential throughput in the literature of signal-processing assisted random access protocols. NDMA uses the concept of protocol-induced retransmissions to create an adaptive source of diversity. This diversity is used to resolve packet collisions employing signal separation tools without the explicit need (or as a complement) of a multiple antenna receiver. This paper proposes a further improvement on the performance of NDMA by allowing each terminal access to an outdated copy of its individual channel state information (CSI). Based on this decentralized CSI, each terminal conveniently decides to transmit only if the estimated channel gain surpasses a threshold that is optimized to maximize performance. This ensures that the probability of terminal presence detection, and thus the probability of correct estimation of the collision multiplicity are considerably improved at the receiver end. The paper is focused on the modelling of the receiver operational characteristic (ROC) of the terminal presence detector considering that the CSI used by each terminal is potentially inaccurate (outdated) due to feedback delay. The results indicate that when the correlation coefficient that describes the accuracy of the available CSI tends to zero, the scheme degrades into the conventional NDMA. By contrast, when the quality of the channel state information improves, the throughput can nearly achieve the nominal channel rate (minimum throughput penalty). The selection of the detector thresholds for channel gain and terminal presence is optimized to maximize system performance.info:eu-repo/semantics/publishedVersio
Performance Analysis of Network Diversity Multiple Access with Sequential Terminal Detection and Non-Orthogonal Training Sequences
No full textThis paper presents a new approach for terminal presence detection in the family of algorithms called network diversity multiple access (NDMA). The new scheme is based on non-orthogonal sequences. In NDMA, system-induced retransmissions are used to resolve the conflicts between colliding terminals. The key initial aspect in NDMA is to use signal processing tools to identify the size of the collision, as well as the identity of the contending terminals. This information is used to calculate the number of required retransmissions. These retransmissions are stored in memory, thereby creating a virtual MIMO (multiple input multiple-output) system that can be used to resolve the collision via source separation or multi-user detection. These detection and source separation processes are based on a set of orthogonal training sequences, each sequence uniquely assigned to one terminal in the network. This paper proposes a new approach for presence detection in NDMA using non-orthogonal sequences. The number of available sequences is increased and the bandwidth used for training is therefore considerably reduced. This comes at the expense of multiple access interference (MAI) between contending terminals. Additionally, in NDMA the estimation of the collision multiplicity is conventionally achieved in the first time-slot of the collision resolution period. This paper extends the detector to include all the received copies of the original transmissions (the initial transmission and also subsequent retransmissions). This means that after each retransmission received by the access point, the estimation of the collision multiplicity and contending terminals identification must be updated. The analysis here presented includes the effects of MAI caused by non orthogonal training sequences and the effect of sequential collision multiplicity estimation. Results suggest a considerably decrease of performance with respect to the orthogonal case scenario, but a more flexible training sequence allocation that becomes relevant for large numbers of terminals.info:eu-repo/semantics/publishedVersio
On the central Chi-square distribution with even degrees of freedom and correlated multivariate complex components
No full textThis paper presents the derivation new expressions for the statistics of a Chi-square distribution with degrees of freedom and where n is an even number. The complex Gaussian components of the chi-square distribution are modelled with a linear correlated model using different statistics (multi-rate) for each component. We focus on the specific expressions for the probability density function (PDF) and complementary cumulative density function (CCDF). Unlike previous approaches, we use a frequency domain interpretation that allows us to derive a closed form expression for the characteristic function (CF) as an inverse polynomial equation. Using the roots of this polynomial equation, it is possible to decompose the CF as a partial fraction expansion (PFE). This allows us to obtain a simple expression for both the PDF and CCDF by simply using the inverse Fourier transform of PFE decomposition of the CF. The statistics derived here have a much lower complexity than the expressions obtained from conventional non-frequency domain methods at the expense of the complexity of the polynomial root solution scheme. In scenarios where the average statistics of the components do not change over some periods of time, the proposed expressions provide the lowest possible complexity, as the polynomial rooting process needs to be conducted only once and potentially offline.info:eu-repo/semantics/publishedVersio
Ultra-Reliable Low Latency based on Retransmission and Spatial Diversity in slowly fading channels with co-channel interference
No full textThis paper presents the analysis of the statistics of latency and information theoretic capacity of an adaptive link with retransmission-spatial diversity in a scenario with co-channel interference. The paper focuses specifically on the delay of the wireless transmission component, measured from the instant a packet at the head of the queue is first transmitted until it is correctly received by the destination (considering retransmissions). The objective is to evaluate the ability of temporal and spatial diversity tools to achieve ultra-low values of latency as desired in future 5G and machine-to-machine (M2M) networks with real-time requirements. It is assumed that the source transmits information towards the destination in a Rayleigh fading spatially correlated channel. In case the instantaneous signal-to-interference-plus-noise (SINR) ratio has not surpassed a predetermined reception threshold, then the source engages in a persistent retransmission protocol. All the copies of the original transmission and subsequent retransmissions are stored in memory and processed at the destination using maximum ratio combining (MRC) to obtain a more reliable copy of the signal (a scheme also called retransmission diversity). The retransmission scheme stops once the instantaneous post-processing SINR achieves the desired target threshold. This persistent retransmission scheme can also be regarded as a security mechanism against interference jamming attacks. Since retransmissions are assumed to take place in a short time interval in order to achieve very low values of latency, they are modelled with statistical temporal correlation, which is explicitly introduced in the embedded Gaussian channel distribution model. Results suggest that retransmission diversity can provide good latency results in moderate to high values of SINR. However, at low SINR, a combination with other diversity sources will be necessary to achieve the desired target value.info:eu-repo/semantics/publishedVersio
220609
No full textThis work deals with the study of artificial intelligence (AI) tools for purposes of vehicular wireless channel prediction. The objective is to test the ability of different types of AI and machine learning (ML) algorithms under different types of implementation constraints. We focus particularly in highly changing scenarios where the channel state information changes relatively fast and therefore the relevant measurements or long-term statistical models are therefore scarce. This means that the training of our models can be potentially inaccurate or incomplete and we need to investigate which AI algorithm behaves better in this challenging condition. In future work we aim to investigate also computation complexity constraints, real-time deadlines, and outdated/distorted or noisy data set samples. We also aim to correlate the main properties of the well-known Jakes' channel model with the effectiveness of the type of prediction and the parameters of the different algorithms being tested. The objective of channel prediction in vehicular networks is to reduce allocation and transmission errors, thereby reducing latency and improving message transmission reliability, which is crucial for future applications such as autonomous vehicles. Results show that even in situations with incomplete data sets, AI can provide good approximate predictions on the channel outcome.This work was partially supported by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology), within the CISTER Research Unit (UIDP/UIDB/04234/2020); also by the Operational Competitiveness Programme and Internationalization (COMPETE 2020) under the PT2020 Agreement, through the European Regional Development Fund (ERDF), and by FCT, under project POCI-01-0145-FEDER-032218 (5GSDN); also by FCT and the ESF (European Social Fund) through the Regional Operational Programme (ROP) Norte 2020. InSecTT project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No. 876038. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Austria, Sweden, Spain, Italy, France, Portugal, Ireland, Finland, Slovenia, Poland, Netherlands, Turkey. Disclaimer: The document reflects only the author’s view and the Commission is not responsible for any use that may be made of the information it contains.info:eu-repo/semantics/publishedVersio
Network Diversity Multiple Access with Imperfect Channel State Information at the Transmitter Side
No full textRTUWO Advances in Wireless and Optical Communications 2016 (RTUWO2016). 3 to 4, Nov, 2016. Riga, Latvia.Network diversity multiple access (NDMA) is the family of algorithms with the highest potential throughput in the literature of signal-processing assisted random access protocols. NDMA uses the concept of protocol-induced retransmissions to create an adaptive source of diversity. This diversity is used to resolve packet collisions employing signal separation tools without the explicit need (or as a complement) of a multiple antenna receiver. This paper proposes a further improvement on the performance of NDMA by allowing each terminal access to an outdated copy of its individual channel state information (CSI). Based on this decentralized CSI, each terminal conveniently decides to transmit only if the estimated channel gain surpasses a threshold that is optimized to maximize performance. This ensures that the probability of terminal presence detection, and thus the probability of correct estimation of the collision multiplicity are considerably improved at the receiver end. The paper is focused on the modelling of the receiver operational characteristic (ROC) of the terminal presence detector considering that the CSI used by each terminal is potentially inaccurate (outdated) due to feedback delay. The results indicate that when the correlation coefficient that describes the accuracy of the available CSI tends to zero, the scheme degrades into the conventional NDMA. By contrast, when the quality of the channel state information improves, the throughput can nearly achieve the nominal channel rate (minimum throughput penalty). The selection of the detector thresholds for channel gain and terminal presence is optimized to maximize system performance.info:eu-repo/semantics/publishedVersio
A Space-Time Correlation Model for MRC Receivers in Rayleigh Fading Channels
Full text linkThis paper presents a statistical model for maximum ratio combining (MRC) receivers in Rayleigh fading channels enabled with a temporal combining process. This means that the receiver effectively combines spatial and temporal branch components. Therefore, the signals that will be processed by the MRC receiver are collected not only across different antennas (space), \mbox{but also} at different instants of time. This suggests the use of a retransmission, repetition or space-time coding algorithm that forces the receiver to store signals in memory at different instants of time. Eventually, these stored signals are combined after a predefined or dynamically optimized number of time-slots or retransmissions. The model includes temporal correlation features in addition to the space correlation between the signals of the different components or branches of the MRC receiver. The derivation uses a frequency domain approach (using the characteristic function of the random variables) to obtain closed-form expressions of the statistics of the post-processing signal-to-noise ratio (SNR) under the assumption of equivalent correlation in time and equivalent correlation in space. The described methodology paves the way for the reformulation of other statistical functions as a frequency-domain polynomial root analysis problem. This is opposed to the infinite series approach that is used in the conventional methodology using directly the probability density function (PDF). The results suggest that temporal diversity is a good complement to receivers with limited spatial diversity capabilities. It is also shown that this additional operation could be maximized when the temporal diversity is adaptive (i.e., activated by thresholds of SNR), thus leading to a better resource utilization.info:eu-repo/semantics/publishedVersio
Energy Efficient Random Transmission Control for Cognitive Radio Systems
No full textAbstractCognitive radio technology will allow terminals to access licensed and unlicensed portions of the spectrum. This feature will improve end-user satisfaction and will partially solve bandwidth scarcity problems. However, this opportunistic access implies more transmission attempts and thus higher power consumption. This goes against the energy/power efficient design that underpins modern wireless communication systems. This paper partially addresses this issue by proposing a random transmission policy that is energy-efficient and that provides high throughput gains. To facilitate analysis, a reception model for Rayleigh channels is here proposed that allows the calculation of correct packet reception statistics in the presence/absence of interference between primary/secondary users. The analysis initially focuses on the derivation of the boundaries of two types of trade-off regions: primary vs. secondary throughput, and sum-throughput vs. power consumption. It is observed that secondary transmissions always increase power consumption, and in the case of low interference they always lead to higher sum-throughput at the expense of reduced primary performance. By contrast, in the case of high interference, secondary transmissions can reduce both sum-throughput and primary user performance, thus requiring more complex control. It is shown that the minimum sum-throughput solution is also the boundary of the region where primary/secondary contributions to sum-throughput start to become dominant. An optimum transmission policy is further derived that maximizes sum-throughput while keeping primary/secondary throughput and power consumption under control. Sketches of the trade-off regions show the benefits of the proposed transmission policy
Ultra-Reliable Low Latency based on Retransmission and Spatial Diversity in slowly fading channels with co-channel interference
No full textThis paper presents the analysis of the statistics of latency and information theoretic capacity of an adaptive link with retransmission-spatial diversity in a scenario with co-channel interference. The paper focuses specifically on the delay of the wireless transmission component, measured from the instant a packet at the head of the queue is first transmitted until it is correctly received by the destination (considering retransmissions). The objective is to evaluate the ability of temporal and spatial diversity tools to achieve ultra-low values of latency as desired in future 5G and machine-to-machine (M2M) networks with real-time requirements. It is assumed that the source transmits information towards the destination in a Rayleigh fading spatially correlated channel. In case the instantaneous signal-to-interference-plus-noise (SINR) ratio has not surpassed a predetermined reception threshold, then the source engages in a persistent retransmission protocol. All the copies of the original transmission and subsequent retransmissions are stored in memory and processed at the destination using maximum ratio combining (MRC) to obtain a more reliable copy of the signal (a scheme also called retransmission diversity). The retransmission scheme stops once the instantaneous post-processing SINR achieves the desired target threshold. This persistent retransmission scheme can also be regarded as a security mechanism against interference jamming attacks. Since retransmissions are assumed to take place in a short time interval in order to achieve very low values of latency, they are modelled with statistical temporal correlation, which is explicitly introduced in the embedded Gaussian channel distribution model. Results suggest that retransmission diversity can provide good latency results in moderate to high values of SINR. However, at low SINR, a combination with other diversity sources will be necessary to achieve the desired target value.info:eu-repo/semantics/publishedVersio
- …
