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5 g wireless systems

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The innovative and effective use of information and communication technologies (ICT) is becoming increasingly important to improve the economy of the world [1]. Wireless communication networks are perhaps the most critical element in the global ICT strategy, underpinning many other industries. It is one of the fastest growing and most dynamic sectors in the world.
The European Mobile Observatory (EMO) reported that the mobile communication sector had total revenue of €174 billion in 2010, there- by bypassing the aerospace and pharmaceutical sectors [2]. The development of wireless technologies has greatly improved people’s ability to communicate and live in both business operations and social functions.
The phenomenal success of wireless mobile communications is mirrored by a rapid pace of technology innovation. From the second generation (2G) mobile communication system debuted in 1991 to the 3G system first launched in 2001, the wireless mobile network has transformed from a pure telephony system to a network that can transport rich multimedia contents. The 4G wireless systems were designed to fulfill the requirements of International Mobile Telecommunications-Advanced (IMT-A) using IP for all services [3]. In 4G systems, an advanced radio interface is used with orthogonal frequency-division multiplexing (OFDM), multiple-input multiple-output (MIMO), and link adaptation technologies. 4G wireless networks can support data rates of up to 1 Gb/s for low mobility, such as nomadic/local wireless access, and up to 100 Mb/s for high mobility, such as mobile access. Long-Term Evolution (LTE) and its extension, LTE-Advanced systems, as practical 4G systems, have recently been deployed or soon will be deployed around the globe.
However, there is still a dramatic increase in the number of users who subscribe to mobile broadband systems every year. More and more people crave faster Internet access on the move, trendier mobiles, and, in general, instant com- munication with others or access to information. More powerful smart phones and laptops are becoming more popular nowadays, demanding advanced multimedia capabilities. This has resulted in an explosion of wireless mobile devices and services. The EMO pointed out that there has been a 92 percent growth in mobile broadband per year since 2006 [2]. It has been predicted by the Wireless World Research Forum (WWRF) that 7 trillion wireless devices will serve 7 billion people by 2017; that is, the number of network-connected wireless devices will reach 1000 times the world’s population [4]. As more and more devices go wireless, many research challenges need to be addressed.

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5 g wireless systems

  1. 1. A HETEROGENEOUS WIRELESS BACKHAUL NETWORKS USING MASSIVE MIMO AND MOBILE FEMTOCELLS Presented by P.SAI KIRAN KUMAR(13751D6107) M.Tech, Communication Systems SITAMS.
  2. 2. Agenda  AIM  HETEROGENEOUS NETWORKS ?  ARCHITECTURE  KEY 5G WIRELESS TECHNOLOGIES  BACKHAUL TRAFFIC MODELS  CENTRAL SOLUTIONS  DISTRIBUTION SOLUTIONS  ENERGY EFFICIENCY OF BACKHAUL NETWORKS  ADVANTAGES  AIM  HETEROGENEOUS NETWORKS ?  ARCHITECTURE  KEY 5G WIRELESS TECHNOLOGIES  BACKHAUL TRAFFIC MODELS  CENTRAL SOLUTIONS  DISTRIBUTION SOLUTIONS  ENERGY EFFICIENCY OF BACKHAUL NETWORKS  ADVANTAGES
  3. 3. AIM  ANY-BODY  ANY- THING  ANY-WHERE  ANY-TIME  ANY-HOW  ANY-BODY  ANY- THING  ANY-WHERE  ANY-TIME  ANY-HOW
  4. 4. HET NET ?  Heterogeneous networks: small cells within macro cells  Improve user data rate near the access point  Offload data from the macro cell to the small cell  Reduce transmit power (terminal and BS)  Flexible deployment in dense areas  Heterogeneous networks: small cells within macro cells  Improve user data rate near the access point  Offload data from the macro cell to the small cell  Reduce transmit power (terminal and BS)  Flexible deployment in dense areas 4G Backhaul 60 GHz Small Cell
  5. 5. ARCHITECTURE
  6. 6. KEY 5G WIRELESS TECHNOLOGIES  Based on the well-known Shannon theory  Bi is the bandwidth of the ith channel,  Pi is the signal power of the ith channel,  Np denotes the noise power.  Based on the well-known Shannon theory  Bi is the bandwidth of the ith channel,  Pi is the signal power of the ith channel,  Np denotes the noise power.
  7. 7. TO INCREASE CSUM (SYSTEM CAPACITY)  NETWORK COVERAGE  HETEROGENEOUS NETWORKS  MACRO CELLS, MICROCELLS  SMALL CELLS  RELAYS  MFEMTOCELL  NUMBER OF SUB CHANNELS  MASSIVE MIMO  SPATIAL MODULATION [SM]  COOPERATIVE MIMO  DAS  NETWORK COVERAGE  HETEROGENEOUS NETWORKS  MACRO CELLS, MICROCELLS  SMALL CELLS  RELAYS  MFEMTOCELL  NUMBER OF SUB CHANNELS  MASSIVE MIMO  SPATIAL MODULATION [SM]  COOPERATIVE MIMO  DAS  BANDWIDTH  CR NETWORKS  MM-WAVE COMMUNICATIONS  VLC POWER (ENERGY-EFFICIENT OR GREEN COMMUNICATIONS).
  8. 8. MASSIVE MIMO  Massive MIMO (also known as “Large-Scale Antenna Systems”, “Very Large MIMO”, “Hyper MIMO”, “Full-Dimension MIMO” and “ARGOS”)  In massive MIMO systems, the transmitter and/or receiver are equipped with a large number of antenna elements (typically tens or even hundreds).  Massive MIMO (also known as “Large-Scale Antenna Systems”, “Very Large MIMO”, “Hyper MIMO”, “Full-Dimension MIMO” and “ARGOS”)  In massive MIMO systems, the transmitter and/or receiver are equipped with a large number of antenna elements (typically tens or even hundreds).
  9. 9. Massive MIMO can increase the capacity 10 times or more  The capacity increase results from the aggressive spatial multiplexing used in massive MIMO Massive MIMO increases data rate  the more antennas, the more independent data streams can be send simultaneously. Massive MIMO can increase the capacity 10 times or more  The capacity increase results from the aggressive spatial multiplexing used in massive MIMO Massive MIMO increases data rate  the more antennas, the more independent data streams can be send simultaneously.
  10. 10. Massive MIMO can be built with inexpensive, low- power components  With massive MIMO, expensive, ultra-linear 50 Watt amplifiers used in conventional systems are replaced by hundreds of low-cost amplifiers with output power in the milli-Watt range  Furthermore, in massive MIMO systems, the effects of noise and fast fading vanish, and intracell interference can be mitigated using simple linear precoding and detection methods Massive MIMO can be built with inexpensive, low- power components  With massive MIMO, expensive, ultra-linear 50 Watt amplifiers used in conventional systems are replaced by hundreds of low-cost amplifiers with output power in the milli-Watt range  Furthermore, in massive MIMO systems, the effects of noise and fast fading vanish, and intracell interference can be mitigated using simple linear precoding and detection methods
  11. 11. Improved energy efficiency  Because the base station can focus its emitted energy into the spatial directions where it knows that the terminals are located Improved energy efficiency  Because the base station can focus its emitted energy into the spatial directions where it knows that the terminals are located
  12. 12. SPATIAL MODULATION  Spatial modulation, as first proposed by haas etal ..,  SM encodes part of the data to be transmitted onto the spatial position of each transmit antenna in the antenna array  signal constellation spatial constellation to increase the data rate INFORMATION BITS Log2(nb) log2(m) bits  NB = number of transmit antennas  M = size of the complex signal constellation diagram  Spatial modulation, as first proposed by haas etal ..,  SM encodes part of the data to be transmitted onto the spatial position of each transmit antenna in the antenna array  signal constellation spatial constellation to increase the data rate INFORMATION BITS Log2(nb) log2(m) bits  NB = number of transmit antennas  M = size of the complex signal constellation diagram
  13. 13.  SM is a combination of space shift keying (SSK) and amplitude/phase modulation  The receiver can then employ optimal maximum likelihood (ML) detection to decode the received signal  Spatial modulation can mitigate inter-channel interference,  inter-antenna synchronization,  and multiple RF chains  Multi-user SM can be considered as a new research direction to be considered in 5G wireless communication systems  SM is a combination of space shift keying (SSK) and amplitude/phase modulation  The receiver can then employ optimal maximum likelihood (ML) detection to decode the received signal  Spatial modulation can mitigate inter-channel interference,  inter-antenna synchronization,  and multiple RF chains  Multi-user SM can be considered as a new research direction to be considered in 5G wireless communication systems
  14. 14. CR NETWORKS  The CR network is an software defined radio technique  In CR networks, a secondary system can share spectrum bands with the licensed primary system  either on an interference free basis or on an interference-tolerant basis  The CR network is an software defined radio technique  In CR networks, a secondary system can share spectrum bands with the licensed primary system  either on an interference free basis or on an interference-tolerant basis
  15. 15. Interference-free CR networks  In interference-free CR networks, CR users are allowed to borrow spectrum resources only when licensed users do not use them  CR receivers should first monitor and allocate the unused spectrums via spectrum sensing and feed this information back to the CR transmitter  In interference-free CR networks, CR users are allowed to borrow spectrum resources only when licensed users do not use them  CR receivers should first monitor and allocate the unused spectrums via spectrum sensing and feed this information back to the CR transmitter
  16. 16. Interference-tolerant CR networks  In interference tolerant CR networks, CR users can share the spectrum resource with a licensed system while keeping the interference below a threshold  In interference-tolerant CR networks can achieve enhanced spectrum utilization the radio spectrum  Better spectral and energy efficiency.  In interference tolerant CR networks, CR users can share the spectrum resource with a licensed system while keeping the interference below a threshold  In interference-tolerant CR networks can achieve enhanced spectrum utilization the radio spectrum  Better spectral and energy efficiency.
  17. 17. MOBILE FEMTOCELL  It combines the mobile relay concept (moving network) with femtocell technology  An MFemtocell is a small cell that can move around and dynamically change its connection to an operator’s core network.  public transport buses, trains, and even private cars.  MFemtocells can improve the spectral efficiency of the entire network.  MFemtocells can contribute to signaling overhead reduction of the network.  the energy consumption of users inside an MFemtocell can be reduced  It combines the mobile relay concept (moving network) with femtocell technology  An MFemtocell is a small cell that can move around and dynamically change its connection to an operator’s core network.  public transport buses, trains, and even private cars.  MFemtocells can improve the spectral efficiency of the entire network.  MFemtocells can contribute to signaling overhead reduction of the network.  the energy consumption of users inside an MFemtocell can be reduced
  18. 18. VISIBLE LIGHT COMMUNICATION Office Lounge BedRoom Indoor Freespace Optics and/or Radio Home Gateway PLC cellular ADSL FTTH RL L B ridge (Mesh) radio Office Lounge BedRoom Indoor Freespace Optics and/or Radio Home Gateway PLC cellular ADSL FTTH RL L B ridge (Mesh) radio
  19. 19. GREEN COMMUNICATIONS  The increase of energy consumption in wireless communication systems causes an increase of CO2 emission indirectly  The indoor communication technologies are promising deployment strategies to get better energy efficiency  VLC and mm-wave technologies can also be considered as energy efficient wireless communication  The increase of energy consumption in wireless communication systems causes an increase of CO2 emission indirectly  The indoor communication technologies are promising deployment strategies to get better energy efficiency  VLC and mm-wave technologies can also be considered as energy efficient wireless communication
  20. 20. BACKHAUL TRAFFIC MODELS  BACKHAUL TRAFFIC MODEL IN CENTRAL SOLUTIONS  BACKHAUL TRAFFIC MODEL IN CENTRAL SOLUTIONS
  21. 21. central solution  S1 serves as a feeder for user data from the advance gateway to the MBS  X2 enables mutual information exchange among small cells  the aggregated backhaul traffic at the MBS is forwarded to the core network by fiber to the cell (FTTC) links  S1 serves as a feeder for user data from the advance gateway to the MBS  X2 enables mutual information exchange among small cells  the aggregated backhaul traffic at the MBS is forwarded to the core network by fiber to the cell (FTTC) links
  22. 22.  Uplink throughput of small cell THcentra small-up= 0.04 .Bsc centra . Ssc centra  Down link throughput of small cell: THcentra small-down = (1 + 0.1 + 0.04) . Bsc centra . Ssc centra Bsc centra is the bandwidth of a small cell Ssc centra is the average spectrum efficiency of a smallcell  Uplink throughput of small cell THcentra small-up= 0.04 .Bsc centra . Ssc centra  Down link throughput of small cell: THcentra small-down = (1 + 0.1 + 0.04) . Bsc centra . Ssc centra Bsc centra is the bandwidth of a small cell Ssc centra is the average spectrum efficiency of a smallcell
  23. 23. Uplink throughput of a macrocell THcentra macro-up = 0.04 . Bmc centra . Smc centra, Downlink throughput of a macrocell THcentra macro-down = (1 + 0.1 + 0.04) . Bmc centra . Smc centra, Bmc centra is the macrocell bandwidth Smc centra is the average spectrum efficiency of a macrocell Total backhaul throughput THsum centra = THcentra sum-up + THcentra sum-down. Uplink throughput of a macrocell THcentra macro-up = 0.04 . Bmc centra . Smc centra, Downlink throughput of a macrocell THcentra macro-down = (1 + 0.1 + 0.04) . Bmc centra . Smc centra, Bmc centra is the macrocell bandwidth Smc centra is the average spectrum efficiency of a macrocell Total backhaul throughput THsum centra = THcentra sum-up + THcentra sum-down.
  24. 24. BACKHAUL TRAFFIC MODEL IN DISTRIBUTION SOLUTIONS
  25. 25. DISTRIBUTION SOLUTIONS  the number of adjacent small cells in a cluster is assumed to be K. Spectrum efficiency Ssc Comp = (K – 1)Ssc dist Ssc dist is the spectrum efficiency of the small cell in the cooperative cluster  the number of adjacent small cells in a cluster is assumed to be K. Spectrum efficiency Ssc Comp = (K – 1)Ssc dist Ssc dist is the spectrum efficiency of the small cell in the cooperative cluster
  26. 26. uplink throughput of a cooperativesmall cell THdist small-up = 1.14 . Bsc dist . Ssc dist downlink throughput of a cooperative small cell THdist small-down = 1.14 . Bsc dist . (Ssc dist + Ssc comp). Bsc dist is the bandwidth of the small cell Total backhaul throughput THsum dist = K . (THdist small-up + THdist small-down). uplink throughput of a cooperativesmall cell THdist small-up = 1.14 . Bsc dist . Ssc dist downlink throughput of a cooperative small cell THdist small-down = 1.14 . Bsc dist . (Ssc dist + Ssc comp). Bsc dist is the bandwidth of the small cell Total backhaul throughput THsum dist = K . (THdist small-up + THdist small-down).
  27. 27. ENERGY EFFICIENCY OF 5G WIRELESS BACKHAUL NETWORKS  The energy consumption of cellular networks should include the operating energy and the embodied energy EOP = POP . Tlifetime POP is the BS operating power Tlifetime is the BS lifetime. BS transmission power PTX POP = a . PTX + b, a > 0 and b > 0.  The energy consumption of cellular networks should include the operating energy and the embodied energy EOP = POP . Tlifetime POP is the BS operating power Tlifetime is the BS lifetime. BS transmission power PTX POP = a . PTX + b, a > 0 and b > 0.
  28. 28. Simple model derivation  The MBS transmission power is normalized as P0 = 40 W radius r0 = 1 km.  The MBS transmission power with coverage radius r is denoted by PTX = P0 . (r/r0)α α is the path loss coefficient.  BS operating power with coverage radius r is expressed as POP = a . P0 . (r/r0)α + b. BS embodied energy = the initial energy + maintenance Energy, EEM = EEMinit + EEMmaint.  The MBS transmission power is normalized as P0 = 40 W radius r0 = 1 km.  The MBS transmission power with coverage radius r is denoted by PTX = P0 . (r/r0)α α is the path loss coefficient.  BS operating power with coverage radius r is expressed as POP = a . P0 . (r/r0)α + b. BS embodied energy = the initial energy + maintenance Energy, EEM = EEMinit + EEMmaint.
  29. 29. In Central Solution The System Energy Consumption Is  the energy efficiency of the central solution is defined as ηcentra = THsum centra /Ecentra system.  the energy efficiency of the central solution is defined as ηcentra = THsum centra /Ecentra system.
  30. 30. In the distribution solution, the system energy consumption  the energy efficiency of the distribution solution is defined as ηdist = THsum centra /Ecentra system.  the energy efficiency of the distribution solution is defined as ηdist = THsum centra /Ecentra system.
  31. 31. Default parameters
  32. 32. Throughput of wireless backhaul networks
  33. 33. Energy efficiency of wireless backhaul networks
  34. 34. Energy efficiency of wireless backhaul networks with respect to the path loss coefficient
  35. 35. CONCLUSIONS  5G networks are expected to satisfy rapid wireless traffic growth.  Massive MIMO, millimeter wave communications, and small cell technologies are presented to achieve gigabit transmission rates in 5G networks.  5G networks are expected to satisfy rapid wireless traffic growth.  Massive MIMO, millimeter wave communications, and small cell technologies are presented to achieve gigabit transmission rates in 5G networks.
  36. 36. THANK YOU

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