Satellite-terrestrial networks are emerging as the next-generation networking paradigm for Beyond-5 G (B5G) and 6 G networks. Meanwhile, Mobile Edge Computing (MEC) is envisioned as the key technology to provide network services within the proximity of users, by deploying computing resource in ground locations that are close to users. With the fast deployment of Low-Earth-Oribt (LEO) satellites, a new paradigm of MEC is emerging by enabling LEO satellites serving as edge servers in lower orbits that are close to ground users. In this way, the ground users can be further served by LEO satellites in lower orbits instead of conventional high-orbit satellites. Also, since LEO satellites provide shorter paths from users to services, the performance is enhanced compared with ground MEC networks. In this paper, we aim to enable low-latency network services in a Satellite Edge Computing (SEC) network that integrates the MEC and satellite-terrestrial networks. In particular, we consider that each network service is composed of a sequence of Virtualized Network Functions (VNFs), where the traffic of user requests has to be processed by the VNFs in a service chain in the specified order before reaching its destination. To this end, we first formulate a delay-aware service chaining problem in an SEC network to minimize the average delay of implementing a user request, by jointly placing VNFs to LEO satellites in the SEC network and routing the traffic of each user request from its source to destination. We then devise an approximation algorithm with an approximation ratio for the problem in an SEC network with a single user request, by devising a novel concept ofchaining orbitand auxiliary graph construction technique. We also design an online algorithm for the online delay-aware service chaining problem in an SEC network, if user requests arrive into the system without the knowledge of their arrivals and the network delays are uncertain. We finally evaluate the performance of the proposed algorithms using real satellite network topologies, and results show that the proposed algorithms achieve 28.5% lower delay than their counterparts.

5G IoT communications have some new requirements on the whole system design, e.g., low cost, low power consumption, long distance coverage and massive connection. To fulfill all these requirements, a narrow-band SCMA scheme is proposed. Narrow band pulse shaping is employed, so that the coverage can be expanded with low-cost and low-power devices. Two types of waveforms are provided, both of which use SCMA to enlarge the number of supported devices. Simulation results show that, comparing to the existing narrow band techniques, narrow-band SCMA scheme can support more dense connectivity without any other performance degradation.

In this study, a two-hop wireless sensor network with multiple relay nodes is considered where the amplify-and-forward (AF) scheme is employed. Two algorithms are presented to jointly consider interference suppression and power allocation (PA) based on the minimization of the symbol error rate (SER) criterion. A stochastic gradient (SG) algorithm is developed on the basis of the minimum-SER (MSER) criterion to jointly update the parameter vectors that allocate the power levels among the relay sensors subject to a total power constraint and the linear receiver. In addition, a conjugate gradient (CG) algorithm is developed on the basis of the SER criterion. A centralized algorithm is designed at the fusion center. Destination nodes transmit the quantized information of the PA vector to the relay nodes through a limited-feedback channel. The complexity and convergence analysis of the proposed algorithms are carried out. Simulation results show that the proposed two adaptive algorithms significantly outperform the other previously reported algorithms.

In this work, we study a joint iterative power allocation and interference suppression technique based on the minimization of the bit error rate (BER) cost function for cooperative direct-sequence code division multiple-access (DS-CDMA)systems that employ multiple relays and the amplifyand-forward (AF) strategy. We develop stochastic gradient (SG) algorithms based on the minimum-BER (MBER) criterion to jointly update the parameter vectors that allocate the power levels among the relays subject to a power constraint and the linear receiver. Simulation results show that the proposed adaptive algorithms significantly outperform the two other comparison schemes.