97 research outputs found
Power Efficient User Cooperative Computation to Maximize Completed Tasks in MEC Networks
In this paper, the user cooperative task computation is explored by sharing the computing capability of the user equipments (UEs) so as to enhance the performance of mobile edge computing (MEC) networks. The number of completed tasks is maximized while minimizing the total power consumption of the UEs by jointly optimizing the user task offloading decision, the computational speed for the offloaded task and the transmit power for task offloading. An iterative algorithm based on the linear programming relaxation is proposed to solve the formulated mixed integer non-linear problem. The simulation results show that the proposed user cooperative computation scheme can achieve a higher completed tasks ratio than the noncooperative scheme
On consideration of content preference and sharing willingness in D2D assisted offloading
Device-to-device (D2D) assisted offloading heavily depends on the participation of human users. The
content preference and sharing willingness of human users are two crucial factors in the D2D assisted
offloading. In this paper, with consideration of these two factors, the optimal content pushing strategy
is investigated by formulating an optimization problem to maximize the offloading gain measured by
the offloaded traffic. Users are placed into groups according to their content preferences, and share
content with intergroup and intragroup users at different sharing probabilities. Although the optimization
problem is nonconvex, the closed-form optimal solution for a special case is obtained, when the
sharing probabilities for intergroup and intragroup users are the same. Furthermore, an alternative group
optimization (AGO) algorithm is proposed to solve the general case of the optimization problem. Finally,
simulation results are provided to demonstrate the offloading performance achieved by the optimal
pushing strategy for the special case and AGO algorithm. An interesting conclusion drawn is that the
group with the largest number of interested users is not necessarily given the highest pushing probability.
It is more important to give high pushing probability to users with high sharing willingness
3D Positioning Algorithm Design for RIS-aided mmWave Systems
In this paper, we investigate a three-dimensional (3D) positioning algorithm
for a millimeter wave (mmWave) system, where the reconfigurable intelligent
surfaces (RIS) are leveraged to enhance the positioning performance of mobile
users (MUs). We propose a two-stage weight least square (TSWLS) algorithm to
obtain the closed-form solution of the MU's position. In the first stage, we
construct the pseudolinear equations based on the angle of arrival (AOA) and
the time difference of arrival (TDOA) estimation at the RISs, then we obtain a
preliminary estimation by solving these equations using the iterative weight
least square (WLS) method. Based on the preliminary estimation in the first
stage, a new set of pseudolinear equations are obtained, and a finer estimation
is obtained by solving the equations using the WLS method in the second stage.
By combining the estimation of both stages, the final estimation of the MU's
position is obtained. Further, we study the theoretical bias of the proposed
algorithm by considering the estimation error in both stages. Simulation
results demonstrate the superiority of the proposed positioning algorithm.
Furthermore, it is also shown that the proposed algorithm still have good
positioning performance with low SNR.Comment: Keywords: Reconfigurable intelligent surface (RIS), intelligent
reflecting surface (IRS
Channel Tracking for RIS-aided mmWave Communications Under High Mobility Scenarios
The emerging reconfigurable intelligent surface (RIS) technology is promising
for applications in the millimeter wave (mmWave) communication systems to
effectively compensate for propagation loss or tackle the blockage issue.
Considering the high mobility of users in realistic scenarios, it is essential
to adjust the phase shifts in real time to align the beam towards the mobile
users, which requires to frequently estimate the channel state information.
Hence, it is imperative to design efficient channel tracking schemes to avoid
the complex channel estimation procedure. In this paper, we develop a novel
channel tracking scheme with two advantages over conventional schemes. First,
our tracking scheme is based on the cascaded angles at the RIS instead of the
accurate angle values, which is more practical. Second, it can be employed
under a more general setting where the noise can be non-Gaussian. Simulation
results show the high tracking accuracy of our proposed scheme, and validate
the superiority to the existing EKF-based tracking scheme.Comment: 5 pages, 4 figures, Submitted to IEE
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