Agile coverage and control for hyper-cellular networks

In this paper, content caching is considered in a software-defined hyper-cellular network (SD-HCN) with capacity-limited backhaul connections. To achieve efficient content caching and delivery at the network edge, an analytical framework of minimizing the average content provisioning cost of SD-HCN, e.g., latency, bandwidth, and so on, is first formulated subjected to a sum storage capacity constraint. An optimal solution to this problem requires a joint design of storage allocation and content placement at the centralized control base station (CBS) and distributed traffic base stations (TBSs), which is NP-hard in general. To provide insights, a baseline non-cooperative caching strategy is first introduced between the CBS and TBSs. Then, an efficient cooperative edge caching strategy is proposed by leveraging the vertical cooperation between the CBS and TBSs, and horizontal cooperation between the TBSs. Analytical results demonstrate that the content provisioning cost of SD-HCN is significantly reduced by using the analytically obtained optimal storage allocation between the CBS and TBSs, and the proposed cooperative edge caching strategy always outperforms the non-cooperative caching strategy. Furthermore, by switching between the vertical and horizontal cooperative caching modes, extra performance gains can be achieved by the proposed cooperative edge caching strategy.

Channel correlation is usually tracked for adaptive channel estimation, prediction and network optimization. Time correlation is determined by the relative movement of the transmitter and the receiver, while frequency and spatial correlation depend on the environment layout that can be collected and stored for future use. In this paper, we introduce the concept of channel correlation map stored at the base station (BS), which adds both frequency and space direction channel correlation parameters as overlay information to a geographic map. We propose a measurement method of channel correlation maps by processing uplink transmission data and show the influence of available bandwidth on the measurement accuracy. Two application cases with the correlation map are shown through numerical simulation. One is adaptive MIMO-OFDM channel estimation without online tracking correlation parameters, the other is channel prediction for transmit scheduling and beamforming design to reduce the performance degradation due to outdated channel state information (CSI) caused by the feedback delay.

SummaryIn this paper, we propose efficient parity allocation schemes when rateless codes are used in satellite communication systems in conjunction with an adaptive coding and modulation (ACM) scheme. ACM schemes are widely used in modern satellite communication systems to maintain the required error rate performance under channel impairment (such as rain fading observed in high‐frequency bands). The performance enhancement of ACM can be achieved by providing a good channel prediction and mode allocation method. In the case of a channel prediction or allocation error, rateless codes can be used as an effective means of retransmission to compensate for the performance degradation. After investigating the performance behaviour of rateless codes combined with ACM, we derive a mathematical formula to find the optimum parity length of the rateless code to be retransmitted to satisfy the target performance requirements. Simulation results described in this paper show that the proposed method can be used to enhance the error performance as well as spectral efficiency.

Fifth-generation (5G) network demands of higher data rate, massive user connectivity and large spectrum can be achieve using Sparse Code Multiple Access (SCMA) scheme. The integration of cognitive feature spectrum sensing with SCMA can enhance the spectrum efficiency in a heavily dense 5G wireless network. In this paper, we have investigated the primary user detection performance using SCMA in Centralized Cooperative Spectrum Sensing (CCSS). The developed model can support massive user connectivity, lower latency and higher spectrum utilization for future 5G networks. The simulation study is performed for AWGN and Rayleigh fading channel. Log-MPA iterative receiver based Log-Likelihood Ratio (LLR) soft test statistic is passed to Fusion Center (FC). The Wald-hypothesis test is used at FC to finalize the PU decision.

Deep learning (DL) enabled semantic communications have been developed to improve the offline communication efficiently and intelligently by exploring the semantic information, while constraining their applications in real-time online scenarios. In this work, we propose SemAudio, the first DL-based streaming semantic communication system for real-time audio processing. To better extract the semantic features of the audio signal, SemAudio employs the Transformer-XL due to its potential to capture long-distance dependency. Moreover, the system works based on a chunk-based mask attention strategy to enable real-time streaming. By incorporating the novel Transformer-XL and chunk-wise approach, SemAudio can effectively learn and extract semantic features from real-time audio data. Furthermore, to alleviate the channel distortion and attenuation, the semantic and channel encoder/decoder are jointly designed by minimizing the mean error in both time and frequency domains rather than the merely time domain. The extensive experimental results suggest that our proposed SemAudio outperforms the traditional communications. Besides, the proposed SemAudio compromises the quality and latency to meet real-time requirements, which obtains satisfactory performance with significantly higher accuracy and lower latency under multiple channel conditions for real-time audio communication.

Device-to-device (D2D) communication has been a potential solution to improve spectral efficiency of cellular systems due to frequency resource sharing. This paper considers D2D communications underlaying an uplink cellular system enabling sparse code multiple access (SCMA) technology, where the base station (BS) can decode the signals of cellular users without mutual interference. The demands for high data rate as well as low latency in massive connectivity is the main challenging requirement in D2D communications, along with ensuring the quality of service (QoS) for the on-running cellular user equipment (CUEs). To tackle the problem, the BS is designed to first assigns the codewords in a codebook to CUEs based on the lower bound of the achievable CUE rates, so that the sum rate (SR) of CUEs is maximized. With the usage of mutual-interference suppression in the SCMA-enabled system, the BS then attempts to maximize the SR of D2Ds in a transmission block through a joint power and resource allocation subject to the QoS requirements for both CUEs and D2Ds. This task is formulated as a mixed-integer non-convex programming. We propose a low-complexity two-phase algorithm of joint heuristic and inner approximation method to efficiently solve the problem. The numerical results verify that the codebook assignment problem based on the lower bound of SR is easily solved, and the proposed algorithm to maximize the SR of D2Ds outperforms existing methods.

With the development of smart grids, existing power private networks fell short of the demanding requirements of industrial applications, especially with respect to bandwidth, end to end latency, and reliability. Combining with vertical industry is a major development direction of 5G mobile communication technology, while its communication capacity of large bandwidth, low latency, high reliability as well as massive connection is matched with the service requirements of smart grid service. How to apply 5G to smart grid is widely concerned. This article is a survey of the related technologies about convergence application of 5G and smart grid. It first reviews the update of the 5G physical layer technologies, which support for realizing the communication requirements of the 5G application scenarios. Then it introduces the key technologies such as 5G mobile edge computing, computational caching and network slicing, which is the basis for 5G to support vertical multi-service networks and meet different service requirements. Finally, it presents several network slicing logic architectures of the access network, transmission network and core network which are matched with power service.

The 5G wireless networks are potentially revolutionizing future technologies. The 5G technologies are expected to foresee demands of diverse vertical applications with diverse requirements including high traffic volume, massive connectivity, high quality of service, and low latency. To fulfill such requirements in 5G and beyond, new emerging technologies such as SDN, NFV, MEC, and CC are being deployed. However, these technologies raise several issues regarding transparency, decentralization, and reliability. Furthermore, 5G networks are expected to connect many heterogeneous devices and machines that will raise several security concerns regarding users’ confidentiality, data privacy, and trustworthiness. To work seamlessly and securely in such scenarios, future 5G networks need to deploy smarter and more efficient security functions. Motivated by the aforementioned issues, blockchain was proposed by researchers to overcome 5G issues because of its capacities to ensure transparency, data reliability, trustworthiness, immutability in a distributed environment. Indeed, blockchain has gained momentum as a novel technology that gives rise to a plethora of new decentralized technologies. In this chapter, we discuss the integration of the blockchain with 5G networks and beyond. We then present how blockchain applications in 5G networks and beyond could facilitate enabling various services at the edge and the core.

The annual increase in the number of accidents across the world have demonstrated the urgent need of supporting V2X communications in order to minimize killed and injured risks on roads. V2X is considered as one of the key applications of 5G system where it uses the non-orthogonal multiple access (NOMA) technique as its access technique for its high transmission rates, high throughput, massive connectivity and low latency. In this work we provide a secure resource allocation algorithm to assure allocating vehicles according to several needed criteria to improve the allocation mechanism and to satisfy users need in the network.

To efficiently support the transport of sub-1-Gbps services, an optical service unit (OSU)-based metro-optimized optical transport network (M-OTN) technology framework is proposed and described. The proposed M-OTN/OSU technologies have been implemented by major OTN equipment vendors and verified in a network operator’s lab for the first time to our knowledge. Moreover, a multivendor interoperability test has been conducted in a real-time field trial. The experimental results show that M-OTN/OSU has clear advantages over existing SDH VC/packet-enhanced OTN technologies in several key aspects, e.g., low latency, massive connections, and agile hitless bandwidth adjustment. M-OTN/OSU will be valuable for network operators providing high-quality leased line services and video/VR services in modern OTNs with unprecedented scalability and performance.

Cognitive radio-based non-orthogonal multiple access (CR-NOMA) is considered to be one of the promising multiple accessing technique candidates for 5G and beyond networks. These networks are facing a lot of challenges to achieve high spectral efficiency, low latency, and massive connectivity. Interference management and efficient power allocation are highly interesting among the researchers to investigate in CR-NOMA networks. This paper studies the power allocation of underlay CR-NOMA network using game theory approach by conducting the pricing technique to achieve efficient power allocation and minimum interference. In particular, the game is formulated, and its solution is achieved by exploring the suboptimal solution represented by the Pareto-efficiency of the Nash equilibrium point. The simulation results show the superiority of the proposed scheme in achieving higher spectral efficiency, fairness index, and sum utilities of secondary users compared to existing schemes.

With cooperative transmission of different access ways and unified resource management, the integration of space-air-ground network has become a historic tendency because of its distinctive superiority in global coverage, massive connectivity, high capacity and low latency, and so on. Intelligent reflecting surface (IRS) techniques rising recently are positioned as a vital enabler for facilitating wireless communication networks. In view of these, this article attempts to give an overview of space-air-ground integrated network (SAGIN) and IRS, as well as to provide a new perspective on how to apply IRS into SAGIN. Based on these, some important research agendas are identified. Then, we present an example of IRSbased vehicle-to-vehicle (V2V) backscatter communication in integrated space-ground network. Finally, preliminary simulations verify the feasibility of the proposed strategy and evidence the benefit of integrating IRS into SAGIN.

The rateless multiple access (RMA) scheme is a promising distributed multiple access scheme to achieve simultaneous high reliability, low latency and massive connectivity. In this paper, we investigate the maximum likelihood (ML) decoding performance of the RMA scheme in an Additive white Gaussian noise (AWGN) channel with binary phase-shift keying (BPSK) modulation. For the first time, this paper derives the ensemble weight distribution of the RMA scheme. We derive an upper bound on the decoding error performance of the RMA scheme under ML decoding in an AWGN channel with BPSK modulation. Using the derived bound as the fitness function, we adopt the continuous genetic algorithm to optimize the parameters of the RMA scheme. Simulation results show the tightness of the derived bound and the superiority of the optimized degree distribution over the conventional degree distributions.

With the rapid development of mobile communication technology, wireless services and application scenarios are evolving toward diversification and intelligence. Large bandwidth, low latency, and massive connections are urgent needs for future network development, and traditional communication network architectures can no longer adapt. With the development of contemporary communication networks, the network architecture of C-RAN (Centralized, Cooperative, Cloud Radio Access Network) can concentrate base station processing resources, dynamically allocate transmitted signals, and have high spectrum utilization. In signal transmission, it also has the advantages of high efficiency, flexible scheduling and energy saving. However, the limited capacity of the fronthaul link under the C-RAN architecture makes signal compression and decompression especially important. This paper proposes an efficient and stable compressed sensing algorithm-a new stepwise orthogonal matching pursuit algorithm (NStOMP algorithm). First, the algorithm does not depend on the number of atoms selected in each iteration, S, and achieves stable compressed signal transmission. Secondly, it combines the idea of backtracking to filter the wrongly selected atoms in the first screening, and performs the second screening of atoms to reconstruct and restore the signal with a higher probability. This paper compares the proposed NStOMP algorithm with the improved StOMP algorithm and other common CS algorithms. The simulation results verify the stability of the proposed algorithm and its advantages compared with the reconstruction effect of common signal compression algorithms. It has better application value in the actual fronthaul network architecture.

The fifth generation (5G) of wireless communication accompanied by the advancement of mobile internet and the Internet of Things (IoT) will create stormy data traffic. The 5G challenges like higher spectral efficiency, massive connectivity, and low latency are addressed by the Non-Orthogonal Multiple Access (NOMA) in recent years. NOMA is proven to be a promising technique from its capability to accommodate a larger number of users in contrast to the conventional orthogonal multiple access (OMA) schemes. NOMA comprises two distinct techniques such as Power-Domain NOMA and Code-Domain NOMA. The non-orthogonal resource allocation in Power-Domain NOMA is practically realized by the Superposition Coding (SC) at the Base Station (BS) and an advanced Successive Interference Cancellation at the User Equipment (UE). In this manuscript, the basic concepts of NOMA, on comparing its channel gain with OMA are discussed first. Specifically, a comprehensive survey of various SIC techniques applied under perfect and imperfect Channel State Information (CSI) uncertainties are summarized in terms of outage probability, ergodic capacity, and system performance. In addition, the sophisticated SIC techniques, when NOMA is integrated with modern wireless communication technologies such as multiple-input multiple-output (MIMO-NOMA) and Cooperative (C-NOMA) communications are investigated. Furthermore, the challenges to be solved with their corresponding opportunities and future research directions of NOMA are explored.