Sudhanshu Gaur

Enhancing ZF-DPC Performance with Receiver Processing

Multiuser multiple-input multiple-output (MU-MIMO) systems are known to achieve superior data rates compared to single user (SU-MIMO) systems in the downlink. The achievable rates of MU-MIMO systems are dependent on the precoder design at the transmitter. Dirty paper coding (DPC) is a well known non-linear algorithm to achieve MIMO broadcast channel (BC) capacity. Zero forcing DPC (ZF-DPC) is a sub-optimal way to achieve DPC by triagularizing the channel. In a recent work, it was shown that ZF-DPC with receiver beamforming can provide further improvements. In this paper, we propose an enhancement of ZF-DPC with receiver processing by utilizing the MAC/BC duality. The proposed algorithm is iterative in nature which provides a useful trade-off between complexity and desired performance. Simulation results show that the proposed ZF-DPC algorithm achieves considerable improvement over conventional ZF-DPC and is within 1% of MIMO BC capacity.

Introducing Finer Prioritization in EDCA using Random AIFSN

The recently adopted WLAN standard IEEE 802.11e provides quality of service (QoS) differentiation by grouping the traffic into different access categories (ACs) with different priorities. It defines different arbitration inter-frame space number (AIFSN) on a per-category basis to ensure that each category has different probability of accessing the channel. Within an AC, random back-off mechanism is used to spread the traffic. However, when there are a large number of QoS stations (QSTAs) within an AC, the probability of two or more stations choosing the identical back-off values is increased leading to increased packet collisions. In this paper, we propose the use of randomized AIFSN. The random AIFSN method can be exploited to introduce finer priority values within an AC. Each AC is assigned an AIFSN interval and a probability distribution function (PDF) defined over that interval. The simulation results indicate that the proposed method leads to reduced probability for collisions and higher throughput. We also present some testbed results to verify the improvement using random AIFSN method.

Improved performance of CSMA/CA WLAN using a random inter-frame spacing algorithm

The recently adopted WLAN standard IEEE 802.11e provides quality of service (QoS) differentiation by grouping the traffic into different access categories (ACs) with different priorities. It defines different arbitration inter-frame space number (AIFSN) on a per-category basis to ensure that each category has different probability of accessing the channel. Within an AC, random back-off mechanism is used to spread the traffic. However, when there are a large number of QoS stations (QSTAs) within an AC, the probability of two or more stations choosing the identical back-off values is increased leading to increased packet collisions. In this paper, we propose the use of randomized AIFSN. The proposed technology leads to reduced probability for collisions and higher throughput. It also allows the introduction of many more priority values within an AC. Each AC is assigned an AIFSN interval and a probability distribution function (PDF) defined over that interval. The simulation results indicate that the proposed method also improves the throughput and latency of traffic at all priority levels.

Performance comparison of ZF-DPC to block diagonalization for quantized feedback

Multiuser multiple-input multiple-output (MU-MIMO) systems can achieve higher data rates compared to single user (SU-MIMO) by exploiting multi-user diversity. The capacity bound for MU-MIMO systems is given by the MIMO broadcast channel (BC) capacity. Dirty paper coding (DPC) is a well known non-linear algorithm to achieve this bound. Zero forcing DPC (ZF-DPC) is a sub-optimal way to achieve DPC by triagularizing the channel. In our previous work, we had proposed an enhancement of ZF-DPC by introducing additional receiver which was shown to improve the achievable rates over linear schemes such as block diagonalization. In practise Block Diagonalization is implemented by the receiver feeding back quantized information about the channel and the transmitter figuring out the precoders subsequently. To establish a comparison of ZF-DPC to Block Diagonalization for such practical feedback, we first derive the framework for operating ZF-DPC with quantized feedback. Next we compare the performance of ZF-DPC over Block Diagonalization with quantized feedback and demonstrate that the former still performs better.

Multiuser MIMO Transmission in Distributed Antenna Systems with Heterogeneous User Traffic

In this paper, we consider multiuser transmission in the downlink of a distributed antenna system with two types of users: i) the real-time users that require a minimum instantaneous rate and ii) the best-effort users that try to maximize their rates. We start with a two-user system consisting of one real-time user and one best-effort user, in which the optimal beamforming scheme is proposed to maximize the instantaneous rate of the best-effort user under the rate constraint of the real-time user and per-antenna-power constraint. Two suboptimal transmission schemes are then proposed to reduce the computational complexity and feedback overhead, respectively. Furthermore, we propose a round-robin based scheduler to extend the proposed schemes to a general multiuser system, such that the outage probability of the real-time users is minimized. System-level simulation results show that the proposed schemes have better performance than two reference schemes.

A Practical GDFE Precoder for Multiuser MIMO Systems

Generalized decision feedback equalizer (GDFE) achieves MIMO broadcast channel (BC) capacity but suffers from huge computational complexity and feedback overhead making it unsuitable for practical systems. Much of the complexity is due to the computation of the covariance matrix corresponding to the least favorable noise. Additionally GDFE implementation requires the base stations (BS) to feedback filter coefficients to the users thus increasing overhead. In this paper, we address both the aspects - computational complexity and feedback overhead. We first propose an alternative framework for realizing the GDFE precoder, which avoids the explicit computation of the least favorable noise. We show that, while maintaining capacity optimality of the GDFE precoder, the proposed algorithm has significantly lower complexity. Next, we propose another algorithm which does not require the feedback of filter coefficients from BS to users with minimal loss in achievable capacity. Thus our algorithms are a step towards adopting GDFE precoders in future wireless systems.

Using Finer AIFSN Granularity to Accurately Tune the Flow Ratios in IEEE 802.11e

The current wireless LAN (WLAN) standard, IEEE 802.11e, provides Quality of Service (QoS) differentiation by grouping the traffic into access classes (AC) with different priorities. The traffic prioritization is accomplished by using the enhanced distributed channel access (EDCA) parameters - arbitration inter-frame space (AIFS) interval, contention window (CW), and transmission opportunity (TXOP) - defined on a per-class basis, thus ensuring that each class has different probabilities of accessing the channel. The EDCA parameters are broadcasted by the access point (AP) during the beacon frames. Although, the WLAN standard IEEE 802.11e provides the means to achieve traffic differentiation, it does not specify the method to tune various EDCA parameters to achieve the desired throughput ratios across different ACs. This paper proposes a method to tune the different EDCA parameters in order to get the desired throughput ratios across different ACs that utilizes the available network bandwidth optimally.

A Near-Capacity GDFE-Like Precoder with Reduced Feedback Overhead for MIMO Broadcast Channel

Downlink multi user multiple input multiple output (MU-MIMO) systems are of increasing importance in current and upcoming wireless applications. The improvement in data rates offered by such systems depends on the design of precoding schemes for the broadcast channel (BC) which is their theoretical generalization. A precoding scheme based on generalized decision feedback equalizer (GDFE) is known to achieve MIMO BC capacity. However, GDFE precoder suffers from huge computational complexity and feedback overhead that renders it unsuitable for practical systems. While the computational complexity has been dealt elsewhere, the feedback overhead issue has not yet been resolved. Thus in this paper we propose an algorithm to significantly reduce the feedback requirements of GDFE and show that the performance loss is minimal. We do this by first presenting a variant of the conventional GDFE algorithm, which we prove has the same theoretical performance.

Enhancements to IEEE 802.11 MAC to Avoid Packet Collisions

The IEEE 802.11 WLAN standard specifies two different ways in which a wireless station (STA) can gain access to the channel - (i) distributed channel access where each STA can access channel in a probabilistic manner, (ii) access point (AP) coordinated channel access where the AP provides channel access to each STA by polling mechanism. Whilst the former is attractive because of simpler implementation, it suffers from packet collisions which tend to increase as more STAs try to gain access to the channel. On the other hand, AP coordinated channel access is more robust to packet collisions but it requires fairly complex implementation and has substantial overhead compared to distributed mode. In this paper we propose to add minimal intelligence to the enhanced distributed channel access (EDCA) mechanism of IEEE 802.11e to avoid the packet collisions while maintaining its fairness and simplicity. The simulation results show that the proposed scheme leads to significant throughput improvements over EDCA.