Abstract
We propose a continuous rate and power allocation algorithm for multiuser downlink multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems with coordinated multipoint (CoMP) transmission that guarantees to satisfy individual rate target across all users. The optimization problem is formulated as a total transmit power minimization problem subject to per-user rate targets and per-antenna power constraints across multiple cooperating base stations. While the per-antenna power constraint leads to a more complex optimization problem, it is a practical consideration that limits the average transmit antenna power and helps to control the resulting high peak powers in OFDM. Our proposed algorithm uses successive convex approximation (SCA) to transform the non-convex power minimization problem and dynamically allocate power to co-channel user terminals. We prove that the transformed power minimization problem is convex and that our proposed SCA algorithm converges to a solution. The proposed algorithm is compared with two alternative approaches: (1) iterative waterfilling (IWF) and (2) zero-forcing beamforming (ZFB) with semi-orthogonal user selection. Simulation results highlight that the SCA algorithm outperforms IWF and ZFB in both medium- and low-interference environments.
Highlights
Intercell interference (ICI) is a limiting factor on the throughput performance of downlink multiuser multipleinput multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems
6 Conclusions In this paper, the individual User terminals (UTs) rate target is achieved by transforming a non-convex optimization problem into a tractable set of successive convex approximations
A convex lower bound is updated at each iteration to improve the approximation of the achievable rate region, where a dual Lagrange decomposition and a subgradient method is efficient in obtaining the locally optimal solution
Summary
Intercell interference (ICI) is a limiting factor on the throughput performance of downlink multiuser multipleinput multiple-output (MIMO) orthogonal frequencydivision multiplexing (OFDM) systems. The physical interpretation of the inter-user interference gain Gnk,j can be explained as the interference function from the jth UT projecting onto the receiving direction of the kth UT This gives in a weighted sum of the transmitted signal in all L spatial subchannels as a result of a conjugate mismatch between the transmit beamforming weights Vjn and the postprocessing of Ukn. we present the optimization problem that satisfy per-UT rate targets for given per-antenna transmit power constraints. Since the SCA technique is employed to transform the original optimization problem in (7) into a convex one and the feasible set has a non-empty interior, the duality gap between P∗ and D∗ is zero This is due to the fact that any finite rate target is achievable for any given arbitrary large transmit powers. 6: Compute the primal objective P[s] in (12) 7: Compute the dual objective d λ[s], μ[s] in (20)
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