On Optimal Beamforming Design for Downlink MISO NOMA Systems

This work focuses on the beamforming design for downlink multiple-input single-output (MISO) nonorthogonal multiple access (NOMA) systems. The beamforming vectors are designed by solving a total transmission power minimization (TPM) problem with quality-of-service (QoS) constraints. In order to solve the proposed nonconvex optimization problem, we provide an efficient method using semidefinite relaxation. Moreover, for the first time, we characterize the optimal beam- forming in a closed form with quasi-degradation condition, which is proven to achieve the same performance as dirty- paper coding (DPC). For the special case with two users, we further show that the original nonconvex TPM problem can be equivalently transferred into a convex optimization problem and easily solved via standard optimization tools. In addition, the optimal beamforming is also characterized in a closed form and we show that it achieves the same performance as the DPC. In the simulation, we show that our proposed optimal NOMA beamforming outperforms OMA schemes and can even achieve the same performance as DPC. Our solutions dramatically simplifies the problem of beamforming design in the downlink MISO NOMA systems and improve the system performance

Performance evaluation of MISO-SDMA in heterogenous networks with practical cell association

In this paper adopting stochastic geometry we investigate the system performance in heterogenous networks including multiple tiers of BSs with multiple-input single output spatial division multiple access (MISO-SDMA) technique. In the related literature on heterogenous systems, ideal cell association (CA) rules are often considered for simplicity, where each user equipment (UE) examines a very large number of pilots across the tiers before choosing its associated base station (BS). Here we consider practical cases where UEs are restricted to examine KH≥1 pilots across all tiers before choosing their associated BS. We then obtain closed-form expressions for the system performance measured by the coverage probability and UE's data rate. Our analytical results provide quantitative insights on the impact of different factors on the system performance including the BS's spatial density, their transmission powers, number of transmit antennas, SIR thresholds, number of UEs served by each BS, and KH. Interestingly, we observe that increasing KH always improves the coverage probability however, it only improves data rate up to a certain point. The data rate is then reduced by further increasing of KH. Given KH pilots in practical cases, the issue is how to allocate the pilots among different tiers. We address this issue by developing an algorithm and show that by careful allocation of available pilots, the network performance is significantly improved even in cases with small KH. Our results also indicate a fundamental tradeoff, as sharing strategies providing the best coverage performance yield very poor capacity and vice versa. Such trade-off provides a new degree of freedom in heterogeneous networks design

Dependable Information Exchange for the Next Generation Mobile Cyber-Physical Systems

Mobile cyber-physical systems (M-CPSs) are envisaged as an integral part of our digital future. Dependability of M-CPSs is subject to timely, reliable, and secure information exchange among M-CPS entities. Information exchange provisioning in such systems is conventionally built with sole reliance on wireless connectivity. The conventional approaches, however, fail to efficiently exploit dynamism and heterogeneity, and to incorporate computing/cooperation as alternative system-wide tools for information exchange. To address these issues, we approach M-CPSs dependability from the information exchange perspective and define dependable-exchange-of-information (DeX) indicating collective M-CPS capability of information exchange provisioning. We then propose a cloud-based architecture for DeX provisioning as a service to facilitate versatile development of dependable M-CPSs

Clustered Jamming in Aerial HetNets with Decoupled Access

The tremendous increase in wireless connectivity demand will result in the degradation of the service quality and the scarcity of network capacity and coverage in the beyond 5 th generation era. To ensure reliable connectivity and enhance the network’s performance, the evolution of heterogeneous networks (HetNets) must incorporate aerial platforms in addition to traditional terrestrial base stations. The performance of Aerial-HetNets (A-HetNets) is largely dependent on the users’ association. The conventional user-association scheme based on downlink received power provides sub-optimal performance for the edge users. For this reason, decoupled user-association along with the reverse frequency allocation (RFA) strategy has been employed in A-HetNets. The performance of A-HetNets is also affected if wide-band jammers (WBJs) are present in the vicinity and impose jamming interference. In this paper, a two-tier A-HetNet with RFA and decoupled access is analyzed in the presence of jamming interference. The obtained results show that for a signal-to-interference ratio threshold of −20 dBm, the percentage decrease in the coverage probability of the decoupled access due to WBJ activity is up to 7.4%, 13.5%, and 19.7%, for the average number of WBJs equal to 2, 4, and 6, respectively. The performance of the decoupled access in A-HetNets is further decreased by increasing the transmit power of the WBJs while it is increased by increasing the radius of the WBJ’s cluster

Radio resource allocation in collaborative cognitive radio networks based on primary sensing profile

In this paper, we present a novel power allocation scheme for multicarrier cognitive radio networks. The proposed scheme performs subchannel power allocation by incorporating primary users activity in adjacent cells. Therefore, we first define the aggregated subchannel activity index (ASAI) as an average indicator which characterizes the collective networkwide primary users' communication activity level. The optimal transmit power allocation is then obtained with the objective of maximizing a total utility function at the secondary base station (SBS), subject to the maximum SBS transmit power, and collision probability constraint at the primary receivers. Utilizing ASAI, we further obtain an energy efficient power allocation for the secondary system. Optimal energy efficiency (EE) and spectral efficiency (SE) are contradicting objectives, and thus, there is a tradeoff between these two performance metrics. We also propose a design approach to handle this tradeoff as a function of the ASAI, which provides quantitative insights into efficient system design. In addition to a lower signaling overhead, the simulation results confirm that the proposed scheme achieves a significantly higher achievable rate. Simulation results further indicate that using ASAI enables obtaining an optimal operating point based on the tradeoff between EE and SE. The optimal operating point can be further adjusted by relaxing/restricting the sensing parameters depending on the system requirements

Inter-cell collaborative spectrum monitoring for cognitive cellular networks in fading environment

We propose a novel inter-cell power allocation for multi-carrier cognitive cellular networks. The proposed scheme incorporates the network-wide primary service communication activity into sub-channel power allocation. To model the primary service activity we define sub-channel activity index (SAI). SAI is then evaluated through a simple yet efficient collaborative spectrum monitoring scheme with very low signaling overhead. Corresponding to a secondary user transmission over a sub-channel, a utility function is defined which is a decreasing function of SAI, and an increasing function of the sub-channel achievable rate. Optimal power allocation is then formulated to maximize the total secondary base station (SBS) utility, subject to SBS transmit power, and primary system collision probability constraints. The sub-optimal solutions to the non-convex optimization are then obtained utilizing dual decomposition method. Comparing with a cognitive cellular network with no signalling among the SBSs, where SBS adopts equal sub-channel power allocation, simulation results indicate a significant gain on the achievable rate. We further compare the rate performance with an ideal system in which perfect interference channel state, and spectrum sensing information are available at the SBS and a combination of underlay and overlay access techniques are adopted. Comparing to the ideal system, the proposed method requires significantly lower signaling overhead while its rate performance closely follows the ideal access

Game-Theoretic Analysis of an Exclusively Transaction-Fee Reward Blockchain System

Miners in a blockchain system are typically rewarded in two ways - through a fixed block reward, and by the transaction fees that are voluntarily offered by its users. As the available space inside a block is limited, users must compete against each other by submitting higher fees to obtain this limited resource. In this paper, we model blockchain transaction inclusion as a time-sensitive dynamic game, where users base their fees depending on both what their competitors in the network are offering, and by their own urgency of having their transactions approved. We then investigate the effect that mempool congestion (the aggregate size of transactions waiting to be confirmed) and different block sizes have on the fees users would be willing to pay. Our analysis concludes that miners have no rational reason to artificially limit the block size, which is in direct contrast with previous research findings. Instead, we find that increasing the block size in relation to a growing mempool both lowers the individual fees that users have to pay, and increases the total in fees collected, which raises not only the utility of the miners, but also of the regular users of the blockchain system

Optimum NN Algorithms Parameters on the UJIIndoorLoc for Wi-Fi Fingerprinting Indoor Positioning Systems

Wi-Fi fingerprinting techniques are commonly used in Indoor Positioning Systems (IPS) as Wi-Fi signal is available in most indoor settings. In such systems, the position is estimated based on a matching algorithm between the enquiry points and the recorded fingerprint data. In this paper, our objective is to investigate and provide quantitative insight into the performance of various Nearest Neighbour (NN) algorithms. The NN algorithms such as KNN are also often employed in IPS. We extensively study the performance of several NN algorithms on a publicly available dataset, UJIIndoorLoc. Furthermore, we propose an improved version of the Weighted KNN algorithm. The proposed model outperforms the existing works on the UJIIndoorLoc dataset and achieves better results for the success rate and the mean positioning error

On Short Term Fairness and Throughput of User Clustering for Downlink Non-Orthogonal Multiple Access System

Non-orthogonal multiple access (NOMA) with power-domain user multiplexing has been considered as one of the potential candidates of the fifth-Generation (5G) systems. In this paper, a two-stage user selection algorithm is proposed based on proportional fairness for downlink NOMA with zero-forcing beamforming (PF-NOMA-ZFBF) in order to improve the throughput-fairness trade-off for NOMA system. We focus on short term fairness, where short term refers to the minimum time window in which a specified fairness is guaranteed and evaluated using Jain's index. A transmit power allocation then applied to enhance the throughput of NOMA system. Simulation results show that the proposed PF-NOMA-ZFBF significantly improves user fairness index with at least 38.96% over conventional NOMA-ZFBF while maintaining the total system sum-rate (near maximum)