TY - GEN
T1 - Optimum pilot and data energy allocation for BPSK transmission over massive MIMO systems
AU - Ballal, Tarig
AU - Suliman, Mohamed A.
AU - Alrashdi, Ayed
AU - Al-Naffouri, Tareq Y.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2016-KKI-2899.
Acknowledgements: This work was supported by the KAUST Office of Sponsored Research under Award OSR-2016-KKI-2899.
PY - 2019
Y1 - 2019
N2 - Recovering data symbols in a wireless communications system consists of two main estimation steps: channel estimation based on transmitted pilot symbols, and estimation of data symbols using the acquired channel information. The amount of energy allocated to each of pilot and data transmission determines the performance of each estimation step, which further impacts the overall system performance. In this paper, we consider a linear minimum mean squared error (LMMSE) receiver that uses the LMMSE estimator for both channel information acquisition and data symbol recovery in the context of a massive MIMO system. We derive the mean squared error (MSE) of the estimated symbols as a function of the energy allocation. Exploiting the large dimensionality of the problem, we leverage tools from random matrix theory to express the MSE only in terms of the deterministic parameters of the system. We further utilize the deterministic expression to find the optimal energy allocation. The theoretical results are matched with simulations showing high level of congruence.
AB - Recovering data symbols in a wireless communications system consists of two main estimation steps: channel estimation based on transmitted pilot symbols, and estimation of data symbols using the acquired channel information. The amount of energy allocated to each of pilot and data transmission determines the performance of each estimation step, which further impacts the overall system performance. In this paper, we consider a linear minimum mean squared error (LMMSE) receiver that uses the LMMSE estimator for both channel information acquisition and data symbol recovery in the context of a massive MIMO system. We derive the mean squared error (MSE) of the estimated symbols as a function of the energy allocation. Exploiting the large dimensionality of the problem, we leverage tools from random matrix theory to express the MSE only in terms of the deterministic parameters of the system. We further utilize the deterministic expression to find the optimal energy allocation. The theoretical results are matched with simulations showing high level of congruence.
UR - http://hdl.handle.net/10754/661881
UR - https://ieeexplore.ieee.org/document/8985379/
UR - http://www.scopus.com/inward/record.url?scp=85079645518&partnerID=8YFLogxK
U2 - 10.1109/WCNC44850.2019.8985379
DO - 10.1109/WCNC44850.2019.8985379
M3 - Conference contribution
SN - 9781538676462
BT - 2019 IEEE Wireless Communications and Networking Conference (WCNC)
PB - IEEE
ER -