Interference-Aware Resource Control in Multi-Antenna Cognitive Ad Hoc Networks with Heterogeneous Delay Constraints

In this work, we consider a multi-antenna cognitive ad hoc network (CAHNet) with heterogeneous delay requirements. To fulfill the interference and delay constraints simultaneously, we propose to perform adaptive zero-forcing beamforming (ZFBF) at cognitive transmitters according to interference channel state information (CSI). To assist the CAHNet to obtain the interference CSI, we use a win-win inter-network cooperation strategy, namely quantized interference CSI feedback from the primary network to CAHNet through a feedback link, under the condition that the CAHNet pays a proper price for it. Considering the scarcity of feedback and power resources, we focus on the minimization of the overall resource cost subject to both interference and delay constraints. To solve the problem, we derive a joint feedback and power control algorithm amongst multiple links of CAHNet. Finally, simulation results validate the effectiveness of the proposed algorithm.Comment: 4 pages, 2 figure

Clustering algorithm in initialization of multi-hop wireless sensor networks

In most application scenarios of wireless sensor networks (WSN), sensor nodes are usually deployed randomly and do not have any knowledge about the network environment or even their ID's at the initial stage of their operations. In this paper, we address the clustering problems with a newly deployed multi-hop WSN where most existing clustering algorithms can hardly be used due to the absence of MAC link connections among the nodes. We propose an effective clustering algorithm based on a random contention model without the prior knowledge of the network and the ID's of nodes. Computer simulations have been used to show the effectiveness of the algorithm with a relatively low complexity if compared with existing schemes

6G Cellular Networks and Connected Autonomous Vehicles

With 5G mobile communication systems been commercially rolled out, research discussions on next generation mobile systems, i.e., 6G, have started. On the other hand, vehicular technologies are also evolving rapidly, from connected vehicles as coined by V2X (vehicle to everything) to autonomous vehicles to the combination of the two, i.e., the networks of connected autonomous vehicles (CAV). How fast the evolution of these two areas will go head-in-head is of great importance, which is the focus of this paper. After a brief overview on technological evolution of V2X to CAV and 6G key technologies, this paper explores two complementary research directions, namely, 6G for CAVs versus CAVs for 6G. The former investigates how various 6G key enablers, such as THz, cell free communication and artificial intelligence (AI), can be utilized to provide CAV mission-critical services. The latter discusses how CAVs can facilitate effective deployment and operation of 6G systems. This paper attempts to investigate the interactions between the two technologies to spark more research efforts in these areas

Double side signal splitting SWIPT for downlink CoMP transmissions with capacity limited backhaul

This letter studies power allocation for simultaneous wireless information and power transfer in downlink coordinated multipoint (CoMP) systems. A central unit (CU) conveys data and channel information to multiple radio remote units (RRUs) via a capacity-limited backhaul. We provide a dual polarized (DP) antenna-based double side signal splitting method. Specifically, signals are split up into information decoding part [user equipment (UE) data transmitted from CU] and energy harvesting part (deterministic data created at RRUs), which are transmitted and received via vertical and horizontal polarizations of DP antennas, respectively. Normal beamformers (such as zero forcing and maximum ratio transmission) are used to reduce complexity. The problem is to maximize the sum rate satisfying per-UE received power, per-backhaul-link capacity, and per-RRU power transmission constraints. The results are provided to verify the effectiveness of the proposed scheme