Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9834000
Qiao Lan, Qunsong Zeng, P. Popovski, Deniz Gündüz, Kaibin Huang
Uploading high-dimensional features from edge devices to an edge server over wireless channels creates a communication bottleneck for edge inference. To tackle the challenge, we propose the progressive feature transmission (ProgressFTX) protocol, which minimizes the overhead by progressively transmitting features until a target confidence level is reached. The control of the protocol to accelerate inference is designed with two key operations. The first, importance-aware feature selection, guides the server to select the most discriminative feature dimensions. The second is transmission-termination control such that the feature transmission is stopped when the incremental uncertainty reduction by further transmission is outweighed by its communication cost. The indices of the selected features and transmission decision are fed back to the device in each slot. The sub-optimal policy is obtained for classification using a convolutional neural network. Experimental results on a real-world dataset shows that ProgressFTX can substantially reduce the communication latency compared to conventional feature pruning and random feature transmission.
{"title":"Progressive Transmission of High-Dimensional Data Features for Inference at the Network Edge","authors":"Qiao Lan, Qunsong Zeng, P. Popovski, Deniz Gündüz, Kaibin Huang","doi":"10.1109/spawc51304.2022.9834000","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9834000","url":null,"abstract":"Uploading high-dimensional features from edge devices to an edge server over wireless channels creates a communication bottleneck for edge inference. To tackle the challenge, we propose the progressive feature transmission (ProgressFTX) protocol, which minimizes the overhead by progressively transmitting features until a target confidence level is reached. The control of the protocol to accelerate inference is designed with two key operations. The first, importance-aware feature selection, guides the server to select the most discriminative feature dimensions. The second is transmission-termination control such that the feature transmission is stopped when the incremental uncertainty reduction by further transmission is outweighed by its communication cost. The indices of the selected features and transmission decision are fed back to the device in each slot. The sub-optimal policy is obtained for classification using a convolutional neural network. Experimental results on a real-world dataset shows that ProgressFTX can substantially reduce the communication latency compared to conventional feature pruning and random feature transmission.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130454471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9834008
Guoda Tian, Xuesong Cai, Tian Zhou, Weinan Wang, F. Tufvesson
Multi-carrier technique is a backbone for modern commercial networks. However, the performances of multi-carrier systems in general depend greatly on the qualities of acquired channel state information (CSI). In this paper, we propose a novel deep-learning based processing pipeline to estimate CSI for payload time-frequency resource elements. The proposed pipeline contains two cascaded subblocks, namely, an initial denoise network (IDN), and a resolution enhancement network (REN). In brief, IDN applies a novel two-step denoising structure while REN consists of pure fully-connected layers. Compared to existing works, our proposed processing architecture is more robust under lower signal-to-noise ratio scenarios and delivers generally a significant gain.
{"title":"Deep-Learning Based Channel Estimation for OFDM Wireless Communications","authors":"Guoda Tian, Xuesong Cai, Tian Zhou, Weinan Wang, F. Tufvesson","doi":"10.1109/spawc51304.2022.9834008","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9834008","url":null,"abstract":"Multi-carrier technique is a backbone for modern commercial networks. However, the performances of multi-carrier systems in general depend greatly on the qualities of acquired channel state information (CSI). In this paper, we propose a novel deep-learning based processing pipeline to estimate CSI for payload time-frequency resource elements. The proposed pipeline contains two cascaded subblocks, namely, an initial denoise network (IDN), and a resolution enhancement network (REN). In brief, IDN applies a novel two-step denoising structure while REN consists of pure fully-connected layers. Compared to existing works, our proposed processing architecture is more robust under lower signal-to-noise ratio scenarios and delivers generally a significant gain.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"13 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133424950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833981
K. Arunkumar, C. Murthy, P. Muralikrishna
In this paper, we develop a new waveform for communicating over a delay and time-scale spread wideband channel. This waveform, named Variable Bandwidth Multicarrier (VBMC) waveform, comprises multiple subcarriers that are constructed from chirp pulses used in radars and sonars, and is a multicarrier analogue of the sweep spread carrier waveform that time multiplexes the digital symbols onto a single chirp pulse. We design the subcarrier chirps to occupy progressively increasing, frequency-dependent bandwidth from the lower to upper frequency edge of the communication band. Due to this, the subcarriers of the VBMC waveform maintain their near mutual orthogonality even after passing through a delay and scale spread channel, resulting in low inter-carrier interference, and thereby facilitating a low complexity subcarrier-by-subcarrier decoding at the receiver. Numerical simulation of the bit error rate over delay-scale channels shows that the VBMC waveform outperforms the widely used Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) and the recently developed Orthogonal Time-Frequency Space (OTFS) waveforms.
{"title":"Variable Bandwidth Multicarrier Communications: A New Waveform for the Delay-Scale Channel","authors":"K. Arunkumar, C. Murthy, P. Muralikrishna","doi":"10.1109/spawc51304.2022.9833981","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833981","url":null,"abstract":"In this paper, we develop a new waveform for communicating over a delay and time-scale spread wideband channel. This waveform, named Variable Bandwidth Multicarrier (VBMC) waveform, comprises multiple subcarriers that are constructed from chirp pulses used in radars and sonars, and is a multicarrier analogue of the sweep spread carrier waveform that time multiplexes the digital symbols onto a single chirp pulse. We design the subcarrier chirps to occupy progressively increasing, frequency-dependent bandwidth from the lower to upper frequency edge of the communication band. Due to this, the subcarriers of the VBMC waveform maintain their near mutual orthogonality even after passing through a delay and scale spread channel, resulting in low inter-carrier interference, and thereby facilitating a low complexity subcarrier-by-subcarrier decoding at the receiver. Numerical simulation of the bit error rate over delay-scale channels shows that the VBMC waveform outperforms the widely used Cyclic Prefix Orthogonal Frequency Division Multiplexing (CP-OFDM) and the recently developed Orthogonal Time-Frequency Space (OTFS) waveforms.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131585620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833988
Dominik Semmler, M. Joham, W. Utschick
We propose efficient algorithms to solve the sum-rate maximization in the Intelligent Reflecting Surface (IRS) assisted Multiple-Input Multiple-Output (MIMO) Downlink (DL) scenario. The recommended methods are based on Linear Successive Allocation (LISA), a well performing linear precoding algorithm for the traditional MIMO DL. Taking LISA as a basis, we can exploit its characteristic zero-forcing structure which allows to obtain a special form of alternating optimization. This special form enables a quick convergence and we observe a reduced iteration number together with a good performance of the proposed methods in the simulations.
{"title":"Linear Precoding in the Intelligent Reflecting Surface Assisted MIMO Broadcast Channel","authors":"Dominik Semmler, M. Joham, W. Utschick","doi":"10.1109/spawc51304.2022.9833988","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833988","url":null,"abstract":"We propose efficient algorithms to solve the sum-rate maximization in the Intelligent Reflecting Surface (IRS) assisted Multiple-Input Multiple-Output (MIMO) Downlink (DL) scenario. The recommended methods are based on Linear Successive Allocation (LISA), a well performing linear precoding algorithm for the traditional MIMO DL. Taking LISA as a basis, we can exploit its characteristic zero-forcing structure which allows to obtain a special form of alternating optimization. This special form enables a quick convergence and we observe a reduced iteration number together with a good performance of the proposed methods in the simulations.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130493366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates a double-IRS cooperatively assisted system, where a multi-antenna BS serves a single-antenna user with the help of two multi-element IRSs connected by the inter-IRS channel. The channel between any two nodes is modeled with Rician fading. The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, and the two IRSs adopt a cooperative quasi-static phase shift design. The goal is to maximize the average achievable rate, which can be reflected by the average channel power of the equivalent channel, at low channel estimation cost and phase adjustment costs and computational complexity. First, we obtain a tractable expression of the average channel power of the equivalent channel. Then, we jointly optimize the phase shifts of the two IRSs to maximize the average channel power of the equivalent channel. We propose a computationally efficient iterative algorithm to obtain a stationary point of the non-convex problem. We show that the optimal quasi-static phase shift design for the double-IRS cooperatively assisted system achieves an average channel power gain in order identical to that of the optimal instantaneous CSI-adaptive phase shift design for the same system and higher than that of the optimal quasi-static phase shift design for a counterpart single-IRS assisted system. Finally, we numerically demonstrate notable gains of the proposed cooperative quasi-static phase shift design over the existing solutions. To our knowledge, this is the first work that optimizes the quasi-static phase shift design of a double-IRS cooperatively assisted system and characterizes its advantage over the optimal quasi-static phase shift design of the counterpart single-IRS-assisted system.
{"title":"Quasi-Static Phase Shift Design for A Double-IRS Cooperatively Assisted System","authors":"Gengfa Ding, Ying Cui, L. Hu, Feng Yang, Lianghui Ding, Xin Xu","doi":"10.1109/spawc51304.2022.9833959","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833959","url":null,"abstract":"This paper investigates a double-IRS cooperatively assisted system, where a multi-antenna BS serves a single-antenna user with the help of two multi-element IRSs connected by the inter-IRS channel. The channel between any two nodes is modeled with Rician fading. The BS adopts the instantaneous CSI-adaptive maximum-ratio transmission (MRT) beamformer, and the two IRSs adopt a cooperative quasi-static phase shift design. The goal is to maximize the average achievable rate, which can be reflected by the average channel power of the equivalent channel, at low channel estimation cost and phase adjustment costs and computational complexity. First, we obtain a tractable expression of the average channel power of the equivalent channel. Then, we jointly optimize the phase shifts of the two IRSs to maximize the average channel power of the equivalent channel. We propose a computationally efficient iterative algorithm to obtain a stationary point of the non-convex problem. We show that the optimal quasi-static phase shift design for the double-IRS cooperatively assisted system achieves an average channel power gain in order identical to that of the optimal instantaneous CSI-adaptive phase shift design for the same system and higher than that of the optimal quasi-static phase shift design for a counterpart single-IRS assisted system. Finally, we numerically demonstrate notable gains of the proposed cooperative quasi-static phase shift design over the existing solutions. To our knowledge, this is the first work that optimizes the quasi-static phase shift design of a double-IRS cooperatively assisted system and characterizes its advantage over the optimal quasi-static phase shift design of the counterpart single-IRS-assisted system.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132990740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9834012
Xiang Zhang, Mingyue Ji
We present a novel Packet Type (PT)-based design framework for the finite-length analysis of Device-to-Device (D2D) coded caching. By the exploitation of the asymmetry in the coded delivery phase, two fundamental forms of subpacketization reduction gain for D2D coded caching, i.e., the subfile saving gain and the further splitting saving gain, are identified in the PT framework. The proposed framework features a streamlined design process which uses several key concepts including user grouping, subfile and packet types, multicast group types, transmitter selection, local/global further splitting factor, and PT design as an integer optimization. In particular, based on a predefined user grouping, the subfile and multicast group types can be determined and the cache placement of the users can be correspondingly determined. In this stage, subfiles of certain types can be potentially excluded without being used in the designed caching scheme, which we refer to as subfile saving gain. In the delivery phase, by a careful selection of the transmitters within each type of multicast groups, a smaller number of packets that each subfile needs to be further split into can be achieved, leading to the further splitting saving gain. The joint effect of these two gains results in an overall subpacketization reduction compared to the Ji-Caire-Molisch (JCM) scheme [1]. Using the PT framework, a new class of D2D caching schemes is constructed with order reduction on subpacketization but the same rate when compared to the JCM scheme.
{"title":"Finite-length Analysis of D2D Coded Caching via Exploiting Asymmetry in Delivery","authors":"Xiang Zhang, Mingyue Ji","doi":"10.1109/spawc51304.2022.9834012","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9834012","url":null,"abstract":"We present a novel Packet Type (PT)-based design framework for the finite-length analysis of Device-to-Device (D2D) coded caching. By the exploitation of the asymmetry in the coded delivery phase, two fundamental forms of subpacketization reduction gain for D2D coded caching, i.e., the subfile saving gain and the further splitting saving gain, are identified in the PT framework. The proposed framework features a streamlined design process which uses several key concepts including user grouping, subfile and packet types, multicast group types, transmitter selection, local/global further splitting factor, and PT design as an integer optimization. In particular, based on a predefined user grouping, the subfile and multicast group types can be determined and the cache placement of the users can be correspondingly determined. In this stage, subfiles of certain types can be potentially excluded without being used in the designed caching scheme, which we refer to as subfile saving gain. In the delivery phase, by a careful selection of the transmitters within each type of multicast groups, a smaller number of packets that each subfile needs to be further split into can be achieved, leading to the further splitting saving gain. The joint effect of these two gains results in an overall subpacketization reduction compared to the Ji-Caire-Molisch (JCM) scheme [1]. Using the PT framework, a new class of D2D caching schemes is constructed with order reduction on subpacketization but the same rate when compared to the JCM scheme.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133640143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833937
K. Ntougias, I. Krikidis
This paper considers an intelligent reflecting surface (IRS)-aided multiple-input single-output broadcasting system for power-splitting (PS) simultaneous wireless information and power transfer, where the access point adopts an analog/digital architecture. We aim at jointly optimizing the hybrid precoder, passive beamformer (PB), and PS ratios, such that the transmit sum-power is minimized subject to the quality-of-service requirements of the receivers. We develop a two-layer, penalty-based block coordinate descent algorithm to solve this challenging non-convex optimization problem and employ manifold optimization to update the analog precoding weights and IRS phase shifts. We also derive a low-complexity, decoupled iterative design where the analog precoder is updated via the stochastic gradient descent algorithm and the PB is computed via the successive convex approximation method. Numerical simulations highlight the performance gains of the proposed schemes over various benchmarks and shed light on the impact of the parameter settings on the performance.
{"title":"Joint Hybrid/Passive Beamforming Design in IRS-aided Multi-User MISO Systems for PS-SWIPT","authors":"K. Ntougias, I. Krikidis","doi":"10.1109/spawc51304.2022.9833937","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833937","url":null,"abstract":"This paper considers an intelligent reflecting surface (IRS)-aided multiple-input single-output broadcasting system for power-splitting (PS) simultaneous wireless information and power transfer, where the access point adopts an analog/digital architecture. We aim at jointly optimizing the hybrid precoder, passive beamformer (PB), and PS ratios, such that the transmit sum-power is minimized subject to the quality-of-service requirements of the receivers. We develop a two-layer, penalty-based block coordinate descent algorithm to solve this challenging non-convex optimization problem and employ manifold optimization to update the analog precoding weights and IRS phase shifts. We also derive a low-complexity, decoupled iterative design where the analog precoder is updated via the stochastic gradient descent algorithm and the PB is computed via the successive convex approximation method. Numerical simulations highlight the performance gains of the proposed schemes over various benchmarks and shed light on the impact of the parameter settings on the performance.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"33 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131894718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833995
A. Fuchs, K. Witrisal
For time-of-flight-based wireless positioning systems operating in (dense) multipath propagation channels, the accuracy is severely influenced by the signal bandwidth, because the dense multipath component (DMC) interferes with the desired, information-bearing line-of-sight (LoS) signal. Several such systems make use of bandwidth-limited frequency resources, e.g. the industrial, scientific and medical (ISM) bands, therefore the achievable position estimation accuracy is limited. In this paper, we propose a model-based delay-estimation method which takes into account a parametric model of the DMC and thus exploits the signal energy carried in the DMC. The resulting algorithm exhibits an enhanced delay estimation accuracy and remarkable robustness in non-LoS situations. The algorithm is benchmarked against a maximum likelihood (ML) estimator not incorporating a model for the DMC and against the estimated Cramér-Rao lower bound (CRLB) in presence of DMC. Results show a significant performance gain for scenarios where the conventional ML estimator performs poorly. An evaluation of measurement data validates the simulation, showing a root-mean-square error (RMSE) of 33.4 cm compared to 1.89 m for the conventional ML estimator, at a signal bandwidth of 80 MHz.
{"title":"Time-of-Arrival Estimation for Positioning in Bandwidth-Limited Dense Multipath Channels","authors":"A. Fuchs, K. Witrisal","doi":"10.1109/spawc51304.2022.9833995","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833995","url":null,"abstract":"For time-of-flight-based wireless positioning systems operating in (dense) multipath propagation channels, the accuracy is severely influenced by the signal bandwidth, because the dense multipath component (DMC) interferes with the desired, information-bearing line-of-sight (LoS) signal. Several such systems make use of bandwidth-limited frequency resources, e.g. the industrial, scientific and medical (ISM) bands, therefore the achievable position estimation accuracy is limited. In this paper, we propose a model-based delay-estimation method which takes into account a parametric model of the DMC and thus exploits the signal energy carried in the DMC. The resulting algorithm exhibits an enhanced delay estimation accuracy and remarkable robustness in non-LoS situations. The algorithm is benchmarked against a maximum likelihood (ML) estimator not incorporating a model for the DMC and against the estimated Cramér-Rao lower bound (CRLB) in presence of DMC. Results show a significant performance gain for scenarios where the conventional ML estimator performs poorly. An evaluation of measurement data validates the simulation, showing a root-mean-square error (RMSE) of 33.4 cm compared to 1.89 m for the conventional ML estimator, at a signal bandwidth of 80 MHz.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116077331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833947
Mateen Ashraf, T. Riihonen
This paper studies an intelligent reflecting surface (IRS) assisted wireless communication system with multiple downlink data and energy harvesting users. We assume that base station uses non-orthogonal multiple access (NOMA) for transmission and downlink users employ successive interference cancellation to decode their information from the received signal. With this setting, our goal is to maximize the harvested energy at the energy harvesting users while guaranteeing the minimum rate requirements of the individual data users. We propose an alternating optimization based algorithm, where semidefinite relaxation is used to obtain the optimal beamforming design at the base station and the IRS. Specifically, an iterative rank minimization approach is used to obtain the optimal reflection phase vector at the IRS. The convergence of the proposed algorithm is also proved. Finally, the efficacy of the proposed algorithm is demonstrated with the help of simulation results.
{"title":"Reflecting Surface Assisted Energy Harvesting with Optimized NOMA Downlink Transmissions","authors":"Mateen Ashraf, T. Riihonen","doi":"10.1109/spawc51304.2022.9833947","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833947","url":null,"abstract":"This paper studies an intelligent reflecting surface (IRS) assisted wireless communication system with multiple downlink data and energy harvesting users. We assume that base station uses non-orthogonal multiple access (NOMA) for transmission and downlink users employ successive interference cancellation to decode their information from the received signal. With this setting, our goal is to maximize the harvested energy at the energy harvesting users while guaranteeing the minimum rate requirements of the individual data users. We propose an alternating optimization based algorithm, where semidefinite relaxation is used to obtain the optimal beamforming design at the base station and the IRS. Specifically, an iterative rank minimization approach is used to obtain the optimal reflection phase vector at the IRS. The convergence of the proposed algorithm is also proved. Finally, the efficacy of the proposed algorithm is demonstrated with the help of simulation results.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124011380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-04DOI: 10.1109/spawc51304.2022.9833938
Hanxiao Ge, Navneet Garg, T. Ratnarajah
This paper proposes a generalized superimposed channel estimation scheme for uplink cell-free massive multiple-input multiple-output orthogonal frequency-division multiplexing (mMIMO-OFDM) system. We consider that some subcarriers transmit superimposed pilots and information symbols; others only carry information symbols, which is different from the standard OFDM system and reduce the pilot reused and enhanced spectral efficiency. The estimated channels are used to detect the data streams, and consequently, bit error rate (BER) and sum-rate performances are evaluated. This work considers two levels of receiver cooperations (centralized processing and local processing). We show that centralized processing provides much lower normalized mean-squared error (NMSE) and BER than that for local processing, and it is also shown that the generalized superimposed training scheme gives better performance in channel estimation compared with the conventional superimposed training (ST) and the regular pilots (RP) scheme.
{"title":"Channel Estimation for Generalized Superimposed Cell-free Massive MIMO-OFDM Systems","authors":"Hanxiao Ge, Navneet Garg, T. Ratnarajah","doi":"10.1109/spawc51304.2022.9833938","DOIUrl":"https://doi.org/10.1109/spawc51304.2022.9833938","url":null,"abstract":"This paper proposes a generalized superimposed channel estimation scheme for uplink cell-free massive multiple-input multiple-output orthogonal frequency-division multiplexing (mMIMO-OFDM) system. We consider that some subcarriers transmit superimposed pilots and information symbols; others only carry information symbols, which is different from the standard OFDM system and reduce the pilot reused and enhanced spectral efficiency. The estimated channels are used to detect the data streams, and consequently, bit error rate (BER) and sum-rate performances are evaluated. This work considers two levels of receiver cooperations (centralized processing and local processing). We show that centralized processing provides much lower normalized mean-squared error (NMSE) and BER than that for local processing, and it is also shown that the generalized superimposed training scheme gives better performance in channel estimation compared with the conventional superimposed training (ST) and the regular pilots (RP) scheme.","PeriodicalId":423807,"journal":{"name":"2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129308203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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