Nageen Himayat

M2M: From mobile to embedded internet

Is M2M hype or the future of our information society? What does it take to turn the M2M vision into reality? In this article we discuss the business motivations and technology challenges for machine-to-machine communications. We highlight key M2M application requirements and major technology gaps. We analyze the future directions of air interface technology improvements and network architectures evolution to enable the mass deployment of M2M services. In particular, we consider the salient features of M2M traffic that may not be supported efficiently by present standards, and provide an overview of potential enhancements. Finally, we discuss standards development for M2M.

Distributed Interference-Aware Energy-Efficient Power Optimization

Power optimization techniques are becoming increasingly important in wireless system design since battery technology has not kept up with the demand of mobile devices. They are also critical to interference management in wireless systems because interference usually results from both aggressive spectral reuse and high power transmission and severely limits system performance. In this paper, we develop an energy-efficient power optimization scheme for interference-limited wireless communications. We consider both circuit and transmission powers and focus on energy efficiency over throughput. We first investigate a non-cooperative game for energy-efficient power optimization in frequency-selective channels and reveal the conditions of the existence and uniqueness of the equilibrium for this game. Most importantly, we discover a sufficient condition for generic multi-channel power control to have a unique equilibrium in frequency-selective channels. Then we study the tradeoff between energy efficiency and spectral efficiency and show by simulation results that the proposed scheme improves both energy efficiency and spectral efficiency in an interference-limited multi-cell cellular network.

Energy Efficient Design in Wireless OFDMA

Energy-efficient transmission is an important aspect of wireless system design due to limited battery power in mobile devices. We consider uplink energy-efficient transmission in OFDMA systems since mobile stations are battery powered. We account for both circuit and transmit power when designing energy-efficient communication mechanisms and emphasize energy efficiency over peak rates or throughput. Both link adaptation and resource allocation schemes are developed to optimize the overall bits transmitted per Joule of energy, which allows for maximum energy savings in a network. Our simulation results show that the proposed schemes significantly improve energy efficiency.

Capacity and coverage enhancement in heterogeneous networks

Disruptive innovations in mobile broadband system design are required to help network providers meet the exponential growth in mobile traffic demand with relatively flat revenues per bit. Heterogeneous network architecture is one of the most promising low-cost approaches to provide significant areal capacity gain and indoor coverage improvement. In this introductory article, we provide a brief overview of heterogeneous network architectures comprising hierarchical multitier multiple radio access technologies (RAT) deployments based on newer infrastructure elements. We begin with presenting possible deployment scenarios of heterogeneous networks to better illustrate the concepts of multitier and multi-RAT. We then focus on multitier deployments with single RAT and investigate the challenges associated with enabling single frequency reuse across tiers. Based on the spectrum usage, heterogeneous networks can be categorized into single carrier usage, where all devices within the network share the same spectrum, and distinct carrier usage, where different types of devices are allocated separate spectra. For single carrier usage, we show that interference management schemes are critical for reducing the resulting cross-tier interference, and present several techniques that provide significant capacity and coverage improvements. The article also describes industry trends, standardization efforts, and future research directions in this rich area of investigation.

Interference management for 4G cellular standards [WIMAX/LTE UPDATE]

4G cellular standards are targeting aggressive spectrum reuse (frequency reuse 1) to achieve high system capacity and simplify radio network planning. The increase in system capacity comes at the expense of SINR degradation due to increased intercell interference, which severely impacts cell-edge user capacity and overall system throughput. Advanced interference management schemes are critical for achieving the required cell edge spectral efficiency targets and to provide ubiquity of user experience throughout the network. In this article we compare interference management solutions across the two main 4G standards: IEEE 802.16m (WiMAX) and 3GPP-LTE. Specifically, we address radio resource management schemes for interference mitigation, which include power control and adaptive fractional frequency reuse. Additional topics, such as interference management for multitier cellular deployments, heterogeneous architectures, and smart antenna schemes will be addressed in follow-up papers.

Interference-Aware Energy-Efficient Power Optimization

While the demand for battery capacity on mobile devices has grown with the increase in high-bandwidth multi-media rich applications, battery technology has not kept up with this demand. Therefore power optimization techniques are becoming increasingly important in wireless system design. Power optimization schemes are also important for interference management in wireless systems as interference resulting from aggressive spectral reuse and high power transmission severely limits system performance. Although power optimization plays a pivotal role in both interference management and energy utilization, little research addresses their joint interaction. In this paper, we develop energy-efficient power optimization schemes for interference-limited communications. Both circuit and transmit powers are considered and energy efficiency is emphasized over throughput. We note that the general power optimization problem in the presence of interference is intractable even when ideal user cooperation is assumed. We first study this problem for a simple two-user network with ideal user cooperation and then develop a practical non-cooperative power optimization scheme. Simulation results show that the proposed scheme improves not only energy efficiency but also spectral efficiency in an interference-limited cellular network.

Energy-Efficient Transmission in Frequency-Selective Channels

Energy efficiency is becoming increasingly important for small form factor mobile devices, as battery technology has not kept up with the growing requirements stemming from ubiquitous multimedia applications. This paper addresses link adaptive transmission for maximization of energy efficiency rather than throughput. We extend our previous results for flat fading OFDMA to frequency-selective channels. Different from existing water-filling power allocation schemes that maximize throughput subject to overall transmit power constraints, our scheme adapts both overall transmit power and its allocation according to the states of all subchannels and circuit power consumption to maximize energy efficiency. We demonstrate the existence of a unique globally optimal link adaptation solution and provide iterative algorithms to obtain this optimum. Simulation results show at least a 15% improvement in energy utilization when frequency selectivity is exploited.

Intelligent access network selection in converged multi-radio heterogeneous networks

Heterogeneous multi-radio networks are emerging network architectures that comprise hierarchical deployments of increasingly smaller cells. In these deployments, each user device may employ multiple radio access technologies to communicate with network infrastructure. With the growing numbers of such multi-radio consumer devices, mobile network operators seek to leverage spectrum across diverse radio technologies, thus boosting capacity and enhancing quality of service. In this article, we review major challenges in delivering uniform connectivity and service experience to converged multiradio heterogeneous deployments. We envision that multiple radios and associated device/infrastructure intelligence for their efficient use will become a fundamental characteristic of future 5G technologies, where the distributed unlicensed-band network (e.g., WiFi) may take advantage of the centralized control function residing in the cellular network (e.g., 3GPP LTE). Illustrating several available architectural choices for integrating WiFi and LTE networks, we specifically focus on interworking within the radio access network and detail feasible options for intelligent access network selection. Both network- and user-centric approaches are considered, wherein the control rests with the network or the user. In particular, our system-level simulation results indicate that load-aware usercentric schemes, which augment SNR measurements with additional information about network loading, could improve the performance of conventional WiFi-preferred solutions based on minimum SNR threshold. Comparison with more advanced network-controlled schemes has also been completed to confirm attractive practical benefits of distributed user-centric algorithms. Building on extensive system-wide simulation data, we also propose novel analytical space-time methodology for assisted network selection capturing user traffic dynamics together with spatial randomness of multi-radio heterogeneous networks.

Low-Complexity Energy-Efficient OFDMA

Energy efficient communications in wireless communications is very important as mobile devices are battery-constrained. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget, due to the RF power requirements for reliable communications over long distances. Our previous work in this area demonstrated significant energy savings in uplink cellular OFDMA transmissions, with iterative approaches maximizing the instantaneous bits-per-Joule energy efficiency. In this paper, we use a time-averaged bits-per-Joule metric to develop low-complexity schemes. Specifically, we obtain closed-form solutions for energy-efficient link adaptation in frequency-selective channels. We also derive closed-form approaches for the maximum arithmetic and geometric mean energy-efficient schedulers. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions.

Multi-radio heterogeneous networks: Architectures and performance

It is well-known that next generation (5G) wireless networks will need to provide orders of magnitude more capacity to address the predicted growth in mobile traffic demand, as well as support reliable connectivity for billions of diverse devices, which comprise the “Internet of Things.” While the industry is focused on a concerted effort to improve capacity of cellular networks, operators are increasingly using WiFi technology over un-licensed spectrum to relieve congestion in their networks. This paper argues that the trend towards integrated use of multiple radio access technologies (RATs) and networks, such as WiFi, will be essential for addressing the challenges faced by future 5G networks. In particular we expect that joint use of multiple RATs can yield beyond additive gains in user connectivity experience by exploiting the rich multi-dimensional diversity (e.g., spatial, temporal, frequency, load, etc.) available across multiple radio networks. We investigate such benefits through a case study on integrating WiFi with 3GPP heterogeneous networks. Our results show that intelligent integration of WiFi/3GPP radio networks can yield an additional 2-3x gains in system capacity and user quality of service, beyond what is achievable from independent use of both networks.