In this contribution, the concept of spatial modulation (SM) is firstly integrated into the structure of space-time block codes (STBC)-aided vertical Bell-labs layered space-time (VBLAST) systems, in order to strike a balanced tradeoff among bit error ratio (BER), spectral efficiency and computational complexity. First of all, in order to enhance the BER performance of STBC-VBLAST, we advocate an effective transmit power allocation (TPA) scheme with negligible implementation costs, while dividing the STBC and VBLAST layers with alleviated interference, so as to facilitate combination with SM. Then, we further utilize the unique structure of SM for enhancing the spectral efficiency of original STBC-VBLAST, wherein the information is conveyed by not only the amplitude/phase modulation (APM) symbols but also the antenna indices. In addition, constellation sets of STBC symbols are specifically designed to be rotated to make full use of the degrees of freedom. Finally, the performance advantages of the above-mentioned structures over traditional STBC-VBLAST are demonstrated by the theoretical derivation of a closed-form expression for the union bound on the bit error probability for various spectral efficiencies, and they are supported by simulation results.
For reducing the switching frequency between the radio frequency (RF) chain and transmit antennas, a class of new sparse space shift keying modulation (SSSK) schemes are presented. This new class is proposed to simplify hardware implementation, through carefully designing the spatial constellation mapping pattern. Specifically, different from traditional space shift keying modulation (SSK), the proposed SSSK scheme utilizes more time slots to construct a joint design of time and spatial domain SSK modulation, while maintaining the special structure of single RF chain. Since part of the multi-dimension constellations of SSSK concentrate the energy in less time slots, the RF-switching frequency is effectively reduced due to the sparsity introduced in the time domain. Furthermore, through theoretical analysis, we obtain the closed-form expression of the bit error probability for the SSSK scheme, and demonstrate that slight performance gain can be achieved compared to traditional SSK with reduced implementation cost. Moreover, we integrate transmit antenna selection (TAS) to achieve considerable performance gain. Finally, simulation results confirm the effectiveness of the proposed SSSK scheme compared to its traditional counterpart.
Unmanned aerial vehicles (UAVs) have been widely considered to enhance the communication coverage, as well as the wireless power transfer (WPT) of energy-constrained communication networks to prolong their lifetime. However, the trajectory design of a UAV in such a system remains a key problem, especially considering the three-dimensional (3D) feature of the UAV. To address this issue, a UAV-assisted dual-user WPT system was investigated in this paper, where a UAV-mounted energy transmitter (ET) flies in the air to broadcast wireless energy to charge the energy receivers (ERs) on the ground. By optimizing the UAV’s 3D trajectory toward a balanced tradeoff between energy consumption and WPT performance, the energy harvested by all ERs during a given mission period was maximized. The above goal was achieved through the following detailed designs. On the one hand, on the basis of previous research results, there is a one-to-one correspondence between the UAV’s abscissa and height, so only the relationship between the height and time was focused on in this work to obtain the UAV’s optimal 3D trajectory. On the other hand, the idea of calculus was employed to calculate the total harvested energy, leading to the proposed high-efficiency trajectory design. Finally, the simulation results demonstrated that this contribution is capable of enhancing the energy supply by carefully designing the 3D trajectory of the UAV, compared to its conventional counterpart. In general, the above-mentioned contribution could be a promising way for UAV-aided WPT in the future Internet of Things (IoT) and wireless sensor networks (WSNs).
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