Search

The 3rd generation partnership project (3GPP) has been engaged in further advancing the evolved universal mobile telecommunications system (UMTS) terrestrial radio access network (E-UTRAN) and UTRAN based radio access network technologies. New radio (NR) is the 3rd generation partnership project (3GPP) endeavor for outlining and standardization of the 5th generation (5G) advanced radio access technology. 3GPP has released the first set of 5G NR standards, i.e., the non-standalone 5G radio specifications. As long-term evolution (LTE) technology is massively deployed and broadly accepted, the transition from LTE to 5G is very critical, and it is of maximal importance that the backward compatibility of 5G with LTE is considered. 3GPP has identified several architecture options for 5G. This article gives an overview of the NR architecture options, their deployment scenarios, and the key migration paths. The LTE-NR dual connectivity (DC) is presented. This DC scenario is unique in the sense that DC is being endowed for two different generations of 3GPP radio access technologies. We, further, present the integration of multipath transmission control protocol (MPTCP) with LTE-NR DC and DC-like aggregation, i.e., 3GPP-non-3GPP interworking to bring in the advantages of MPTCP in terms of link robustness, reliability and dynamic mapping between the traffic flows and the available paths. Finally, we discuss the future research and standardization directions of the next-generation networks., Comment: To appear in IEEE Wireless Communications Magazine

The next-generation wireless networks are evolving into very complex systems because of the very diversified service requirements, heterogeneity in applications, devices, and networks. The mobile network operators (MNOs) need to make the best use of the available resources, for example, power, spectrum, as well as infrastructures. Traditional networking approaches, i.e., reactive, centrally-managed, one-size-fits-all approaches and conventional data analysis tools that have limited capability (space and time) are not competent anymore and cannot satisfy and serve that future complex networks in terms of operation and optimization in a cost-effective way. A novel paradigm of proactive, self-aware, self- adaptive and predictive networking is much needed. The MNOs have access to large amounts of data, especially from the network and the subscribers. Systematic exploitation of the big data greatly helps in making the network smart, intelligent and facilitates cost-effective operation and optimization. In view of this, we consider a data-driven next-generation wireless network model, where the MNOs employ advanced data analytics for their networks. We discuss the data sources and strong drivers for the adoption of the data analytics and the role of machine learning, artificial intelligence in making the network intelligent in terms of being self-aware, self-adaptive, proactive and prescriptive. A set of network design and optimization schemes are presented with respect to data analytics. The paper is concluded with a discussion of challenges and benefits of adopting big data analytics and artificial intelligence in the next-generation communication system.

We study the coexistence of different multicarrier waveforms such as orthogonal frequency division multiplexing (OFDM), filter-bank multicarrier (FBMC) and universal-filtered multicarrier (UFMC) waveforms in licensed shared access (LSA) for next-generation communication systems. The fundamental changes required in the existing physical layer using OFDM towards a hybrid physical layer (either OFDM-FBMC or OFDM- UFMC) ensuring backward compatibility are discussed. We also perform mutual interference analysis for the coexisting asynchronous systems sharing the LSA frequency band. Be- cause of the non-orthogonality between their respective transmit signals, power is spilled from a system to the other causing interference. In consideration of analyzing this interaction, power spectral densities of the multicarrier waveforms are exploited. We quantify the amount of percentage power-loss experienced by the interfering systems for not fully exploiting their available power budgets. The simulation results reveal that the interfering system with FBMC suffers the least percentage power-power loss due to its very low side-lobes while conventional OFDM-based system suffers the most. The UFMC-based system exhibits intermediary performance with respect to achieved throughput and power-loss when compared with OFDM and FBMC-based systems., Comment: Proc. IEEE Wireless Personal Multimedia Communications (IEEE WPMC)., Hyderabad, India, Dec. 2015

In this paper, we study inter-operator spectrum sharing and intra-operator resource allocation in shared spectrum access communication systems and propose efficient dynamic solutions to address both inter-operator and intra-operator resource allocation optimization problems. For inter-operator spectrum sharing, we present two competent approaches, namely the subcarrier gain based sharing and fragmentation based sharing, which carry out fair and flexible allocation of the available shareable spectrum among the operators subject to certain well-defined sharing rules, traffic demands and channel propagation characteristics. Subcarrier gain based spectrum sharing scheme has been found to be more efficient in terms of achieved throughput. However, fragmentation based sharing is more attractive in terms of computational complexity. For intra-operator resource allocation, we consider resource allocation problem with users' dissimilar service requirements, where the operator supports users with delay-constraint and non-delay constraint service requirements, simultaneously. This optimization problem is a mixed integer nonlinear programming problem and nonconvex, which is computationally very expensive, and the complexity grows exponentially with the number of integer variables. We propose less-complex and efficient suboptimal solution based on formulating exact linearization, linear approximation and convexification techniques for the nonlinear and/or non-convex objective functions and constraints. Extensive simulation performance analysis has been carried out that validates the efficiency of the proposed solution.

In this paper, we conceive an advanced neutral host micro operator (NH-{\mu}O) network approach providing venues with services tailored to their specialized/specific requirements and/or local context related services that the mobile network operators (MNOs) are poorly-suited to providing it, as well as mobile broadband experience to the users from MNOs in a venue where only a single infrastructure is mandated under shared spectrum access framework. A radio access network slicing concept is conceived to support and optimize both the slice instance (SI) use cases independently and efficiently by running all network implementations in parallel, simultaneously on a common physical network infrastructure. We devise a common shared architecture for the NH-{\mu}O small cell base stations and dynamic spectrum assignment control unit, and their required functionalities supporting coexistence of different SIs as well as multiple MNOs in shared spectrum access communications. We devise both inter-SI and intra- SI dynamic spectrum allocation policies considering time-varying requirements of different SIs. The policies are capable of taking care of application level priority, -i.e., mixture of guaranteed quality of service and best-effort service users served by each SI while ensuring a healthy competition. Our proposed framework serves two-fold advantages, such as it gives the venue owner its own managed wireless networks tailored to its very specific requirements, and it also brings out cost savings and coverage extension for MNOs and efficiency of resources that arise from sharing wireless networks, and delivering the network capacity into high density venues.

We consider a cognitive radio 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 pre-specified 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 subband 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.

Small cells deployment is one of the most significant long-term strategic policies of the mobile network operators. In heterogeneous networks (HetNets), small cells serve as offloading spots in the radio access network to offload macro users (MUs) and their associated traffic from congested macrocells. In this paper, we perform analytical analysis and investigate how the radio propagation effects such as multipath and shadowing and small cell base station density affect MUs' offloading to small cell network (SCN). In particular, we exploit composite fading channels in our evaluation when an MU is offloaded to SCN with varying small and macro cell densities in the stochastic HetNets framework. We derive the expressions for outage probability (equivalently success probability) of the MU in macro network and SCN for two different cases, viz.: i) Nakagami-lognormal channel fading; ii) time-shared (combined) shadowed/unshadowed channel fading. We propose efficient approximations for the probability density functions of the channel fading (power) for the above-mentioned fading distributions that do not have closed-form expressions employing Gauss-Hermite integration and finite exponential series, respectively. Finally, the outage probability performance of MU with and without offloading options/services is analyzed for various settings of fading channels.

This letter studies the limited feedback cognitive radio system, where the primary users (PU) are interfered by the secondary transmitter (ST) due to the imperfect beamforming. We propose to allocate the feedback bits among multiple PUs to minimize the maximum interference caused by the ST, by exploiting the heterogeneous average channel gains. In addition, we study the problem of minimizing the total feedback bits under a predefined interference threshold at the PUs. The solutions with low complexity are proposed for the studied problems, and the performances of bit allocations are analyzed. Simulation results validate our analysis and demonstrate that the proposed solutions work very well in terms of minimizing the maximum interference caused by the ST and minimizing the total feedback bits under predefined interference threshold at the PUs for limited feedback CR system., Comment: Feedback Bits Allocation