Limited access to available spectrum motivates new age radio frequency (RF) systems to co-exist and cooperate. In this paper, we consider a joint communication and radar system (labeled Comm-Radar), that is capable of receiving and decoding communication signals while simultaneously enabling radar functionalities. Traditionally, systems that leverage principles of spectrum convergence, deemed each functions to be detrimental to the others. This has led to successive interference cancellations strategies that effectively isolate each of the functionalities. Here, in the context of Comm-Radar processing structure, we show that ambient communication transmissions actually assist in radar estimation. The insight is that communications multipath reflects off radar targets (we denote these comm-target paths) in the environment, and can be processed at the receiver to extract extra information. In this work we characterize the fundamental performance limits of such a joint system.To demonstrate the radar performance gain achievable via the processing of extra comm-target paths, the closed-form Cramér-Rao Bound (CRB) for the estimation of direction, range and velocity of a target is derived, for both the general case, and practical radar and communication signalling schemes. Based on the CRB, joint outer bounds are obtained to characterize the trade off between estimation performance and communication rate. Finally, numerical results verify the advantages of utilizing the target reflections from the communication signal to bolster radar performance.

To realize the vision of the Internet of Things (IoT), mobile-edge computing (MEC) has recently emerged as a promising paradigm to meet the computation demand from mobile users (MUs). In this article, we study the network performance in large-scale stochastic MEC wireless networks, where the tasks can be computed locally by the local computation capabilities (LCCs) or be offloaded to MEC servers for edge computing. To this end, a MEC network is modeled featuring random node distribution, dynamic task requests, orthogonal frequency-division multiple access, task retransmission, and parallel computing in MEC servers. Given the model, a 2-D discrete-time Markov chain is first adopted to characterize the task execution process, including local computing and task offloading. Based on the coupling between communication and computing, the average outage probability of the task transmission and the average MEC computation load are derived by integrating the stochastic geometry and queuing theory. Furthermore, by jointly analyzing the local computation latency, transmission latency, and edge computation latency, we derive the average end-to-end latency of the task execution. Our results show that the LCCs in MUs can improve the network performance, including communication and computation performance, in stochastic MEC networks. In addition, useful guidelines for MEC network provisioning and planning are provided to avoid either the local computing or the task offloading being the latency performance bottleneck.

In this paper, the downlink outage performance of full-duplex (FD) multi-cell networks considering interference cancellation at receivers is investigated. Different from previous FD cellular works, where all the interference is assumed to be perfectly cancelled, we propose the concept of strong interference region to distinguish strong interference and weak interference. A practical interference cancellation scheme is proposed to suppress the strong interference. Instead of assuming full-loaded cells in the analysis on FD networks, we consider the dynamic traffic request of the users in the stochastic networks where the cells may not always actively transmit and/or receive signals, consequently they do not always introduce interference to others. The probabilities of base stations (BSs) working in the FD, downlink, uplink and idle modes have been derived. To evaluate the system performance, we derive the outage probability and throughput. The simulation results show that outage performance is significantly improved compared to that without interference cancellation. Meanwhile, after cancelling the strong interference, the performance approaches that of cancelling all the interference. The impacts of the number of user equipments (UEs), the traffic request rate, the density of BSs and the size of the strong interference region on outage performance and throughput performance are further revealed.

Mobile edge computing (MEC) is an emerging architecture to enable variety of innovative applications and services with ultra low latency at the resource-limited mobile devices. In this paper, we investigate how the communication resources and the computing resources, including mobile users and MEC servers, interact with each other in multi-cell MEC-enabled stochastic wireless networks. To this end, the MEC-enabled network model including mobile users with limited storage capacity and computing capabilities is considered, which is characterized in random node distribution, dynamic traffic, orthogonal frequency division multiple access and task retransmission mechanism. Based on the model, the two-dimensional discrete Markov chain is employed to characterize the task execution process. We derive the stationary distribution of the buffer length and outage probability by combining the queuing theory and stochastic geometry, based on which the radio access network throughput is calculated to measure the network performance. Extensive simulations have been conducted to verify the effectiveness of the proposed offloading strategy and to provide valuable insight.

Multi-User scheduling is challenging due to the channel unbalance problem, which leads to system performance degradation. In this paper, two optimal multi-user scheduling schemes maximizing the system throughput are proposed for the fixed and adaptive power transmission scenarios of the full-duplex (FD) multi-user buffer-aided relay system, respectively. Independent and non-identically distributed (i.ni.d.) model is used to characterize the unbalanced channels of different links. In particular, the optimal weight factor of each pair is designed based on the statistical channel state information in both scenarios. With the weight factors, the proposed schemes are able to balance the throughput gaps between different links. In addition, we propose an optimal power allocation scheme with closed-form expressions under average power constraint for the adaptive power transmission scenario. By combining the optimal weight factor and the power allocation scheme, novel optimal selection function is obtained to facilitate the selection process. Considering the specific i.ni.d. Rayleigh fading, the system throughput is further derived in both cases. Theoretical analysis is verified by the numerical simulations and the results demonstrate the superiority of the proposed schemes.

Multi-User scheduling is a challenging problem under the relaying scenarios. Traditional schemes, which are based on the instantaneous signal-to- interference-plus-noises ratios (SINRs), cannot solve the inherent disparities of the qualities between different links. Hence, the system performance is always limited by the weaker links. In this paper, from the whole system throughput view, we propose an optimal multi-user scheduling scheme for the multi-user full-duplex (FD) buffer aided relay systems. We first formulate the throughput maximization problem. Then, according to the characteristics of the Karush-Kuhn-Tucker conditions, we obtain the optimal decision functions and the optimal weighted factors of different links of the proposed scheme. Simulation results show that the proposed scheme not only solves the disparities of the qualities between Si- R and R-Dilinks, but also that between different Si-R or Di-R links, which can be used as guidance in the design of the practical systems.

In this paper, we mainly analyze the inter-cell interference (ICI) and its impacts on system performance for cellular networks with dynamic traffic, where base stations (BSs) do not remain active all the time. This is quite different from the assumption in previous works that base stations (BSs) are full-loaded, which overestimates the interference. To ensure the packet transmission, automatic repeat request (ARQ) protocol is adopted and packets will remain at the head of the buffer until they are successfully transmitted. Retransmissions bring a coupled relationship between the ICI and the buffer states, i.e., the packet transmission is impaired by the ICI, and packets will be blocked at the buffer to be retransmitted, which aggravates the interference in turn. To better reveal this coupled relationship, a queuing model is established to analyze the packet arrival and departure processes. With the aid of the probability generating function (PGF) and the Laplace transform, both the outage probability and the buffer empty probability are derived.

In this paper, we focus on the efficient deployment of high altitude platforms (HAPs). As the accuracy of the channel model highly affects the deployment scheme, we first propose a geometry-based HAP channel model, which considers the statistical and geometry properties of the terrestrial environments comprehensively. Based on the proposed channel model, we derive the Line-of-Sight (LoS) transmission probability of air-to-ground communication, and characterize the path loss analytically. We further propose an algorithm to maximize the deployment efficiency in terms of the coverage ratio, i.e., the ratio of the radius of the HAP to the inter-HAP distance. The accuracy of our theoretical analysis is validated by simulations.

The hybrid half-duplex/full-duplex (HD/FD) relaying scheme is an effective paradigm to overcome the negative effects of the self-interference incurred by the full-duplex (FD) mode. However, traditional hybrid HD/FD scheme does not consider the diversity gain incurred by the multiple antennas of the FD node when the system works in the HD mode, leading to the waste of the system resources. In this paper, we propose a new hybrid HD/FD relaying scheme, which utilizes both the antennas of the FD relay node for reception and transmission when the system works in the HD mode. With multiple antennas, the maximum ratio combining/maximum ratio transmission is adopted to process the signals at the relay node. Based on this scheme, we derive the exact closed-form system outage probability and conduct various numerical simulations. The results show that the proposed scheme remarkably improves the system outage performance over the traditional scheme, and demonstrate that the proposed scheme can more effectively alleviate the adverse effects of the residual self-interference.

In this paper, we address the multi-user scheduling problem of the multi-user two-way full-duplex (FD) decode-and-forward relay system. According to the availability of the channel state information (CSI) and system state information (SSI), three scheduling schemes are investigated in terms of the system outage performance. Specifically, for the non-CSI case, we analyze the random scheduling scheme, which serves as a baseline for comparison. For the full CSI case, we propose the Max-Min scheduling scheme, which is theoretically proved to be sub-optimal in the low signal-to-interference-plus-noise ratio (SINR) regime but optimal in the high SINR regime. To minimize the outage probability, we propose the optimal scheduling scheme, which involves the full SSI. In addition, the exact closed-form outage probability expressions corresponding to different schemes are derived under the general independent but not identically distributed channels. The residual self-interference incurred by the FD mode is taken into account. Moreover, independent and identically distributed channels are also considered as special cases. Finally, numerical simulations are performed to corroborate the theoretical results. The results reveal that the Max-Min scheduling and optimal scheduling schemes significantly improve the outage performance compared with the random scheduling scheme.