Energy Harvesting Technique for Massive MIMO Wireless Communication Networks

Abstract

Massive For wireless data and energy transfer, MIMO, a key component of future 5G systems, is favourable. A big part of the reason for this is that it has the ability to narrow down the distribution of energy. The scope of something enormous Multiple-Input in 5G, harvesting may be used to boost system capacity and efficiency via multiple-output multiple access. This was followed by the introduction of the Simultaneous Wireless Information and Power Transfer (SWIPT) method, commonly known as energy harvesting optimization. Specific to each user’s needs, we connected a splitter on the receiver, and we measured their output using power beacons. In order to achieve the lowest possible communication rate, the user’s total gathered power is boosted. Simulations show that the proposed technique is more successful than the other options out there. There are two sources of energy for D2D transmitters: specialised beacon signals, and cellular users (CUs) radio frequency (RF) interference. In D2D transmitters, inverse power control techniques are used for power regulation. We employ Poisson Point Processes(PPP) to model the proposed hybrid network’s CU, D2D user (DU), and PB locations. Each slot in the time period is assigned a different beam forming weight. Using the alternating minimization technique, we provide a solution approach for a non-convex quadratic ally limited linear problem. Long-distance wireless power transmission requires the use of energy beam generation technologies in a large-scale MIMO system in order to make sure that the transmission is safe. In other words, this letter tries to maximise the energy efficiency of information transmission (bits per joule) while keeping the required quality of service (QoS), which is a delay constraint, in mind. This is done by maximising the transfer length and transmits power, among other things. In this case, we try to maximise the total amount of energy at the relays, use block diagonalization (BD) at the source, and try to minimise interference between the relay-destination channels. As a last step, we also run simulations of the power consumption of a generic circuit. As a supplement to this work, there are some basic online rules for all possible situations. Numerical results show that a near-optimal online technique can do the same job as its offline counterpart when the maximum power consumption of the circuit is taken into account.