Interference Mitigation Techniques for Wireless Networks

doi:10.1017/9781316771655.012

11 - Interference Mitigation Techniques for Wireless Networks

from Part II - Physical Layer Communication Techniques

Published online by Cambridge University Press: 28 April 2017

Koralia N. Pappi and

George K. Karagiannidis

Edited by

Vincent W. S. Wong ,

Robert Schober ,

Derrick Wing Kwan Ng and

Li-Chun Wang

Show author details

Koralia N. Pappi: Affiliation:
Aristotle University of Thessaloniki, Greece
George K. Karagiannidis: Affiliation:
Aristotle University of Thessaloniki, Greece
Vincent W. S. Wong: Affiliation:
University of British Columbia, Vancouver
Robert Schober: Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Derrick Wing Kwan Ng: Affiliation:
University of New South Wales, Sydney
Li-Chun Wang: Affiliation:
National Chiao Tung University, Taiwan

Book contents

Get access

Summary

Introduction

Mobile broadband communications based on fourth generation (4G) Long Term Evolution (LTE) services are currently being deployed worldwide and are increasingly expanding across global markets, providing a user experience that was previously possible only through wired connections. The evolving fifth generation (5G) of wireless communication systems is expected to cope with a thousand-fold increase in total mobile broadband data and a hundred-fold increase in connected devices. It will also be required to overcome various challenges affecting current cellular networks, and provide higher data rates, improved end-to-end performance and coverage, low latency, and low energy consumption at low cost per transmission [1]. These challenges are expected to be addressed in 5G wireless networks by adopting a multi-tier heterogeneous architecture, since the capacity of the current macrocellular network cannot be increased infinitely. Future mobile networks will comprise macrocells and small cells, relays, and device-to-device (D2D) links, while they will be accessed by a large number of smart and heterogeneous devices.

This chapter discusses the management of interference in wireless networks of the 5G era. In the following, the goals of 5G networks and the interference management challenges they pose are first presented. Furthermore, the characteristics of future mobile networks which offer new tools for combating interference are also summarized. In this framework, coordinated multipoint techniques for both the uplink and the downlink are revisited, with special focus on the improvement of the cell-edge user experience. Finally, two indicative techniques for interference management are discussed, namely interference alignment and the compute-and-forward protocol.

The Interference Management Challenge in the 5G Vision

The 5G Primary Goals and Their Impact on Interference

The advance from 4G to 5G networks is based on some primary visions and goals, which are summarized in the following [2]:

• High data rates and low latency. 5G networks are envisioned to enable data rates of 300 Mb/s and 60 Mb/s in the downlink and uplink, respectively, and end-to-end latency between 2 and 5 milliseconds.
• Machine-type communications (MTC). The Internet of Things (IoT) is expected to introduce a large number of self-organized MTC devices, such as home appliances, and surveillance and sensor devices.

Information

Type: Chapter
Information: Key Technologies for 5G Wireless Systems , pp. 214 - 235

DOI: https://doi.org/10.1017/9781316771655.012 [Opens in a new window]

Publisher: Cambridge University Press

Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Book purchase

Temporarily unavailable

References

[1] Ericsson,“5G radio access, research and vision,” White paper, Jun. 2013.

[2] E., Hossain, M., Rasti, H., Tabassum, and A., Abdelnasser, “Evolution toward 5G multi-tier cellular wireless networks: An interference management perspective,” IEEE Wireless Commun., vol. 21, no. 3, pp. 118–127, Jun. 2014.Google Scholar

[3] N., Bhushan, J., Li, D., Malladi, R., Gilmore, D., Brenner, A., Damnjanovic, R. T., Sukhavasi, C., Patel, and S., Geirhofer, “Network densification: The dominant theme for wireless evolution into 5G,” IEEE Commun. Mag., vol. 52, no. 2, pp. 82–89, Feb. 2014.Google Scholar

[4] China Mobile Research Institute, “C-RAN: The road towards green RAN,” White paper, ver. 2.5, Oct. 2011.

[5] B., Bangerter, S., Talwar, R., Arefi, and K., Stewart, “Networks and devices for the 5G era,” IEEE Commun. Mag., vol. 52, no. 2, pp. 90–96, Feb. 2014.Google Scholar

[6] M., Sawahashi, Y., Kishiyama, A., Morimoto, D., Nishikawa, and M., Tanno, “Coordinated multipoint transmission/reception techniques for LTE-Advanced [Coordinated and distributed MIMO],” IEEE Wireless Commun., vol. 17, no. 3, pp. 26–34, Jun. 2010.Google Scholar

[7] D., Lee, H., Seo, B., Clerckx, E., Hardouin, D., Mazzarese, S., Nagata, and K., Sayana, “Coordinated multipoint transmission and reception in LTE-Advanced: Deployment scenarios and operational challenges,” IEEE Commun. Mag., vol. 50, no. 2, pp. 148–155, Feb. 2012.Google Scholar

[8] J., Lee, Y., Kim, H., Lee, B. L., Ng, D., Mazzarese, J., Liu, W., Xiao, and Y., Zhou, “Coordinated multipoint transmission and reception in LTE-Advanced systems,” IEEE Commun. Mag., vol. 50, no. 11, pp. 44–50, Nov. 2012.Google Scholar

[9] V., Jungnickel, K., Manolakis, W., Zirwas, B., Panzner, V., Braun, M., Lossow, M., Sternad, R., Apelfrojd, and T., Svensson, “The role of small cells, coordinated multipoint, and massive MIMO in 5G,” IEEE Commun. Mag., vol. 52, no. 5, pp. 44–51, May 2014.Google Scholar

[10] R., Irmer, H., Droste, P., Marsch, M., Grieger, G., Fettweis, S., Brueck, H. P., Mayer, L., Thiele, and V., Jungnickel, “Coordinated multipoint: Concepts, performance, and field trial results,” IEEE Commun. Mag., vol. 49, no. 2, pp. 102–111, Feb. 2011.Google Scholar

[11] S. A., Jafar, Interference Alignment: A New Look at Signal Dimensions in a Communication Network, NOW Publishers, 2011.

[12] S. A., Jafar and S., Shamai, “Degrees of freedom region for the MIMO X channel,” IEEE Trans. Inf. Theory, vol. 54, no. 1, pp. 151–170, Jan. 2008.Google Scholar

[13] V., Cadambe and S., Jafar, “Interference alignment and degrees of freedom of the K-user interference channel,” IEEE Trans. Inf. Theory, vol. 54, no. 8, pp. 3425–3441, Aug. 2008.Google Scholar

[14] C., Suh and D., Tse, “Interference alignment for cellular networks,” in Proc. of Allerton Conf. on Communications, Control and Computing, Sep. 2008.

[15] A., Ghasemi, A., Motahari, and A., Khandani, “Interference alignment for the K user MIMO interference channel,” in Proc. of IEEE International Symposium on Information Theory (ISIT), Jun. 2010.

[16] S., Gollakota, S., Perli, and D., Katabi, “Interference alignment and cancellation,” in Proc. of ACM Special Interest Group on Data Communication (SIGCOMM), Aug. 2009.

[17] B., Nazer and M., Gastpar, “Compute-and-forward: Harnessing interference through structured codes,” IEEE Trans. Inf. Theory, vol. 57, no. 10, pp. 6463–6486, Oct. 2011.Google Scholar

[18] U., Erez and R., Zamir, “Achieving 1 2 log (1+SNR) on the AWGN channel with lattice encoding and decoding,” IEEE Trans. Inf. Theory, vol. 50, no. 10, pp. 2293–2314, Oct. 2004.Google Scholar

[19] S., Zhang, S., Liew, and P. P., Lam, “Hot topic: Physical-layer network coding,” in Proc. of ACM International Conf. on Mobile Computing and Networking (MobiCom), Sep. 2006.

[20] J. H., Conway and N. J. A., Sloane, Sphere Packings, Lattices and Groups, 3rd edn, Springer, 1998.

[21] C., Feng, D., Silva, and F., Kschischang, “Design criteria for lattice network coding,” in Proc. of 45th Annual Conf. on Information Sciences and Systems (CISS), Mar. 2011.

[22] C., Feng, D., Silva, and F., Kschischang, “An algebraic approach to physical-layer network coding,” IEEE Trans. Inf. Theory, vol. 59, no. 11, pp. 7576–7596, Nov. 2013.Google Scholar

[23] U., Niesen and P., Whiting, “The degrees of freedom of compute-and-forward,” IEEE Trans. Inf. Theory, vol. 58, no. 8, pp. 5214–5232, Aug. 2012.Google Scholar

[24] U., Niesen, B., Nazer, and P., Whiting, “Computation alignment: Capacity approximation without noise accumulation,” IEEE Trans. Inf. Theory, vol. 59, no. 6, pp. 3811–3832, Jun. 2013.Google Scholar

[25] A. S., Motahari, S. O., Gharan, M. A., Maddah-Ali, and A. K., Khandani, “Real interference alignment: Exploiting the potential of single antenna systems,” IEEE Trans. Inf. Theory, vol. 60, no. 8, pp. 4799–4810, Aug. 2014.Google Scholar

Accessibility standard: Unknown

Why this information is here

This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

Accessibility Information

Accessibility compliance for the PDF of this chapter is currently unknown and may be updated in the future.