Throughput Analysis for Multi-Point Joint Transmission with Quantized CSI Feedback

This paper addresses the problem of limited CSI feedback in coordinated multi-point (CoMP) networks. Specifically, the system throughput is obtained for block-fading CoMP channels with quantized CSI feedback, and the effect of feedback bit allocation on the system throughput is investigated for different user locations and fading distributions. The analytical and simulation results show that substantial throughput increment is achieved via CoMP joint transmission with very limited number of feedback bits per base station. The effect of optimal bit allocation becomes more important for the user that is located in the CoMP cluster edge areas. Also, the standard Zonal-sampling scheme provides the best bit allocation strategy in many cases, maximizing the system throughput

Interference management using one bit feedback

This paper studies the performance of quasi-static spectrum sharing networks utilizing one bit interference indicator feedback. Assuming no channel state information at the transmitters, the channel average rate is obtained under different power allocation strategies. Simulation results show that interference indicator feedback leads to considerable rate increment even with no transmitter channel state information

On the Ergodic Achievable Rates of Spectrum Sharing Networks with Finite Backlogged Primary Users and an Interference Indicator Signal

Spectrum sharing networks are communication setups in which unlicensed secondary users (SUs) are permitted to work within the spectrum resources of licensed primary users (PUs). This paper aims to study the ergodic achievable rates of spectrum sharing networks with finite backlogged primary user and an interference indicator signal. Here, in contrast to the standard interference-avoiding schemes, the secondary user activity is not restricted within the primary user inactive periods. Considering both fading and nonfading channels, the unlicensed user ergodic achievable rate is obtained for different unlicensed user transmission power and licensed user received interference power or signal-to-interference-and-noise (SINR) constraints. In the case of fading channels, the results are obtained for both short-and long-term primary user quality-of-service requirements. Further, the results are generalized to the case of multiple interfering users. In terms of unlicensed user ergodic achievable rate, analytical results indicate that while the standard interference-avoiding approach is the optimal transmission scheme at low secondary user or high primary user transmission powers, higher rates can be achieved via simultaneous transmission at high secondary user SINRs. Moreover, numerical results show that, using an interference indicator signal, there is considerable potential for data transmission of unlicensed users under different licensed users quality-of-service requirements

On the Average Rate of HARQ-Based Quasi-Static Spectrum Sharing Networks

Spectrum sharing networks are communication setups in which unlicensed secondary users are permitted to work within the spectrum resources of primary licensees. Considering quasi-static fading environments, this paper studies the effect of hybrid automatic repeat request (HARQ) feedback on the average rate of unlicensed spectrum sharing channels. The results are obtained for different scenarios; Under both peak and average secondary user transmission power constraints, the channel average rate is determined under primary user limited received interference power conditions when there is perfect information about the interference available at the secondary user transmitter. An approximate solution for power allocation between incremental redundancy (INR) HARQ-based data retransmissions is proposed which can be applied in single-user networks as well. Then, we investigate the effect of imperfect secondary-primary channel state information on the interference-limited average rate of the secondary channel. Finally, we restudy all mentioned scenarios in the case where the data transmission is constrained to have limited outage probability. Substantial performance improvement is observed with even a single HARQ-based retransmission in all simulations

On Noisy ARQ in Block-Fading Channels

Assuming noisy feedback channels, this paper investigates the data transmission efficiency and robustness of different automatic repeat request (ARQ) schemes using adaptive power allocation. Considering different block-fading channel assumptions, the long-term throughput, the delay-limited throughput, the outage probability and the feedback load of different ARQ protocols are studied. A closed-form expression for the power-limited throughput optimization problem is obtained which is valid for different ARQ protocols and feedback channel conditions. Furthermore, the paper presents numerical investigations on the robustness of different ARQ protocols to feedback errors. It is shown that many analytical assertions about the ARQ protocols are valid both when the channel remains fixed during all retransmission rounds and when it changes in each round (in)dependently. As demonstrated, optimal power allocation is crucial for the performance of noisy ARQ schemes when the goal is to minimize the outage probability

Channel Capacity Bounds in the Presence of Quantized Channel State Information

The goal of this paper is to investigate the effect ofchannel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where 1) there is imperfect channel quality information available to the transmitter and the receiver and 2) while the channel gain is continuously varying, there are few cross-region changes and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channeldistributions, and for both Max-Lloyd and equal probabilityquantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR\u27s, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and longtermpower constraints

Channel Capacity Bounds in the Presence of Quantized Channel State Information

<p/> <p>The goal of this paper is to investigate the effect of channel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where (1) there is imperfect channel quality information available to the transmitter and the receiver and (2) while the channel gain is continuously varying, there are few cross-region changes, and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channel distributions, and for both Max-Lloyd and equal probability quantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR's, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and long-term power constraints.</p

Channel Capacity Bounds in the Presence of Quantized Channel State Information

The goal of this paper is to investigate the effect ofchannel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where 1) there is imperfect channel quality information available to the transmitter and the receiver and 2) while the channel gain is continuously varying, there are few cross-region changes and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channeldistributions, and for both Max-Lloyd and equal probabilityquantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR\u27s, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and longtermpower constraints