Anders Gjendemsjø

Optimal Power Allocation and Scheduling for Two-Cell Capacity Maximization

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 single-cell scheduler [1] is generalized to the two-cell case. Thus, both power allocation and multiuser diversity are exploited to give substantial network capacity gains.

Binary power control for multi-cell capacity maximization

We consider the problem of optimally allocating the base station transmit powers for a wireless multi-cellular (W-cell) system in order to maximize the total system throughput under interference and noise impairments, and short term (minimum and peak) power constraints. Employing dynamic reuse of spectral resources, we impose the power constraints at each base station and allow for coordination between the base stations. For the two-cell case, the capacity-optimal power allocation has been previously shown to be binary [1]. We now propose to perform binary power allocation, (by simply checking the corners of the domain resulting from the power constraints), also when N > 2, and we identify two scenarios in which the optimality of binary power control can be proven also for arbitrary N. Furthermore, in the general setting for N > 2, we demonstrate by simulations that a network performance with negligible loss, compared to the best non-binary scheme found by geometric programming, can be obtained.

Optimal power control for discrete-rate link adaptation schemes with capacity-approaching coding

In wireless communications, bandwidth is a scarce resource. By employing link adaptation we achieve bandwidth-efficient wireless transmission schemes. We propose a variable-power transmission scheme for slowly varying flat-fading channels using a fixed number of codes. Assuming that capacity-achieving codes for AWGN channels are available, the proposed power adaptation scheme maximizes the average spectral efficiency (ASE) for any finite number N of available rates. We show that the power adapted transmission scheme, using just four different rates, achieves a spectral efficiency within 0.15 bits/s/Hz of the Shannon capacity for continuous rate and power adaptation. Further, when restricted to N optimally chosen rates, introducing power adaptation has significant ASE and outage probability gains over a constant power scheme

Optimal Discrete-Level Power Control for Adaptive Coded Modulation Schemes with Capacity-Approaching Component Codes

In wireless communications, bandwidth is a scarce resource. By employing link adaptation we achieve bandwidth-efficient wireless transmission schemes. Using a fixed number of codes we propose a variable-power transmission scheme for slowly flat-fading channels. Assuming that capacity-achieving codes for AWGN channels are available, we develop new combined discrete-rate discrete-power adaptation algorithms with limited feedback for wireless systems. The adaptation schemes are optimized in order to maximize the average spectral efficiency (ASE) for any finite number of available rates. We show that the new transmission schemes can achieve significantly higher ASE when compared to constant power schemes, almost reaching the upper bound of continuous power adaptation. Specifically, using just four rates and four power levels per rate results in a spectral efficiency that is within 1 dB of the continuous-rate continuous-power Shannon capacity. Further, the novel discrete transmission schemes reduce the probability of outage and are more robust against imperfect channel estimation and prediction.

Rate and power allocation for discrete-rate link adaptation

Link adaptation, in particular adaptive coded modulation (ACM), is a promising tool for bandwidth-efficient transmission in a fading environment. The main motivation behind employing ACM schemes is to improve the spectral efficiency of wireless communication systems. In this paper, using a finite number of capacity achieving component codes, we propose new transmission schemes employing constant power transmission, as well as discrete- and continuous-power adaptation, for slowly varying flat-fading channels. We show that the proposed transmission schemes can achieve throughputs close to the Shannon limits of flat-fading channels using only a small number of codes. Specifically, using a fully discrete scheme with just four codes, each associated with four power levels, we achieve a spectral efficiency within 1 dB of the continuous-rate continuous-power Shannon capacity. Furthermore, when restricted to a fixed number of codes, the introduction of power adaptation has significant gains with respect to average spectral efficiency and probability of no transmission compared to a constant power scheme.

Joint Adaptive Modulation and Diversity Combining With Downlink Power Control

We consider the problem of finding low-complexity, bandwidth-efficient, and processing-power-efficient transmission schemes for a downlink scenario under the framework of diversity combining. Capitalizing on recent results for joint adaptive modulation and diversity combining (AMDC) schemes, we design and analyze two AMDC schemes that utilize power control to reduce the radiated power and, thus, the potential interference to other systems/users. Based on knowledge of channel fading, the proposed schemes adaptively select the signal constellation, diversity combiner structure, and transmit power level. We show that the novel schemes also provide significant average transmit power gains compared to existing joint adaptive quadratic-amplitude modulation (QAM) and diversity schemes. In particular, over a large signal-to-noise ratio (SNR) range, the transmitted power is reduced by 30%-50%, yielding a substantial decrease in interference to coexisting systems/users, while maintaining high average spectral efficiency, low combining complexity, and compliance with bit-error-rate constraints.

A simple greedy scheme for multicell capacity maximization

We study joint optimization of transmit power and scheduling in a multicell wireless network. Despite promising significant gains, this problem is known to be NP-hard and thus difficult to tackle in practice. However, we show that this problem lends itself to analysis for large wireless networks which allows simpler modeling of inter-cell interference. We introduce a low complexity greedy algorithm that is efficient for large networks. As the number of users per cell increases, the solution converges to all cells being active and employing maximum SINR scheduling, which can be implemented in a distributed manner. Using simulation parameters equivalent to those used in realistic wireless networks we show that the scheme, though simple, exhibits substantial gains over existing resource allocation schemes.

Joint Adaptive Transmission and Combining with Optimized Rate and Power Allocation

We consider the problem of finding optimal transmission rates and power allocation under the framework of diversity combining. Capitalizing on recent results for both link adaptation schemes and adaptive combining, we design and analyze two joint link adaptation and diversity combining schemes. Based on the channel fading, the proposed schemes adaptively select both the signal constellation and diversity combiner structure. We show that the novel schemes provide significant throughput gains compared to existing joint adaptive QAM and diversity schemes. Further, contrary to previous results on power control for discrete rate link adaptation, power control does not give significant average spectral efficiency gains in this jointly adaptive setting. However, power control yields significant outage probability gains over the constant power schemes

Minimum Selection GSC with Adaptive Modulation and Post-Combining Power Control

We consider the problem of finding low-complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario under the framework of diversity combining. Capitalizing on recent results for joint adaptive modulation and diversity combining schemes (AMDC), we design and analyze two AMDC schemes that utilize power control to reduce the radiated power, and thus the potential interference to other systems/users. Based on knowledge of the channel fading, the proposed schemes adaptively select the signal constellation, diversity combiner structure, and transmit power level. We show that the novel schemes also provide significant average transmit power gains compared to existing joint adaptive QAM and diversity schemes. In particular, over a large signal to noise ratio range, the transmitted power is reduced by 30-50%, yielding a substantial decrease in interference to co-existing systems/users, while maintaining high average spectral efficiency, low combining complexity, and compliance with bit error rate constraints.

Image Transmission with Adaptive Power and Rate Allocation over Flat Fading Channels Using Joint Source Channel Coding

A joint source channel coder (JSCC) for image transmission over flat fading channels is presented. By letting the transmitter have information about the channel, and by letting the code-rate vary slightly around a target code-rate, it is shown how a robust image coder is obtained by using time discrete amplitude continuous symbols generated through the use of nonlinear dimension changing mappings. Due to their robustness these mappings are well suited for the changing conditions on a fading channel.