Kashif Mahmood

On the Flow-Level Delay of a Spatial Multiplexing MIMO Wireless Channel

The MIMO wireless channel offers a rich ground for quality of service analysis. In this work, we present a stochastic network calculus analysis of a MIMO system, operating in spatial multiplexing mode, using moment generating functions (MGF). We quantify the spatial multiplexing gain, achieved through multiple antennas, for flow level quality of service (QoS) performance. Specifically we use Gilbert-Elliot model to describe individual spatial paths between the antenna pairs and model the whole channel by an

Delay Constrained Throughput Analysis of a Correlated MIMO Wireless Channel

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Performance of multiuser CDMA receivers with bursty traffic and delay constraints

-State Markov Chain, where

Delay constrained throughput analysis of CDMA using stochastic network calculus

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Delay constrained throughput analysis of SISO

depends upon the degrees of freedom available in the MIMO system. We derive probabilistic delay bounds for the system and show the impact of increasing the number of antennas on the delay bounds under various conditions, such as channel burstiness, signal strength and fading speed. Further we present results for multi-hop scenarios under statistical independence.

State Modulated Traffic Models for Machine Type Communications

The maximum traffic arrival rate at the network for a given delay guarantee (delay constrained throughput) has been well studied for wired channels. However, few results are available for wireless channels, especially when multiple antennas are employed at the transmitter and receiver. In this work, we analyze the network delay constrained throughput of a multiple input multiple output (MIMO) wireless channel with time-varying spatial correlation. The MIMO channel is modeled via its virtual representation, where the individual spatial paths between the antenna pairs are Gilbert-Elliot channels. The whole system is then described by a K-State Markov chain, where K depends upon the degree of freedom (DOF) of the channel. We prove that the DOF based modeling is indeed accurate. Furthermore, we study the impact of the delay requirements at the network layer, violation probability and the number of antennas on the throughput under different fading speeds and signal strength.

On the modeling of delay and burstiness for calculating throughput

In this work, we analyze the performance of linear multiuser CDMA receivers under bursty traffic and queuing delay constraints. An ON/OFF source is used to model the traffic burstiness and stochastic network calculus incorporates the queuing delay constraints in the analysis. At the physical layer, adaptive modulation and coding scheme is adopted and the channel service process is modeled by using a finite-state Markov chain. The following receivers are considered for performance evaluation: single-user matched filter, decorrelator, and linear minimum mean square error detector. We quantify the effect of these multiuser receivers on the traffic carrying capacity of uplink CDMA channels in the large system limit.

Achievable throughput for communication networks: a survey

Code-division multiple-access (CDMA) has the potential to support traffic sources with a wide range of quality of service (QoS) requirements. The traffic carrying capacity of CDMA channels under QoS constraints (such as delay guarantee) is, however, less well-understood. In this work, we propose a method based on stochastic network calculus and large system analysis to quantify the maximum traffic that can be carried by a multiuser CDMA network under the QoS constraints. At the physical layer, we have linear minimum-mean square error receivers and adaptive modulation and coding, while the channel service process is modeled by using a finite-state Markov chain. We study the impact of delay requirements, violation probability and the user load on the traffic carrying capacity under different signal strengths. A key insight provided by the numerical results is as to how much one has to back-off from capacity under the different delay requirements.

Context Awareness in Next Generation of Mobile Core Networks.

We analyze the traffic carrying capacity of a single-input single-output system for a given delay guarantee at the flow level. A continuous time ON/OFF data source is considered as the traffic model while the wireless channel is modeled using the Gilbert-Elliot model. We study the impact of the delay bound violation probability, traffic burstiness, channel memory and the delay requirements at the network layer on the throughput under different signal strength.

Scheduling Policies for the LTE Downlink Channel: A Performance Comparison.

Machine-to-machine (M2M) traffic is variegate and finding a traffic model which can cover a wide range of M2M sources is challenging. In this paper we address this challenge by proposing an extension of legacy renewal processes for modeling of M2M traffic sources. To this end, we first describe the model and derive some performance parameters, as the overall packet arrival distribution and its moments. We then discuss the packetgeneration process and consider the counting variable in atime interval, and give the mean and the Laplace transformof the z-transform for this variable. Successively, we present the asymptotic expansion for the variance and the Index of Dispersion of Counts (IDC). We derive the expression of the two first coefficients of this expansion in the general case, while more explicit expressions are provided for some special cases. More specifically, for the special case of a source model with two states, geometric distribution of the numbers of arrivals in each state, and exponential inter-arrival times, we solve for the modelparameters in terms of mean, variance and two IDCs. The model is then applied to real M2M traces obtained from an operational network. Albeit the match is not perfect, yet the proposed model captures the main features of the traces, in particular the large burstiness in the packet arrival process.