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See detailReliability of Spectrum-Efficient Mixed Satellite-Underwater Systems
Gamal, Christina; Elsayed, Mohamed; Samir, Ahmed et al

in IEEE Open Journal of the Communications Society (2022), 3

The combination of radio-frequency (RF) communication and underwater optical wireless communication (UOWC) plays a vital role in the underwater Internet of Things (UIoT). This correspondence proposes a ... [more ▼]

The combination of radio-frequency (RF) communication and underwater optical wireless communication (UOWC) plays a vital role in the underwater Internet of Things (UIoT). This correspondence proposes a dual-hop hybrid satellite underwater system that exploits non-orthogonal multiple access (NOMA) as a spectrum-efficient access technique. The RF link from the satellite to the relay on an oil platform is presumptively subject to a Shadowed-Rician (SR) fading, while the UOWC channels from the relay to the underwater destinations are suggested to follow Exponential-Generalized Gamma (EGG) distributions. The reliability of the system is characterized in terms of both underwater destinations and system outage probabilities (OPs). We derive new closed-form expressions for the OPs under imperfect successive interference cancellation (SIC) conditions. Furthermore, the asymptotic OP and the diversity order (DO) are obtained to learn more about the system’s performance. The results are verified through an extensive representative Monte-Carlo simulation. Also, we investigate the performance against the turbulence of the salty water, air bubbles level (BL), temperature gradients (TG), shadowing parameters, and satellite pointing errors due to satellite motion, even if the beam is pointed at the center of the directive antenna relay, the beam will randomly oscillate. Finally, we contrast our approach with the conventional orthogonal multiple access (OMA) scheme to demonstrate its superiority. [less ▲]

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See detailTask-Oriented Data Compression for Multi-Agent Communications Over Bit-Budgeted Channels
Mostaani, Arsham UL; Vu, Thang Xuan UL; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2022)

Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their ... [more ▼]

Various applications for inter-machine communications are on the rise. Whether it is for autonomous driving vehicles or the internet of everything, machines are more connected than ever to improve their performance in fulfilling a given task. While in traditional communications the goal has often been to reconstruct the underlying message, under the emerging task-oriented paradigm, the goal of communication is to enable the receiving end to make more informed decisions or more precise estimates/computations. Motivated by these recent developments, in this paper, we perform an indirect design of the communications in a multi-agent system (MAS) in which agents cooperate to maximize the averaged sum of discounted one-stage rewards of a collaborative task. Due to the bit-budgeted communications between the agents, each agent should efficiently represent its local observation and communicate an abstracted version of the observations to improve the collaborative task performance. We first show that this problem can be approximated as a form of data-quantization problem which we call task-oriented data compression (TODC). We then introduce the state-aggregation for information compression algorithm (SAIC) to solve the formulated TODC problem. It is shown that SAIC is able to achieve near-optimal performance in terms of the achieved sum of discounted rewards. The proposed algorithm is applied to a geometric consensus problem and its performance is compared with several benchmarks. Numerical experiments confirm the promise of this indirect design approach for task-oriented multi-agent communications. [less ▲]

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See detailUser selection for massive MIMO under line-of-sight propagation
Chaves, Rafael da Silva; Cetin, Ediz; Lima, Markus V. S. et al

in IEEE Open Journal of the Communications Society (2022)

This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is ... [more ▼]

This paper provides a review of user selection algorithms for massive multiple-input multiple-output (MIMO) systems under the line-of-sight (LoS) propagation model. Although the LoS propagation is extremely important to some promising technologies, like in millimeter-wave communications, massive MIMO systems are rarely studied under this propagation model. This paper fills this gap by providing a comprehensive study encompassing several user selection algorithms, different linear precoders and simulation setups, and also considers the effect of partial channel state information (CSI). One important result is the existence of practical cases in which the LoS propagation model may lead to significant levels of interference among users within a cell; these cases are not satisfactorily addressed by the existing user selection algorithms. Motivated by this issue, a new user selection algorithm based on inter-channel interference (ICI) called ICI-based selection (ICIBS) is proposed. Unlike other techniques, the ICIBS accounts for the ICI in a global manner, thus yielding better results, especially in cases where there are many users interfering with each other. In such scenarios, simulation results show that when compared to the competing algorithms, the proposed approach provided an improvement of at least 10.9% in the maximum throughput and 7.7% in the 95%-probability throughput when half of the users were selected. [less ▲]

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See detailDemand and Interference Aware Adaptive Resource Management for High Throughput GEO Satellite Systems
Abdu, Tedros Salih UL; Kisseleff, Steven UL; Lagunas, Eva UL et al

in IEEE Open Journal of the Communications Society (2022)

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS ... [more ▼]

The scarce spectrum and power resources, the inter-beam interference, together with the high traffic demand, pose new major challenges for the next generation of Very High Throughput Satellite (VHTS) systems. Accordingly, future satellites are expected to employ advanced resource/interference management techniques to achieve high system spectrum efficiency and low power consumption while ensuring user demand satisfaction. This paper proposes a novel demand and interference aware adaptive resource management for geostationary (GEO) VHTS systems. For this, we formulate a multi-objective optimization problem to minimize the total transmit power consumption and system bandwidth usage while matching the offered capacity with the demand per beam. In this context, we consider resource management for a system with full-precoding, i.e. all beams are precoded; without precoding, i.e. no precoding is applied to any beam; and with partial precoding, i.e. only some beams are precoded. The nature of the problem is non-convex and we solve it by jointly using the Dinkelbach and Successive Convex Approximation (SCA) methods. The simulation results show that the proposed method outperforms the benchmark schemes. Specifically, we show that the proposed method requires low resource consumption, low computational time, and simultaneously achieves a high demand satisfaction. [less ▲]

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See detailBayesian Poisson Factorization with SideInformation for User Interest Prediction inHierarchical Edge-Caching Systems
Mehrizi, Sajad; Chatzinotas, Symeon UL

in IEEE Open Journal of the Communications Society (2022), 3

Edge-caching is an effective solution to cope withthe unprecedented data traffic growth by storing contents inthe vicinity of end-users. In this paper, we formulate a hier-archical caching policy where ... [more ▼]

Edge-caching is an effective solution to cope withthe unprecedented data traffic growth by storing contents inthe vicinity of end-users. In this paper, we formulate a hier-archical caching policy where the end-users and cellular basestation (BS) are equipped with limited cache capacity with theobjective of minimizing the total data traffic load in the network.The caching policy is a nonlinear combinatorial programmingproblem and difficult to solve. To tackle the issue, we design aheuristic algorithm as an approximate solution which can besolved efficiently. Moreover, to proactively serve the users, itis of high importance to extract useful information from datarequests and predict user interest about contents. In practice,the data often containimplicit feedbackfrom users which isquite noisy and complicates the reliable prediction of userinterest. In this regard, we introduce a Bayesian Poisson matrixfactorization model which utilizes the available side informationabout contents to effectively filter out the noise in the data andprovide accurate prediction. Subsequently, we design an efficientMarkov chain Monte Carlo (MCMC) method to perform theposterior approximation. Finally, a real-world dataset is appliedto the proposed proactive caching-prediction scheme and ourresults show significant improvement over several commonly-used methods. For example, when the BS and the users havecaches with storage of25%and10%of the total contents sizerespectively, our approach yields around8%improvement withrespect to the state-of-the-art approach in terms of cachingperformance. [less ▲]

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See detailAmbient Backscatter Assisted Co-Existence in Aerial-IRS Wireless Networks
Solanki, Sourabh UL; Gautam, Sumit; Sharma, Shree Krishna et al

in IEEE Open Journal of the Communications Society (2022), 3

Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks ... [more ▼]

Ambient backscatter communication (AmBC) is an emerging technology that has the potential to offer spectral- and energy-efficient solutions for the next generation wireless communications networks, especially for the Internet of Things (IoT). Intelligent reflecting surfaces (IRSs) are also perceived to be an integral part of the beyond 5G systems to complement the traditional relaying scheme. To this end, this paper proposes a novel system design that enables the co-existence of a backscattering secondary system with the legacy primary system. This co-existence is primarily driven by leveraging the AmBC technique in IRS-assisted unmanned aerial vehicle (UAV) networks. More specifically, an aerial-IRS mounted on a UAV is considered to be employed for cooperatively relaying the transmitted signal from a terrestrial primary source node to a user equipment on the ground. Meanwhile, capitalizing on the AmBC technology, a backscatter capable terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency signals from the UAV-IRS. We comprehensively analyze the performance of the proposed design framework with co-existing systems by deriving the outage probability and ergodic spectral efficiency expressions. Moreover, we also investigate the asymptotic behaviour of outage performance in high transmit power regimes for both primary and secondary systems. Importantly, we analyze the performance of the primary system by considering two different scenarios i.e., optimal phase shifts design and random phase shifting at IRS. Finally, based on the analytical performance assessment, we present numerical results to provide various useful insights and also provide simulation results to corroborate the derived theoretical results. [less ▲]

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailTrend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Mehrizi Rahmat Abadi, Sajad UL; X. Vu, Thang; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), (4369),

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See detailReconfigurable Intelligent Surface Optimal Placement in Millimeter-Wave Networks
Ntontin, Konstantinos UL; Boulogeorgos, Alexandros-Apostolos A.; Selimis, Dimitrios et al

in IEEE Open Journal of the Communications Society (2021), 2

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the ... [more ▼]

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the relationship between the transmission beam footprint at the RIS plane and the RIS size. Subsequently, based on the model we derive the end-to-end expression of the received signal power and, furthermore, provide approximate closed-form expressions in the case that the RIS size is either much smaller or at least equal to the transmission beam footprint. Moreover, building upon the expressions, we derive the optimal RIS placement that maximizes the end-to-end signal-to-noise ratio. Finally, we substantiate the analytical findings by means of simulations, which reveal important trends regarding the optimal RIS placement according to the system parameters. [less ▲]

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See detailDemand-Based Adaptive Multi-Beam Pattern and Footprint Planning for High Throughput GEO Satellite Systems
Jubba Honnaiah, Puneeth UL; Maturo, Nicola; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021)

The current broadband coverage area requisites and the expected user demand is satisfied by the state of the art satellite industry by using multiple spot beams of high throughput satellites with fixed ... [more ▼]

The current broadband coverage area requisites and the expected user demand is satisfied by the state of the art satellite industry by using multiple spot beams of high throughput satellites with fixed multi-beam pattern and footprint planning. However, in recent years, new mobile broadband users with dynamic traffic demand are requesting for services in remote geographical locations such as air (aeroplanes) and water (ships). Furthermore, the expected demand varies with time and geographical location of the users. Hence, a practical approach to meet such heterogeneous demand is to plan adaptive beams to the satellites equipped with beamforming capabilities. In this paper, we study the state of the art fixed multi-beam pattern and footprint plan and show its drawbacks to support the non-uniformly distributed user terminals and varying traffic demands. To end this, we propose an adaptive multi-beam pattern and footprint plan where we design spot beams with flexible size and position based on the spatial clustering of the users in order to increase the flexibility of the high throughput satellite system. Numerical simulations demonstrate the high system performance of the proposed methodology. [less ▲]

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See detailMultipair Two-Way DF Relaying with Cell-Free Massive MIMO
PAPAZAFEIROPOULOS, ANASTASIOS K.; KOURTESSIS, PANDELIS; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021), 2

We consider a two-way half-duplex decode-and-forward (DF) relaying system with multiple pairs of single-antenna users assisted by a cell-free (CF) massive multiple-input multiple-output (mMIMO ... [more ▼]

We consider a two-way half-duplex decode-and-forward (DF) relaying system with multiple pairs of single-antenna users assisted by a cell-free (CF) massive multiple-input multiple-output (mMIMO) architecture with multiple-antenna access points (APs). Under the practical constraint of imperfect channel state information (CSI), we derive the achievable sum spectral efficiency (SE) for a finite number of APs with maximum ratio (MR) linear processing for both reception and transmission in closed-form. Notably, the proposed CF mMIMO relaying architecture, exploiting the spatial diversity, and providing better coverage, outperforms the conventional collocated mMIMO deployment. Moreover, we shed light on the power-scaling laws maintaining a specific SE as the number of APs grows. A thorough examination of the interplay between the transmit powers per pilot symbol and user/APs takes place, and useful conclusions are extracted. Finally, differently to the common approach for power control in CF mMIMO systems, we design a power allocation scheme maximizing the sum SE. [less ▲]

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See detailDemand-Based Adaptive Multi-Beam Pattern and Footprint Planning for High Throughput GEO Satellite Systems
Jubba Honnaiah, Puneeth UL; Maturo, Nicola; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021)

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See detailData-driven Precoded MIMO Detection Robust to Channel Estimation Errors
Mayouche, Abderrahmane UL; Alves Martins, Wallace UL; Chatzinotas, Symeon UL et al

in IEEE Open Journal of the Communications Society (2021)

We study the problem of symbol detection in downlink coded multiple-input multiple-output (MIMO) systems with precoding and without the explicit knowledge of the channel-state information (CSI) at the ... [more ▼]

We study the problem of symbol detection in downlink coded multiple-input multiple-output (MIMO) systems with precoding and without the explicit knowledge of the channel-state information (CSI) at the receiver. In this context, we investigate the impact of imperfect CSI at the transmitter (CSIT) on the detection performance. We first model the CSIT degradation based on channel estimation errors to investigate its impact on the detection performance at the receiver. To mitigate the effect of CSIT deterioration at the latter, we propose learning based techniques for hard and soft detection that use downlink precoded pilot symbols as training data. We note that these pilots are originally intended for signal-to-interference-plus-noise ratio (SINR) estimation. We validate the approach by proposing a lightweight implementation that is suitable for online training using several state-of-the-art classifiers. We compare the bit error rate (BER) and the runtime complexity of the proposed approaches where we achieve superior detection performance in harsh channel conditions while maintaining low computational requirements. Specifically, numerical results show that severe CSIT degradation impedes the correct detection when a conventional detector is used. However, the proposed learning-based detectors can achieve good detection performance even under severe CSIT deterioration, and can yield 4-8 dB power gain for BER values lower than 10-4 when compared to the classic linear minimum mean square error (MMSE) detector. [less ▲]

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See detailCarrier Aggregation in Satellite Communications: Impact and Performance Study
Kibria, Mirza; Lagunas, Eva UL; Maturo, Nicola UL et al

in IEEE Open Journal of the Communications Society (2020)

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See detailWeighted Sum-SINR and Fairness Optimization for SWIPT-Multigroup Multicasting Systems with Heterogeneous Users
Gautam, Sumit UL; Lagunas, Eva UL; Sharma, Shree Krishna UL et al

in IEEE Open Journal of the Communications Society (2020)

The development of next generation wireless communication systems focuses on the expansion of existing technologies, while ensuring an accord between various devices within a system. In this paper, we ... [more ▼]

The development of next generation wireless communication systems focuses on the expansion of existing technologies, while ensuring an accord between various devices within a system. In this paper, we target the aspect of precoder design for simultaneous wireless information and power transmission (SWIPT) in a multi-group (MG) multicasting (MC) framework capable of handling heterogeneous types of users, viz., information decoding (ID) specific, energy harvesting (EH) explicit, and/or both ID and EH operations concurrently. Precoding is a technique well-known for handling the inter-user interference in multi-user systems, however, the joint design with SWIPT is not yet fully exploited. Herein, we investigate the potential benefits of having a dedicated precoder for the set of users with EH demands, in addition to the MC precoding. We study the system performance of the aforementioned system from the perspectives of weighted sum of signal-to-interference-plus-noise-ratio (SINR) and fairness. In this regard, we formulate the precoder design problems for (i) maximizing the weighted sum of SINRs at the intended users and (ii) maximizing the minimum of SINRs at the intended users; both subject to the constraints on minimum (non-linear) harvested energy, an upper limit on the total transmit power and a minimum SINR required to close the link. We solve the above-mentioned problems using distinct iterative algorithms with the help of semi-definite relaxation (SDR) and slack-variable replacement (SVR) techniques, following suitable transformations pertaining the problem convexification. The main novelty of the proposed approach lies in the ability to jointly design the MC and EH precoders for serving the heterogeneously classified ID and EH users present in distinct groups, respectively. We illustrate the comparison between the proposed weighted sum-SINR and fairness models via simulation results, carried out under various parameter values and operating conditions. [less ▲]

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See detailLearning-Assisted Eavesdropping and Symbol-Level Precoding Countermeasures for Downlink MU-MISO Systems
Mayouche, Abderrahmane UL; Spano, Danilo UL; Tsinos, Christos UL et al

in IEEE Open Journal of the Communications Society (2020), 1

In this work, we introduce a machine-learning (ML) based detection attack, where an eavesdropper (Eve) is able to learn the symbol detection function based on precoded pilots. With this ability, an Eve ... [more ▼]

In this work, we introduce a machine-learning (ML) based detection attack, where an eavesdropper (Eve) is able to learn the symbol detection function based on precoded pilots. With this ability, an Eve can correctly detect symbols with a high probability. To counteract this attack, we propose a novel symbol-level precoding (SLP) scheme that enhances physical-layer security (PLS) while guaranteeing a constructive interference effect at the intended users. Contrary to conventional SLP schemes, the proposed scheme is robust to the ML-based attack. In particular, the proposed scheme enhances security by designing Eve's received signal to lie at the boundaries of the detection regions. This distinct design causes Eve's detection decisions to be based almost purely on noise. The proposed countermeasure is then extended to account for multi-antennas at the Eve and also for multi-level modulation schemes. In the numerical results, we validate both the detection attack and the countermeasures and show that this gain in security can be achieved at the expense of only a small additional power consumption at the transmitter, and more importantly, these benefits are obtained without affecting the performance at the intended user. [less ▲]

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See detailJoint Power and Resource Block Allocation for Mixed-Numerology-Based 5G Downlink Under Imperfect CSI
Korrai, Praveenkumar UL; Lagunas, Eva UL; Bandi, Ashok UL et al

in IEEE Open Journal of the Communications Society (2020), 1

Fifth-generation (5G) of wireless networks are expected to accommodate different services with contrasting quality of service (QoS) requirements within a common physical infrastructure in an efficient way ... [more ▼]

Fifth-generation (5G) of wireless networks are expected to accommodate different services with contrasting quality of service (QoS) requirements within a common physical infrastructure in an efficient way. In this article, we address the radio access network (RAN) slicing problem and focus on the three 5G primary services, namely, enhanced mobile broadband (eMBB), ultra-reliable and lowlatency communications (URLLC) and massive machine-type communications (mMTC). In particular, we formulate the joint allocation of power and resource blocks to the heterogeneous users in the downlink targeting the transmit power minimization and by considering mixed numerology-based frame structures. Most importantly, the proposed scheme does not only consider the heterogeneous QoS requirements of each service, but also the queue status of each user during the scheduling of resource blocks. In addition, imperfect Channel State Information (CSI) is considered by including an outage probabilistic constraint into the formulation. The resulting non-convex problem is converted to a more tractable problem by exploiting Big-M formulation, probabilistic to non-probabilistic transformation, binary relaxation and successive convex approximation (SCA). The proposed solution is evaluated for different mixed-numerology resource grids within the context of strict slice-isolation and slice-aware radio resource management schemes via extensive numerical simulations. [less ▲]

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