Optimal Power Allocation and Scheduling for Two-Cell Capacity Maximization

Abstract

Abstract-We consider the problem of optimally allocating the base station transmit power in two neighboring cells for a TDMA wireless cellular system, to maximize the total system throughput under interference and noise impairments. Employing dynamic reuse of spectral resources, we impose a peak power constraint at each base station and allow for coordination between the base stations. By an analytical derivation we find that the optimal power allocation then has a remarkably simple nature: Depending on the noise and channel gains, transmit at full power only at base station 1 or base station 2, or both.Utilizing the optimal power allocation we study optimal link adaptation, and compare to adaptive transmission without power control. Results show that allowing for power control significantly increases the overall capacity for an average user pair, in addition to considerable power savings. Furthermore, we investigate power adaptation in combination with scheduling of users in a time slotted system. Specifically, the capacity-optimal singlecell scheduler [1] is generalized to the two-cell case. Thus, both power allocation and multiuser diversity are exploited to give substantial network capacity gains.

Transmit Power Control in MIMO Cellular Systems

“…Setting s*= 0 and solving (15) (14) or (15 All simulations were carried out in a shadow fading environment with log-normal shadowing (with standard deviation 9dB) and path loss effects (with path loss exponent a = 3). We use the classic fading model: Fi = ALr-l. (16) where A is a constant, L is a lognormal shadowing variable and r is the link distance.…”

“…In the downlink this works by adjusting the total output power for each BS, in an attempt to mitigate interference, while maintaining a satisfactory intracell link. Examples of this approach for single antenna links are given in [12], [13], [14], [15], [16]. However, as for the other techniques, optimal power control still requires BS collaboration and a significant amount of feedback and processing.…”

Joint Scheduling and Power Control in Coordinated Multi-Point Clusters

“…In [5], a fast multi-cell RRM algorithm is proposed and evaluated for the uplink of a coordinated cluster, which shows that RRM coordination can provide significant performance gains compared to traditional single-cell configurations. A capacitymaximizing coordinated power control is derived for the downlink of a two-cell cluster in [6], where binary power control is proved to be the optimal power allocation, i.e., in any given time slot, the cell either transmits with full power (turned on) or does not transmit (turned off). Based on [6], it is shown in [7] and [8] that the binary power control can be extended to the multi-cell environment with negligible performance loss compared to the optimal solution.…”

“…A capacitymaximizing coordinated power control is derived for the downlink of a two-cell cluster in [6], where binary power control is proved to be the optimal power allocation, i.e., in any given time slot, the cell either transmits with full power (turned on) or does not transmit (turned off). Based on [6], it is shown in [7] and [8] that the binary power control can be extended to the multi-cell environment with negligible performance loss compared to the optimal solution. The main limitation of [6]- [8] is, however, that no CoMP joint transmission is supported.…”

“…Based on [6], it is shown in [7] and [8] that the binary power control can be extended to the multi-cell environment with negligible performance loss compared to the optimal solution. The main limitation of [6]- [8] is, however, that no CoMP joint transmission is supported. In [9], the authors consider a system model with CoMP joint transmission and the user scheduling problem is treated assuming that all BSs always transmit on full power, i.e., no joint power control across multiple BSs is considered.…”