The need for load balancing in 5th generation (5G) networks is evident from the fact that the traffic load can vary over time and space. When the traffic demand varies over time and space, it can put a strain on certain parts of the network, and can lead to congestion, delays, and other performance issues. If one RRU or cell becomes overloaded with traffic, it can result in reduced performance and degraded user experience for the users connected to that RRU or cell. The need for less complex, simple, and flexible load balancing solutions in 5G networks is driven by the need to support and manage high volume of data under dynamic network conditions of complex 5G mobile networks. In this paper, we propose a simple-to-implement, flexible and fast-convergent algorithm for load balancing in scalable user-centric massive MIMO system. The evaluation results show that the proposed solution has very good load balancing capability and can converge to the desired solution very fast, for example, 3-5 iterations. The proposed load balancing framework is adaptable to many different types of networks such as conventional systems, coordinated joint transmission systems as well as clustered (overlapping, non-overlapping cluster of cells) cellular systems.

Data-driven approaches, e.g., deep learning (DL),have been widely studied in terrestrial wireless communications fields, proving the benefits and potentials of such techniques. In comparison, DL for satellite networks is studied to a limited extent in the literature. In this paper, we develop a DL assisted approach to facilitate efficient beam hopping (BH) in multibeam satellite systems. BH is adopted to provide a high level of flexibility to manage irregular and time variant traffic requests in the satellite coverage area. Conventional iterative optimization approaches and typical data-driven techniques may have their respective limitations in achieving timely and satisfactory performance. We herein explore a combined learning-and-optimization approach to provide a fast, feasible, and near-optimal solution for BH scheduling. Numerical study shows that in the proposed solution, the learning component is able to largely accelerate the procedure of BH pattern selection and allocation, while the optimization component can guarantee the solution's feasibility and improve the overall performance.

This paper designs dynamic onboard signal processing schemes in a multiple gateway multi-beam satellite system where full frequency reuse pattern is considered among the beams and feeds. In particular, we deploy on-board Joint Precoding, Feed selection and Signal switching mechanism (JPFS) so that the following advantages are realized, I) No need of Channel State Information (CSI) exchange among the gateways and satellite, since the performance of precoding is highly sensitive to the quality of CSI, II) In case one gateway fails, rerouting signals through other gateways can be applied without any extra signal processing, III) Properly selecting on-board feed/s to serve each user which generates maximum gain toward corresponding user, IV) Flexibly switching the signals received from the gateways to requested users where each user can dynamically request traffic from any gateway, and V) Multiple users with multiple traffic streams can be dynamically served at each beam. However, deploying such JPFS architecture imposes high complexity to the satellite payload. To tackle this issue, this study aims at deploying JPFS that can provide affordable complexity at the payload. In addition, while increasing the data demand imposes extensive bandwidth resources requirement in the feeder link, the proposed JPFS design works efficiently with available feeder link resources even if the data demand increases. The proposed design is evaluated with a close-to-real beam pattern and the latest broadband communication standard for satellite communications.

Carrier Aggregation (CA) is an integral part of current terrestrial networks. Its ability to enhance the peak data rate, to efficiently utilize the limited available spectrum resources and to satisfy the demand for data-hungry applications has drawn large attention from different wireless network communities. Given the benefits of CA in the terrestrial wireless environment, it is of great interest to analyze and evaluate the potential impact of CA in the satellite domain. In this paper, we study CA in multibeam high throughput satellite systems. We consider both inter-transponder and intra-transponder CA at the satellite payload level of the communication stack, and we address the problem of carrier-user assignment assuming that multiple users can be multiplexed in each carrier. The transmission parameters of different carriers are generated considering the transmission characteristics of carriers in different transponders. In particular, we propose a flexible carrier allocation approach for a CA-enabled multibeam satellite system targeting a proportionally fair user demand satisfaction. Simulation results and analysis shed some light on this rather unexplored scenario and demonstrate the feasibility of the CA in satellite communication systems.

Beam-Hopping (BH) and precoding are two trending technologies for the satellite community. While BH enables flexibility to adapt the offered capacity to the heterogeneous demand, precoding aims at boosting the spectral efficiency. In this paper, we consider a high throughput satellite (HTS) system that employs BH in conjunction with precoding. In particular, we propose the concept of Cluster-Hopping (CH) that seamlessly combines the BH and precoding paradigms and utilize their individual competencies. The cluster is defined as a set of adjacent beams that are simultaneously illuminated. In addition, we propose an efficient time-space illumination pattern design, where we determine the set of clusters that can be illuminated simultaneously at each hopping event along with the illumination duration. We model the CH time-space illumination pattern design as an integer programming problem which can be efficiently solved. Supporting results based on numerical simulations are provided which validate the effectiveness of the proposed CH concept and time-space illumination pattern design.

The IEEE 802.11ad technology, which allows wireless devices to communicate in the unlicensed 60 GHz ISM band, promisingly provides multi-Gbps data rates for bandwidth-intensive applications. After years of research and development, we are now observing an increasing number of commodity IEEE 802.11ad radios that motivate researchers to exploit the IEEE 801.11ad capability for applications. This work first conducts an empirical study on the IEEE 802.11ad performance. In particular, we characterize the performance of IEEE 802.11ad links considering the variation of network parameters and interference. Secondly, we investigate the possibility of introducing IEEE 802.11ad to an evolving Wi-Fi network. The evaluation results show that our off-the-shelf IEEE 802.11ad hardware can achieve the Gbps level throughput of the transmission control protocol (TCP) and user datagram protocol (UDP). However, the evolvement is not trivial since the hardware can not well maintain the 60 GHz link. The main reason is lacking the fast switchover function between an IEEE 802.11ad and a legacy Wi-Fi link. We then seek the potential of multipath TCP (MPTCP) for the expected switchover. The default MPTCP, which enables data transmissions on both the IEEE 802.11ad and Wi-Fi links, is harmful to the IEEE 802.11ad throughput. Meanwhile, the backup mode of MPTCP, in which the Wi-Fi link acts as a backup for IEEE 802.11ad one, can maintain the comparable performance. Therefore, we propose to adopt MPTCP with the backup mode in the evolving Wi-Fi networks. The efficiency of MPTCP-based switchover is confirmed by conducting real experiments.

The 3rd generation partnership project (3GPP) has recently specified the non-standalone 5G New Radio (NR), in which the dual connectivity (DC) feature plays an essential role. A User Equipment (UE) with DC is able to concurrently connect to an evolved NodeB (eNB) (e.g., using LTE in a macro cell) and a next generation NodeB (gNB) (e.g., using 5G NR in a small cell) aiming to satisfy the 5G's required Key Performance Indicators (KPIs). In this work, we focus on the issue of concurrent transmissions on the 5G small cell, which potentially exploit the benefits of DC. With DC, an application is able to spread its traffic over different two paths (via eNB and gNB) between the UE and the LTE core network. The traffic over diverse paths may experience different delay since the conditions are generally different (e.g., due to wireless channel, background traffic). Therefore, one of the most important problems in efficient operation with DC is minimizing the end-to-end delay considering all the connections. To address that problem, we adopt the deterministic network calculus to first characterize the delay experienced by each connection; then to model the overall end-to- end delay in the 5G small cell. We then formulate an optimization problem that attempts to find the optimal traffic splitting over the connections while minimizing the delay. We derive the solution for the problem, as well as, present the numerical results.

The shared resource access wireless communication system is regarded as a paradigm that allows the mobile network operators (MNOs) to have extended coverage and allows them to satisfy their subscribers' high capacity demands while keeping the capital and operational expenditure in check. On the other hand, dual connectivity (DC), a small cell enhancement feature, allows the subscribers to have two simultaneous connections increasing throughput and enhancing mobility robustness. For the DC mechanism, the user needs to be under the coverage of multiple BSs concurrently. Because of random nature of the wireless links and distribution of BSs in a network, the practicability/operability of DC for a typical user under such random operating conditions (both topological and wireless link randomness) needs to be properly evaluated. In this paper, we perform stochastic analysis of DC in shared resource access high capacity wireless networks. We consider a fading-averaged signal propagation loss process, where the selection of the serving BS is perturbed shadowing, not by fading. The DC coverage probability is analyzed in terms of tractable, integral expressions. We have observed that the DC coverage probability is greatly affected by the density of the small cell BSs and the variance of the log-normal shadowing.

To make WiGig/IEEE 802.11ad backward compatible with the legacy Wi-Fi, a multi-band device that is capable of WiGig and Wi-Fi is necessarily equipped a function of fast switchover between the WiGig and Wi-Fi link. It is expected that the switching action is done as quickly as possible in order to minimize negative effects on an ongoing application. The IEEE 802.11ad standard defines the switching operation within the scope of fast session transfer (FST) protocol. To properly run FST, the device needs extra layer-2 entities that simultaneously manage the PHY/MAC states of multiple radios. Although introducing WiGig radios is a trivial task, installing those entities on an existing legacy Wi-Fi network is unfortunately a challenging one. This work presents an experimental feasibility study of achieving the backward compatibility without FST. We initially analyze the feasible capability of multipath transmission control protocol (MPTCP). We then setup a real- world testbed and evaluate different operational modes of MPTCP, aiming to find the most suitable one. Our experimental results show that the fast switchover between a multi-Gigabit WiGig and a legacy Wi-Fi link is achievable with the MPTCP's backup mode.

We investigate an advanced two-phase shared spectrum access communication scheme as an efficient approach to enhance the spectral utilization of a network. In the first phase, we devise a spectrum-sharing policy based on demands, fairness, and so on, which utilizes a priority scheme in fulfilling operators' demands, and envision a secure operator-specific information sharing policy where no critical information is exchanged between the operators. In the second phase, a macro cell network (MCN) benefits through offloading services offered by small cell network (SCN). This allows the MCN to satisfy its users' capacity demands, improve its quality of services and coverage under Nakagami fading channel. As a repayment, the SCN is rewarded with licenses to share and operate on the spectrum originally owned by the MCN. We devise a density division-based shared spectrum access model, where the density of the licensee's SCN deployment is exploited as network resources. A fair division of the densities of the licensee operator's small cell base stations into fractions of licensed small cell base stations serving its own users and offloading small cells is presented. Unlike most of the previous research works that considered Poisson point process (PPP) to model the distribution of the network entities even when PPP modeling is not accurate for the networks, where the number of MCN/SCN base stations is definite and the number of MCN/SCN base stations in disjoint areas is not independent, we employ a more realistic network model known as binomial point process to perform an analytical analysis of the cumulative interference and performance of the system. Furthermore, we analyze the rate coverage and outage performances considering a wide range of values for path-loss exponent and fading severity parameter of Nakagami fading.

In this paper, we conceive an advanced small cells wireless network deployment framework within a managed space under shared spectrum access paradigm. We also conceive a complementary business model, referred to as neutral host micro operator (NH-μO), that leverages a single shared wireless infrastructure to mutually benefit μO (a third party service provider), the owner of the space/facility, and mobile network operators (MNOs). The model is composed of a μO slice, which delivers a venue with customized wireless services tailored to the its local service requirements, and an MNO slice, which facilitates improved wireless coverage to visitors/end-users with subscriptions to several different MNOs. The NH-μO is not biased to favor any specific client, which can be enforced through a concrete commercial agreement. A radio access network slicing concept is exploited to support and optimize both the slice instances (SIs) efficiently in a shared manner on a single physical network infrastructure. In addition, we devise an efficient architecture for the NH-μO small cell base station and dynamic spectrum assignment control unit, and their required functionalities supporting sustainable coexistence of different SIs in shared spectrum. We also devise both interSI and intra-SI dynamic spectrum allocation policies considering time-varying requirements of different SIs. These policies take care of application level priority by providing a proper mixture of users with guaranteed quality of service and best-effort users, while ensuring a healthy SI competition. The advantages of the proposed framework are twofold. It enables the venue owner to manage its wireless networks and consider its very specific requirements while capitalizing from the MNO slice. This, in turn, reduces the need for deployment of new infrastructure while providing improved wireless coverage and savings to MNOs. Finally, our proposed framework leverages efficient utilization of spectrum, physical infrastructure, and computational resources. The simulation results exhibit various important features of the proposed shared spectrum access policies.

We consider a cognitive radio (CR) network consisting of a primary cellular system and a secondary cognitive machine-to-machine (M2M) system, and study the throughput enhancement problem of the latter system employing universal-filtered orthogonal frequency division multiplexing (UF-OFDM) modulation. The downlink transmission capacity of the cognitive M2M system is thereby maximized, while keeping the interference introduced to the primary users (PUs) below the prespecified threshold, under total transmit power budget of the secondary base station (SBS). The performance of UF-OFDM-based CR system is compared to the performances of OFDM-based and filter bank multicarrier (FBMC)-based CR systems. We also propose a near-optimal resource allocation method separating the sub-band and power allocation. The solution is less complex compared to optimization of the original combinatorial problem. We present numerical results that show that for given interference thresholds of the PUs and maximum transmit power limit of the SBS, the UF-OFDM-based CR system exhibits intermediary performance in terms of achievable capacity compared to OFDM- and FBMC-based CR systems. Interestingly, for a certain degree of robustness of the PUs, the UF-OFDM performs equally well as FBMC. Furthermore, the percentage rate-gain of UF-OFDM-based CR system increases by a large amount when UF-OFDM modulation with lower sidelobes ripple is employed. Numerical results also show that the proposed throughput enhancing method despite having lower computational complexity compared to the optimal solution achieves near-optimal performance.

We optimize the throughput of a single cell multiuser orthogonal frequency division multiplexing system with proportional data rate fairness among the users. The concept is to support mobile users with different levels of service. The optimization problem is a mixed integer nonlinear programming problem, which is computationally very expensive. We propose a novel and efficient near-optimal solution adopting a two-phase optimization approach that separates the subcarrier and power allocation. In the first phase, we relax the strict proportional data rate requirements and employ an iterative subcarrier allocation approach that coarsely satisfies desired data rate proportionality constraints. In the second phase, we reallocate the power among the users in an iterative way to further enhance the adherence to the desired proportions by exploiting the normalized proportionality deviation measure. The simulation results show that the proposed solution exhibits very strong adherence to the desired proportional data rate fairness while achieving higher system throughput compared to the other existing solutions.

This paper considers distributed linear beamforming in downlink multicell multiuser orthogonal frequency-division multiple access networks. A fast convergent solution maximizing the weighted sum-rate with per base station (BS) transmiting power constraint is formulated. We approximate the noncon-vex weighted sum-rate maximization (WSRM) problem with a semidefinite relaxed solvable convex form by means of a series of approximation based on interference alignment (IA) analysis. The WSRM optimization is a two-stage optimization process. In the first stage, the IA conditions are satisfied. In the second stage, the convex approximation of the non-convex WSRM is obtained based on the consequences of IA, and high signal-to-interference-plus-noise ratio assumption. Compared to the conventional iterative distributed algorithms where the BSs exchange additional information at each iteration, the BSs of our proposed solution optimize their beamformers locally without reporting additional information during the iterative procedure.

In this paper, we analyze the performance of a downlink beamforming system with partitioned vector quantization (P-VQ). A multiuser multiple-input single-output (MU-MISO) downlink beamforming system with accurate channel state information (CSI) at user terminals is considered. The optimization of feedback bits allocation to different partitions and channel direction indicator (CDI), channel quality indicator (CQI) corresponding to each partition has been performed exploiting quantization mean square error (MSE). The impacts of equal and unequal partitioning, and the number of partitions on codebook memory and overall system capacity have also been investigated and depicted through simulation results. We have found that with optimized CQI and CDI bits allocations, the amount of bits allotted to equal and unequal partitions are proportional to the size ratios of the respective partitioned sub-vectors. It has also been observed that for small-sized partitions, the optimal ratio of CDI to CQI is much smaller than that of large-sized partitions.

In this study, an adaptive and variable-rate feedback reduction technique for partitioned vector quantization (P-VQ) in MU-MISO downlink precoding is proposed. Independent feed-back reduction is performed for both channel quality indicator (CQI) and channel direction indicator (CDI) over slowly-varying Rayleigh channel. The users adaptively reduce the feedback over-head for quantized channel state information (CSI) depending on the rate and direction of change in the correlated CQIs and CDIs. Simulation results show that the proposed scheme greatly lessens the communication overhead with very small performance loss and enhances the quantization efficiency.

This paper considers coordinated linear precoding in downlink multicell multiuser orthogonal frequency-division multiple access (OFDMA) network. A less-complex, fast and provably convergent algorithm that maximizes the weighted sum-rate with per base station (BS) transmit power constraint is formulated. We approximate the nonconvex weighted sum-rate maximization (WSRM) problem with a solvable convex form by means of sequential parametric convex approximation (SPCA) approach. The second order cone program (SOCP) formulations of the objective function and constraints of the optimization problem are derived through proper change of variables, first order linear approximation and hyperbolic constraints transformation, etc. The algorithm converges to the suboptimal solution taking fewer number of iterations in comparison to other known iterative WSRM algorithms. Finally, numerical results are presented to justify the effectiveness and superiority of the proposed algorithm.

A practical and efficient vector quantization called partitioned vector quantization (P-VQ) based non-linear precoder for MIMO downlink broadcasting channels has been analyzed in this paper. P- VQ has been found to be an efficient way of reducing the memory requirements and search complexity in conventional VQ systems, especially for large MIMO. Simulation results reveal that P-VQ technique can enhance the overall quantization performance in terms of achieved capacity, bit error rate (BER) at a cost of reasonable additional complexity under certain feedback budgets. Tomlinson-Harashima precoding (THP), a power and complexity efficient precoding technique along with data dependent vector perturbation (VP) has been employed to meet the power constraint requirements of our system. Least-square (LS) channel estimation is performed at the user terminals to acquire their channel state information (CSI).