This paper considers the optimum single cell power-control maximizing the aggregate (uplink) communication rate of the cell when there are peak power constraints at mobile users, and a low-complexity data decoder (without successive decoding) at the base station. It is shown, via the theory of majorization, that the optimum power allocation is binary, which means links are either "on" or "off". By exploiting further structure of the optimum binary power allocation, a simple polynomial-time algorithm for finding the optimum transmission power allocation is proposed, together with a reduced complexity near-optimal heuristic algorithm. Sufficient conditions under which channel-state aware time-division-multiple-access (TDMA) maximizes the aggregate communication rate are established. Finally, a numerical study is performed to compare and contrast the performance achieved by the optimum binary power-control policy with other sub-optimum policies and the throughput capacity achievable via successive decoding. It is observed that two dominant modes of communication arise, wideband or TDMA, and that successive decoding achieves better sum-rates only under near-perfect interference cancellation efficiency.
In addition to @cite_18 , some other works such as @cite_6 , @cite_21 and @cite_3 also motivate us to investigate the optimality of binary power-control. Both @cite_6 and @cite_21 consider jointly optimal allocation of rates and transmission powers in CDMA networks under alternative objectives such as maximization of the sum of signal-to-interference-plus-noise-ratios ( @math ) @cite_6 and the packet success probability @cite_21 . Both approaches convert the problem into a convex optimization problem, and show that the optimum power-control is indeed binary under such approximations. In @cite_3 , the authors proved the optimality of an almost binary power-control strategy, up to one exceptional transmission power level in the continuum between @math and the peak power level, maximizing the total uplink communication rate.
@cite_18 @cite_21 @cite_3 @cite_6
2150586017 2045996972 1974592452 2063449729
We consider allocating the transmit powers for a wireless multi-link (N-link) system, in order to maximize the total system throughput under interference and noise impairments, and short term power constraints. Employing dynamic spectral reuse, we allow for centralized control. In the two-link case, the optimal power allocation then has a remarkably simple nature termed binary power control: depending on the noise and channel gains, assign full power to one link and minimum to the other, or full power on both. Binary power control (BPC) has the advantage of leading towards simpler or even distributed power control algorithms. For N>2 we propose a strategy based on checking the corners of the domain resulting from the power constraints to perform BPC. We identify scenarios in which binary power allocation can be proven optimal also for arbitrary N. Furthermore, in the general setting for N>2, simulations demonstrate that a throughput performance with negligible loss, compared to the best non-binary scheme found by geometric programming, can be obtained by BPC. Finally, to reduce the complexity of optimal binary power allocation for large networks, we provide simple algorithms achieving 99 of the capacity promised by exhaustive binary search. This paper addresses the problem of dynamic resource allocation in a multiservice direct-sequence code-division multiple-access (DS-CDMA) wireless network supporting real-time (RT) and nonreal-time (NRT) communication services. For RT users, a simple transmission power allocation strategy is assumed that maximizes the amount of capacity available to NRT users without violating quality of service requirements of RT users. For NRT users, a joint transmission power and spreading gain (transmission rate) allocation strategy, obtained via the solution of a constrained optimization problem, is provided. The solution maximizes the aggregate NRT throughput, subject to peak transmission power constraints and the capacity constraint imposed by RT users. The optimization problem is solved in a closed form, and the resulting resource allocation strategy is simple to implement as a hybrid CDMA time-division multiple-access strategy. Numerical results are presented showing that the optimal resource allocation strategy can offer substantial performance gains over other conventional resource allocation strategies for DS-CDMA networks. The information-theoretic sum capacity of reverse link CDMA systems with QoS constraints is investigated in this paper. Since the reverse link of CDMA systems are, for a given channel and noise conditions, interference-limited, the sum capacity can be achieved by optimally allocating the transmit powers of the mobile stations with the optimal (Shannon) coding. Unfortunately, the sum capacity is usually achieved via unfair resource allocation. This can be avoided by imposing QoS constraints on the system. The results here show that for a single cell system, the sum capacity can be achieved while meeting the QoS constraints with a semi-bang-bang power allocation strategy. Numerical results are then presented to show the multi-user diversity gain and the impact of QoS constraints. The implication of TDM operation in a practical reverse link CDMA system is also discussed. We determine the optimal adaptive rate and power control strategies to maximize the total throughput in a multirate code-division multiple-access system. The total throughput of the system provides a meaningful baseline in the form of an upper bound to the throughput achievable with additional restrictions imposed on the system to guarantee fairness. Peak power and instantaneous bit energy-to-noise spectral density constraints are assumed at the transmitter with matched filter detection at the receiver. Our results apply to frequency selective fading in so far as the bit energy-to-equivalent noise power spectral density ratio definition can be used as the quality-of-service metric. The bit energy-to-equivalent noise power spectral density ratio metric coincides with the bit-error rate metric under the assumption that the processing gains and the number of users are high enough so that self-interference can be neglected. We first obtain results for the case where the rates available to each user are unrestricted, and we then consider the more practical scenario where each user has a finite discrete set of rates. An upper bound to the maximum average throughput is obtained and evaluated for Rayleigh fading. Suboptimal low-complexity schemes are considered to illustrate the performance tradeoffs between optimality and complexity. We also show that the optimum rate and power adaptation scheme with unconstrained rates is in fact just a rate adaptation scheme with fixed transmit powers, and it performs significantly better than a scheme that uses power adaptation alone.