Analytic Modeling for Grant-Free Transmission in Cell-Free Massive MIMO: A Stochastic Geometry Approach

Success Probability ◽

Closed Form Expression ◽

Disk Model ◽

<p>Cell-free (CF) massive multiple-input multiple-output (MIMO), as a promising network architecture for beyond the fifth generation (5G), has a great potential to support grant-free (GF) transmission for machine-type communication (MTC). To shed light on this subject, this work aims to model and evaluate the performance of GF transmission in CF massive MIMO under a realistic network deployment scenario, where the spatial locations of both access points (APs) and devices are assumed to be random in nature. In particular, by capitalizing on the distinctive CF network architecture and features, we design a new two-disk based geometric model for GF transmission, which facilitates analysis and understanding in CF massive MIMO. Based on the proposed two-disk model, we derive an approximated closed-form expression for the access success probability by leveraging on techniques from stochastic geometry, and investigate the impact of different key system parameters on the network performance. To highlight the performance superiority of CF massive MIMO, we further provide a comparative analysis by using an analogous single-disk model in an equivalent co-located massive MIMO network. Simulation results verify our analysis and demonstrate that CF massive MIMO is able to significantly outperform its co-located counterpart in terms of access success probability and provide robust performance against increased access density, which well suits to crowd scenarios.</p>

A Statistical Estimation of 5G Massive MIMO Networks’ Exposure Using Stochastic Geometry in mmWave Bands

Applied Sciences ◽

10.3390/app10238753 ◽

2020 ◽

Vol 10 (23) ◽

pp. 8753

Author(s):

Maarouf Al Hajj ◽

Shanshan Wang ◽

Lam Thanh Tu ◽

Soumaya Azzi ◽

Joe Wiart

Keyword(s):

Stochastic Geometry ◽

Massive Mimo ◽

Path Loss ◽

Transmission Probability ◽

Base Station ◽

Channel Gain ◽

Closed Form Expression ◽

Mimo Antenna ◽

This paper aims to derive an analytical modelling of the downlink exposure in 5G massive Multiple Input Multiple Output (MIMO) antenna networks using stochastic geometry. The Poisson point process (PPP) is assumed for base station (BS) distribution. The power received at the transmitter is modeled as a shot-noise process with a modified power law. The distributions of 5G massive MIMO antenna gain and channel gain were obtained by fitting simulation results from the NYUSIM channel simulator. The fitted distributions, e.g., exponential and gamma distribution for antenna and channel gain respectively, were then implemented into an analytical framework. In this paper, we obtained the closed-form expression of the moment-generating function (MGF) for the total exposure in the network. The framework is then validated by numerical simulations. The sensitivity analysis is carried out to investigate the impact of key parameters, e.g., BS density, path loss exponent, and transmission probability. We then proved and quantified the significant impact the transmission probability on global exposure, which indicates the importance of considering the network usage in 5G exposure estimations.

Improved Water-Filling Power Allocation for Energy-Efficient Massive MIMO Downlink Transmissions

International Journal of Electronics and Telecommunications ◽

10.1515/eletel-2017-0011 ◽

2017 ◽

Vol 63 (1) ◽

pp. 79-84

Author(s):

M. K Noor Shahida ◽

Rosdiadee Nordin ◽

Mahamod Ismail

Keyword(s):

Power Allocation ◽

Network Architecture ◽

Massive Mimo ◽

Base Station ◽

Downlink Transmission ◽

Allocation Algorithm ◽

Mimo Antenna ◽

Water Filling ◽

Water Filling Algorithm

Abstract Energy Efficiency (EE) is becoming increasingly important for wireless communications and has caught more attention due to steadily rising energy costs and environmental concerns. Recently, a new network architecture known as Massive Multiple-Input Multiple-Output (MIMO) has been proposed with the remarkable potential to achieve huge gains in EE with simple linear processing. In this paper, a power allocation algorithm is proposed for EE to achieve the optimal EE in Massive MIMO. Based on the simplified expression, we develop a new algorithm to compute the optimal power allocation algorithm and it has been compared with the existing scheme from the previous literature. An improved water filling algorithm is proposed and embedded in the power allocation algorithm to maximize EE and Spectral Efficiency (SE). The numerical analysis of the simulation results indicates an improvement of 40% in EE and 50% in SE at the downlink transmission, compared to the other existing schemes. Furthermore, the results revealed that SE does not influence the EE enhancement after using the proposed algorithm as the number of Massive MIMO antenna at the Base Station (BS) increases.

FDIPP: False Data Injection Prevention Protocol for Smart Grid Distribution Systems

Sensors ◽

10.3390/s20030679 ◽

2020 ◽

Vol 20 (3) ◽

pp. 679 ◽

Cited By ~ 1

Author(s):

Hosam Hittini ◽

Atef Abdrabou ◽

Liren Zhang

Keyword(s):

Communication Network ◽

Smart Grid ◽

Distribution System ◽

Network Architecture ◽

Distribution Systems ◽

Network Performance ◽

Vast Number ◽

False Data Injection ◽

Prevention Protocol ◽

In this paper, a false data injection prevention protocol (FDIPP) for smart grid distribution systems is proposed. The protocol is designed to work over a novel hierarchical communication network architecture that matches the distribution system hierarchy and its vast number of entities. The proposed protocol guarantees both system and data integrity via preventing packet injection, duplication, alteration, and rogue node access. Therefore, it prevents service disruption or damaging power network assets due to drawing the wrong conclusions about the current operating status of the power grid. Moreover, the impact of the FDIPP protocol on communication network performance is studied using intensive computer simulations. The simulation study shows that the proposed communication architecture is scalable and meets the packet delay requirements of inter-substation communication as mandated by IEC 61850-90-1 with a minimal packet loss while the security overhead of FDIPP is taken into account.

Massive MIMO-NOMA Networks with Imperfect SIC: Design and Fairness Enhancement

10.36227/techrxiv.11566725 ◽

2020 ◽

Author(s):

Arthur Sousa de Sena ◽

Pedro Nardelli

Keyword(s):

Outage Probability ◽

Power Allocation ◽

Interference Cancellation ◽

Massive Mimo ◽

Multiple Access ◽

Mimo Systems ◽

Optimal Solution ◽

Input Multiple Output ◽

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

Hardware Implementation and Performance Analysis of Improved Sphere Decoder in Spatially Correlated Massive MIMO Channels

10.36227/techrxiv.15042759.v2 ◽

2021 ◽

Author(s):

Dimitris Vordonis ◽

Vassilis Paliouras

Keyword(s):

Massive Mimo ◽

Large Scale ◽

Hardware Implementation ◽

Low Complexity ◽

Mimo Channels ◽

Sphere Decoder ◽

Trade Offs ◽

Simulation Results ◽

Detection for high-dimensional multiple-input multiple-output (MIMO) and massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), for both single-user (SU) and multi-user (MU) scenarios. The complexity of SD is mainly determined by the initial radius (IR) method and the number of visited nodes during detection. This paper employs an efficient IR and proposes a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, an introduced hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented. The trade-offs are achieved by either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless of the level of noise. The decoding gain of SD compared to the low-complexity linear detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware implementation aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.<br>

Hardware Implementation and Performance Analysis of Improved Sphere Decoder in spatially correlated Massive MIMO channels

10.36227/techrxiv.15042759 ◽

2021 ◽

Author(s):

Dimitris Vordonis ◽

Vassilis Paliouras

Keyword(s):

Massive Mimo ◽

Large Scale ◽

Hardware Implementation ◽

Low Complexity ◽

Mimo Channels ◽

Sphere Decoder ◽

Trade Offs ◽

Simulation Results ◽

<div>Detection for high-dimensional multiple-input multiple-output (MIMO) and Massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), not only for Single-User (SU) but also for Multi-User (MU) scenarios. The complexity of SD is mainly determined by the Initial Radius (IR) method and the number of visited nodes during detection. This paper proposes both an efficient IR and a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, a hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented, either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless the level of noise. The decoding gain of SD compared to the low-complexity Linear Detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.</div>

An Analytical Study of the Impact of Arbitrary Receive Antenna Correlation in TAS/MRC

International Journal of Antennas and Propagation ◽

10.1155/2014/798015 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Juan P. Peña-Martín ◽

Juan M. Romero-Jerez

Keyword(s):

Closed Form ◽

Channel Capacity ◽

Antenna Selection ◽

Mimo System ◽

Maximal Ratio Combining ◽

Closed Form Expression ◽

Transmit Antenna Selection ◽

Input Multiple Output ◽

Novel closed-form expressions are derived for the performance analysis of a multiple-input multiple-output (MIMO) system in Rayleigh fading using transmit antenna selection (TAS) at the transmitter and maximal ratio combining (MRC) at the receiver. Receive antennas are assumed to be arbitrarily correlated, as no restriction is imposed on the correlation matrix. General exact and asymptotic expressions to evaluate the bit error rate (BER) of different modulation schemes are presented for uncoded transmission, and a closed-form expression is presented for the channel capacity. It is demonstrated that channel capacity may improve due to correlation at the receive antennas if the transmit array size is large enough as a result of a higher signal variability and the antenna selection performed at the transmitter. Monte Carlo simulations have been carried out to validate the analysis, showing an excellent agreement with the theoretical results.

Hardware Implementation and Performance Analysis of Improved Sphere Decoder in spatially correlated Massive MIMO channels

10.36227/techrxiv.15042759.v1 ◽

2021 ◽

Author(s):

Dimitris Vordonis ◽

Vassilis Paliouras

Keyword(s):

Massive Mimo ◽

Large Scale ◽

Hardware Implementation ◽

Low Complexity ◽

Mimo Channels ◽

Sphere Decoder ◽

Trade Offs ◽

Simulation Results ◽

<div>Detection for high-dimensional multiple-input multiple-output (MIMO) and Massive MIMO (MMIMO) systems is an active field of research in wireless communications. While most works consider spatially uncorrelated channels, practical MMIMO channels are correlated. This paper investigates the impact of correlation on Sphere Decoder (SD), not only for Single-User (SU) but also for Multi-User (MU) scenarios. The complexity of SD is mainly determined by the Initial Radius (IR) method and the number of visited nodes during detection. This paper proposes both an efficient IR and a new metric constraint in the tree searching algorithm, that significantly decrease the number of visited nodes and render SD feasible for large-scale systems. In addition, a hardware implementation featured with a one-node-per-cycle architecture, minimizes the latency of the detection process. Trade-offs between bit error rate (BER) performance and computational complexity are presented, either modifying the backtracking mechanism or limiting the number of radius updates. Simulation results prove that the proposed optimizations are effective for both correlated and uncorrelated channels, regardless the level of noise. The decoding gain of SD compared to the low-complexity Linear Detectors (LD) is higher in the presence of correlation than in the uncorrelated case. However, as expected, spatial correlation adversely affects the performance and the complexity of SD. Simulation results reported here also confirm that correlation at the side equipped with more antennas is less detrimental. Hardware aspects are examined for both a Virtex-7 FPGA device and a 28-nm ASIC technology.</div>

PAPR and ISI Reduction in Cognitive Radio Network based 5G Network using Massive MIMO SC - FDMA ES.

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a1915.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 4697-4705

Keyword(s):

Cognitive Radio ◽

Massive Mimo ◽

Network Performance ◽

Average Power ◽

Network Simulator ◽

Fifth Generation ◽

5G Network ◽

Multiple Input ◽

Input Multiple Output

Extended use of spectrum increased the number of users; this was the major cause to introduce Cognitive Radio Networks (CRN) which is designed to access the available spectrum effectively. Advanced telecommunication technology that is fifth-generation (5G) is inbuilt in CRNs. Fusion Center (FC) in CRN plays an important role in decision making for allocating available spectrum. A novel FC rotation (FCR) method is applied over FC to mitigate the occurrence of interference. Massive-Multiple Input Multiple Output (MaMi) system is used to enhance network performances to accommodate the huge participation of users by means of having a large number of antennas. Existing research works in CRN based 5G network fails to decrease intersymbol interference (ISI) and Peak-to-Average Power Ratio (PAPR). A novel Massive MIMO SC – FDMA ES is proposed in this paper to mitigate high PAPR values to enhance network performance. Our proposed work in CRN is experimentally designed using Network Simulator 3 from which the performances are evaluated. The extensive simulation result shows betterment in terms of channel capacity, reduction of PAPR, bit error rate and spectral efficiency.