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where is the upper bound on the mean of I /S, 2 is the upper bound on the variance of I /S, and is the density of the users per unit area, which is given by 2n = , 3 f rm rd = rm rd rm rd

exp[ / ] exp[ X / ] 2 exp[ / ] + Pc Pr 1 exp[ / ] 1

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modest increase in channel capacity. On the other hand, the upper bound of the channel capacity in a MIMO environment is given by CMIMO = min(n, m) BW log2(1 + SNR) where n is the number transmitter antennas and m is the number of receiver antennas. The channel capacity can now be increased in a linear fashion with the minimum of the transmitter and receiver antennas. Although this relation provides for an upper bound of the capacity, in practice, numbers very close to the upper bound are achievable. Many analog techniques have been utilized in the past to effectively combat multipath fading in a wireless system. These include simple antenna diversity selection or more sophisticated analog maximum-ratio-combining techniques using phase shifters or programmable delay elements. However, a true MIMO system (one where each receiver and transmitter antenna is connected to the baseband processor through a dedicated analog chain) provides for many advantages (Fig. 7.5). For example, phase shifting, combining, and beam forming can be performed easily at digital baseband on a persubcarrier basis in OFDM systems. Further, such a true MIMO system allows for spatial multiplexing, thereby increasing the channel capacity dramatically, as discussed earlier. On the other hand, such true MIMO systems consume more power and area than analog-only multiantenna solutions. The draft 802.11n standard combines the capabilities offered by OFDM coding along with those offered by multiple antennas. As a result, a MIMO OFDM system is constructed which offers diversity gain as well as

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5: R sum s .........................................117 Do I even need a r sum ........................118 Avoiding the biggest r sum mistakes ........120 Too long .............................................120 Too short ............................................121

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US dollar, which supported the price of oil (denominated in US dollars) and encouraged Americans to buy relatively cheap imports from Asia Between 2000 and 2007, US Treasuries owned by foreign investors rose from $1 trillion to $24 trillion China alone increased its holdings of US Treasuries from $60 billion in 2000 to $478 billion in 20075 In other words, there was an implicit agreement on a global recycling process By consuming massive amounts of imported goods and oil, the US ran huge trade de cits, which resulted in large trade surpluses with oil producers and Asian exporters These two groups of countries then recycled most of these surpluses back to the United States by investing in US Treasury securities This global recycling process kept the rates on long-term Treasury bonds approximately 1 percent lower than they otherwise would have been.

6 The role of the Federal Reserve in elevating US housing prices is more complex In response to the 2001 recession resulting from the burst of the dot-com bubble and the September 11, 2001 terrorist attacks on the World Trade Center, the Fed aggressively lowered the interest rate on short-term US Treasuries (eg, one week to three months), which declined to almost 1 percent at the end of 2002 The Fed then held the short-term rate close to 1 percent until the middle of 2004 Concerned about the fragility of the economic recovery, the Fed held interest rates too low for too long Only toward the very end of 2006 did the Fed bring the short-term interest rate back to normal levels7 To see how far the Federal Reserve suppressed interest rates during this period, consider Figure 12.

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